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Commodities, the Decade Ahead: 2020 – 2030 Your guide to earning profits (and avoiding losses) from trading the 43 most liquid commodities David J. Howden, Ph.D.
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Copyright © 2020 by David J. Howden All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electrical or mechanical, including photocopying, recording oy by any information storage or retrieval system, without permission in writing from the author. Inquiries should be addressed to David Howden, Ave. del Valle 34, Madrid, Spain, 28009, or electronically to [email protected]. Howden, David J. Commodities, the Decade Ahead: 2020 – 2030 / David J. Howden. ISBN 9781734911619 1. Business & Economics—Forecasting. 2. Investments & Securities—Commodities.
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Disclaimer Although the data found in this book have been produced and processed from sources believed to be reliable, no warranty, expressed or implied, is made regarding accuracy, adequacy, completeness, legality, reliability, or usefulness of any information. This disclaimer applies to both isolated and aggregate uses of the information. The information is provided on an "as is" basis. All investments, including equities and foreign exchange, are speculative in nature and involve substantial risk of loss. I encourage investors to get personal advice from a professional investment advisor and to make independent investigations before acting on information that I publish. Past performance is not necessarily indicative of future results. All investments carry risk and all investment decisions of an individual remain the responsibility of that individual. There is no guarantee that systems, forecasts, indicators, or signals will result in profits or that they will not result in losses. All investors are advised to fully understand all risks associated with any kind of investing they choose to do. Hypothetical or simulated performance is not indicative of future results. Unless specifically noted otherwise, all return examples provided in in this book are based on hypothetical or simulated investing. I make no representations or warranties that any investor will, or is likely to, achieve profits similar to those shown, because hypothetical or simulated performance is not necessarily indicative of future results.
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Contents Introduction ................................................................................... 5 Relative Valuation ......................................................................... 13 Period Forecasts............................................................................ 21 Cycle Analysis ...............................................................................29 A Historical Review of the Commodities .....................................39 Introduction to the Commodity Reports ...................................... 51 Commodity Reports ......................................................................57 Aluminum .....................................................................................59 Baltic Dry Index ............................................................................ 71 Canola ........................................................................................... 81 CBOE Volatility Index.................................................................. 91 Coal ............................................................................................. 101 Cobalt .......................................................................................... 113 Cocoa .......................................................................................... 125 Coffee .......................................................................................... 137 Copper ......................................................................................... 149 Corn ............................................................................................. 161 Cotton.......................................................................................... 173 Crude Oil: Brent .......................................................................... 185 Crude Oil: West Texas Intermediate .......................................... 197 Ethanol ........................................................................................ 209 Feeder Cattle ............................................................................... 221 Gold ............................................................................................. 233
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Heating Oil ................................................................................. 245 Iron .............................................................................................. 255 Lead ............................................................................................ 267 Lean Hogs .................................................................................. 279 Live Cattle ................................................................................... 291 Lumber........................................................................................ 303 Milk ............................................................................................. 315 Natural Gas ................................................................................. 327 Nickel .......................................................................................... 339 Oats ............................................................................................. 351 Orange Juice ............................................................................... 363 Palladium .................................................................................... 375 Palm Oil ...................................................................................... 387 Platinum ...................................................................................... 397 RBOB Gasoline........................................................................... 409 Rice ............................................................................................. 419 S&P GS Commodity Index ......................................................... 431 Steel ............................................................................................. 441 Silver ............................................................................................ 453 Soybean Meal .............................................................................. 465 Soybean Oil ................................................................................. 475 Soybeans ..................................................................................... 485 Sugar ........................................................................................... 497 Tin ............................................................................................... 509 Uranium ...................................................................................... 521 Wheat .......................................................................................... 533 Zinc ............................................................................................. 545 Ranking and Conclusion ............................................................ 557
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Audentis fortuna iuvat.  Virgil
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Introduction This book concerns itself with two questions. The first is whether the major exchangetraded commodities are presently under or overvalued. By this I mean whether they are priced at a discount or a premium compared to other goods that are available for purchase. The second question is more pressing for the investor. Given any discount or premium on the spot markets, what is the expected return that the investor can expect to earn by entering a commodity investment today? This return can be thought of in either an absolute (e.g., some percentage per year) or relative form (e.g., some percentage above a benchmark return). The absolute return is important to aid the investor in forming an expectation of what the return of a commodity will be, without reference to any other investment (e.g., will the price breakeven?). Even more relevant in many cases is the relative return: how well a specific commodity can be expected to perform against other commodities. This book sheds light on both these views. Determining whether a commodity will under or overperform other assets classes in the future depends critically not just on its current valuation, but also on its valuation at some future date in time. In turn, these valuations can be described in the absolute sense and a relative sense. In the former case, I am concerned with the question of whether the price of a specific commodity trades at a discount or premium compared to its historical norms. In the latter case the discount or premium is relative to other commodities. Answering these questions is difficult enough for the spot price, and the search for a method of determining the future valuation is somewhat like the “Holy Grail” of investment analysis. This book provides a method not only to comment on present prices but also on the prices I can expect to see prevail on the futures markets. The problem of estimating the current discount or premium on a commodity and of estimating the future return from holding it is eased by approaching the problems in two ways. In economic and financial analysis all variables are categorized as being either stocks or flows. A stock variable is one that exists at a moment in time. It is usually reported on a balance sheet, and includes items like assets or liabilities, but also such variables as the rate of unemployment or the price level. In contrast flow variables occur over some period. These are typically reflected on a statement of cash flows, and include items such as revenue and expenses, but also variables such as the rate of inflation or the trade balance. In the latter cases the flow variables are all expressed for some period, typically over a year. In the former case I see the stock variables existing irrespective of any period. This book takes the approach that the market is generally quite efficient at pricing commodities, though waves of under and overvaluations appear periodically. There are
6  David J. Howden strong economic forces aligning various prices with each other and mispricings, in the sense of a commodity selling at a discount or premium to other commodities, cannot last indefinitely. Basic economic reasoning explains why: any commodity selling at a premium will entice firms to look for a substitute that is more cost effective and entice a greater number of producers to supply the good at a profit. The result of this process is a diminution of the premium back to some “fair” value level more closely aligned with the prices that other commodities sell at. Consider a similar approach: the goldtosilver ratio. This ratio expresses the commodities’ prices in real terms: specifically, the number of ounces of silver it takes to buy one ounce of gold. Throughout history this price has oscillated around some median value. This backandforth nature of the price is most apparent since the early 1970s, when gold´s price was allowed to be set by market supply and demand conditions, but even in earlier periods one can see that its price was anchored in terms of silver.
Only rarely since 1900 has gold´s price neared or exceeded 80 ounces of silver. At each the six cases prior to today (1932, 193742, 199093, 2003, 2008, and 2016) the silver price of gold backed off, as a result of either the dollar price of gold falling or because of the dollar price of silver increasing. The immediate repricing of gold has typically been at a price of 60 ounces of silver, and often much less. To look at this from the other way ´round, only rarely has the price of gold dipped below 40 ounces of silver (most recently in 2011). In these cases where it has, eventually this price ventures higher because of a higher dollar price for gold or a lower dollar price for silver. The economic forces at play are obvious. To the degree that silver and gold are substitutable, either to traders or producers, a high price of gold in terms of dollars will motivate a shift into silver. This backandforth process takes some time, but the market
Commodities, the Decade Ahead  7 finds a way to eventually price each commodity at some fairvalue level with respect to the other. Since 1900 the average gold price has been 50 ounces of silver. (If one wanted to just focus on the period since 1972, when the price of gold could fluctuate freely, this figure increases to 60 ounces of silver.) This average price is not the fairvalue price of either commodity. The reason is that a fairvalue price will change over time as market and commodity specific factors that determine its price evolve. Changes to, for example, the tax code will change this price. One could imagine a regime that the government suddenly taxes silver advantageously to gold, and consequently the price of gold falls relative to silver. An industrial use for gold that cannot make use of silver could cause the fairvalue price of gold to surge. In sum, although the average gold price in terms of silver is helpful, it is not synonymous with its fairvalue price. Once a method to estimate whether a commodity is priced at a discount or premium is secured attention can be turned to forecasting its future price path. This is the flow variable and represents the largest challenge facing the investor. It also affects directly where he chooses to allocate his funds. There are several common approached that shed light on the future price path for a commodity. One wellcited insight looks at the general negative relationship between the interest rate on U.S. Treasury bonds of 10year maturity and the return to holding gold over the same period. Approximately onethird of the return to holding gold can be explained by looking only at Treasury yields, at least historically during the post1972 period. Using this approach yields an expected 10year annual return to holding gold of 15.5% (given the current 10year Treasury yield of 0.7%). This forecast is based on the historical relationship between the Treasury yield and gold´s subsequent return, extrapolated into the future from the current interest rate. Although understanding this relationship is a start, there are some significant problems with drawing conclusions from it. For starters, the relationship between Treasury yields and the return to gold is statistically significant, but quite weak. Only 31% of the variance in gold´s return is explained which leaves the other 69% unexplained. More importantly, there are some significant nonlinearities in the relationship. The negative relationship is quite strong when Treasury yields are under 10%, but at higher rates the relationship loses significance. The immediate problem is that the statistical relationship is not stable over time. This instability is reflected both in the sign of the relationship and its strength. While the overall period shows a weakly negative relationship between the two variables, the period since 2001 has shown an even more weak (R2 = 0.22) but positive relationship. There might be an important relationship between bond yields and gold´s (or any other
8  David J. Howden commodity´s) return, but identifying it is difficult. Even though the explanatory power of the relationship is low, it still yields important information about the plausibility of a forecast. Given the standard error of the relationship between Treasury yields and gold´s return I can make statements concerning the probabilities of a forecast, based on the historical relationship between the variables. Although probabilistic in nature, and with a large margin of error given the general lack of fit that my simple model of gold´s return has, this probability forecast is still a start and sheds light on the forecast´s plausibility. For example, there is only a 19% probability that the return to gold will be greater than 20.8% annually over the coming decade given the current yield on Treasuries. This 10year return was chosen because it was the highest that an investor could have earned on gold historically and resulted from a purchase made in August 2001 and sold in August 2011. It´s possible that buying gold today will provide a return comparable to the best alltime recorded return on holding gold, but given the historical relationship with Treasuries, it´s unlikely. What of the possibility that gold will return 6% annually over the coming decade? This figure is the lowest 10year return the yellow metal has yielded historically and occurred for an investment made in June 1980. The yield on 10year Treasury bonds that month was 9.8%. It is possible that gold could return a loss of 6% annually for the next ten years but given the statistical relationship between its price and bond yields, the probability is only 0.000006%. In other words, betting on such a drastic loss is not consistent with historical experience. Rather than looking at gold in terms of dollars, I can also think of its return relative to other commodities. This is already alluded to in the previous figure showing the price of gold in terms of silver. At 113 ounces of silver to the ounce, gold is more expensive today, at least according to this measure, than ever (our record of this ratio begins in 1791). The closest gold´s price has come to this high was between September 1939 and December 1941 when an ounce traded for 100 ounces
Commodities, the Decade Ahead  9 of silver, and September 1992 when it traded for 93 silver ounces. Given this extreme valuation in gold, what is a reasonable expectation for the future return on gold in terms of silver. While the answer to this question is highly uncertain, historical norms and patterns can shed light on what is likely to occur. Over the past 30 years, over 49% of the variance in the 5year return of gold in terms of silver, and 54% of the variance of the metal´s 10year return, have been explained by the goldtosilver ratio. By this measure, the best statistical forecast is that gold will decline relative to silver by 14% annually over the coming five years, and by 8% annually over the next decade. All periods where gold was worth near or more than 80 ounces of silver (January 1991: 97 silver ounces; April 2003: 80; October 2008: 77) have been associated with negative annual returns over the next five years (5%; 7%; 4%). Considering these historical facts, the negative return presently forecasted is not unusual, and the real value of the foregoing analysis is a look at the plausibility of a future event happening. We have created a very simple model based only on knowledge of the historical price action of gold and silver over the past 30 years. These three decades had their fair share of economic and financial bumps along the way, and the booms and busts add a robustness that a mundane period (economically speaking) would not provide. Given the standard error of my model, I can also calculate the associated probabilities that the forecasted event will happen. For example, the worst 5year return from buying gold and selling silver over the past thirty years was 13% annually and occurred over the period between February 1993 and February 1998. What is the probability that gold will perform as badly or worse than an 13% annual decline? About 65%, statistically speaking given the interactions between gold and silver over the previous thirty years. There is almost no chance (less than 1%) that gold is expected to breakeven against silver over this period. Now, it could be that the historical relationships between the two metals change moving forward, but it would take a significant change, as well as one that breaks from an even longerstanding tradition, to meaningfully affect the general thrust of this statistical analysis. Admittedly, this forecast of gold´s price in terms of silver is not very robust. Over the 301 5year periods since April 1990 the model only explains approximately half of the return variance. What is needed is a sufficient number of variables and their relationship with the price of gold (and each other) to be understood so that a larger majority of the return variation is explained. This is a difficult feat to achieve, complicated by the threat that I overfit the model and end up with a highly accurate description of the time period under analysis, but with little predictive capability of outofsample or future results. Ultimately, I need to understand the determinants of returns in the simplest terms possible, without including spurious factors that might compromise the statistical value of the results. This book tries to simplify the process for the investor. Instead of detailing the factors that are relevant for future security returns, I focus on the relationship between these factors and the subsequent return. I then complete the analysis by providing the forecasted returns and their associated probabilities so the reader can judge for himself how relevant and robust the statistical analysis is. The problem of estimating future returns is simplified by taking recourse in three simple ideas: 1) that the spot (or cash) price is efficient in that it incorporates all known and relevant information of the commodity into it, 2) that this spot price oscillates
10  David J. Howden between over and undervalued positions over long time periods, and 3) that the effect of these oscillations on the return of a commodity can be forecast with varying degrees of accuracy by looking at historical patterns. The first step – accepting that the spot price is “correct” in the sense that it incorporates the information necessary for price formation, is a standard component of price theory. The idea usually falls under the guise of the efficiency markets hypothesis (EMH) when applied to financial markets. In economics, EMH is an example of a theory that drives a wedge between academics and practitioners. Broadly stated, EMH implies that the price of a security at any given time will include all information which is known and relevant to that price. Simple enough. One implication of this is that no one investor can estimate better what the price should be other than the current price, at least not based on widely available information. Applied to financial assets, this implies that no individual can “beat the market”, since the market is already priced to include all relevant information. More properly understood, it is important to note that EMH does not imply that a price is correct. It only implies that the price includes all information that is currently available and relevant to it. It could turn out that the price is “wrong”, as it often looks with the benefit of hindsight, but this would not be known in the present given the current state of information. The use of EMH simplifies the forecasting problem somewhat because I can rely on technical price data to summarize the qualitative and at times tacit information that exists and is relevant for a commodity´s price. This second step, that the price always incorporates all information available and relevant to its formation, seems to conflict with the first step: the belief that commodity prices oscillate in valuation cycles over time. After all, how can a commodity´s price be “correct” if at the same time it meanders through periods of over and undervaluation? Remember that EMH only states that the spot price will incorporate all known information relevant for its formation. For several reasons, mispricings can still occur, though their cause will be unforeseen in advance, or alternatively these mispricings cannot be quantified in a way that can be acted on. The spot price cycles through periods of over and undervaluations caused by temporary mispricings, whereby investors don´t know what a commodity´s price should be, and the market undertakes a search process to unearth it. As investors bid on and sell commodities, prices rise and fall around the “correct” value. These valuation cycles also appear over longer periods. Here prices rise and fall due to changing information that concerns the market as a whole, e.g., prevailing interest rates or growth expectations. Mostly these price cycles are governed by the “money illusion” – waves of expectations that stem from central bank monetary policies that raise and diminish investor confidence and expectations over longer periods. Under this reasoning, the global equity indexes were “correctly” valued in early 2000 and late 2007. The same could be said of the commodity markets in 1974, or 2008. “Correct” in this sense refers to the fact that given all the information available at the time, including expectations about future interest rates, inflation, and optimism, investors actually did believe those lofty valuations to be reasonable. my emphasis on longterm secular cycles stems from central bank actions that skew important expectations concerning the future. By looking at the foundation of the skewed expectation – monetary policies constructed by the world´s major central banks – I can identify periods where commodities are over or undervalued relative to those counterfactual expectations that
Commodities, the Decade Ahead  11 would exist absent such policies. The belief that value reverts to a level consistent with real and reasonable expectations in the long term gives my relative valuation model a high degree of accuracy, especially over longer periods. The third step in the analysis is that these valuation cycles are probabilistically similar over time. It is commonly said that history does not repeat but it rhymes. In my view, the valuation cycles that commodity markets go through are not isolated events. They are related to each other and anchored by the continual search for true value. In this way, the price formation process – and by extension, the return from holding an asset – is no different for soybeans as it is for sweaters. In August of each year stores put winter clothes on display at high prices. As the season progresses retailers search for the true price of sweaters or, in economic terms, the marketclearing price. Although this simple example is easy to understand from basic supplydemand analysis coupled with the fact that it is easier for a retailer to lower a price than to raise it, the same method can be applied to the commodity market. Traders buy and sell commodities in a bid to seek out the marketclearing price. Along the way, central bank monetary policy skews expectations and places temporary pressure on the spot price, causing either a period of under or overvaluation. Eventually economic forces prevail and the price returns to its “marketclearing” or “correct” level. This book provides the method and results of one approach to estimate these mispricings in real time and produce forecasts of future returns based on this information. We end this introduction with a word of caution. The future is fundamentally unknowable with any exactness. At the same time, it is unreasonable to think that the future will not be related to the present or past in any way whatsoever. After all, how often have you read the following statements: 
Past performance does not guarantee future results. This time is different.
Since they are mutually exclusive, which statement is correct? The most defensible answer is that they are both partially correct. The past does not guarantee the future, but it provides a roadmap. This time is surely different than any other moment in history, but not completely so. The successful investor must balance these two philosophies. Today´s state of financial affairs is the result of decisions that were made in the past, dependent as they were on interest rates, advances in production technology, unemployed workers entering the workforce and a wide range of other real economic and financial factors. In all the forecasts that follow I list the associated probability of the event. These probabilities are based on historical experience. While not completely applicable to future events (since they are backward looking in nature) they give the investor a starting place to assess the likelihood of the future. Future returns concern outcomes of various likelihoods. Historical relationships don´t tell us the complete story, but they give us a foundation to differentiate between those events more likely to occur in the future and those that are less likely to occur. This book is not and should not be interpreted as investment advice. The investor´s propensity for risk, desire for exchange rate exposure, as well as local laws governing investments are all beyond the scope of the book. It is aimed solely at shaping expectations and providing a roadmap to navigate one potential coming decade.
12  David J. Howden In what follows I apply my general methodology to forecast the 43 most widely traded commodities around the globe. These commodities come from a wide array of sectors, from metals to softs. But before delving into these 43 commodity reports, I must overview briefly the three key components of my forecasting methodology: the measure of relative valuation, the 5 and 10year statistical forecasting process, and the use of historical valuation cycles to estimate when turning points in a commodity´s price will occur.
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Relative Valuation The foundation of my analysis is a measure I call “relative valuation.” With the benefit of hindsight that the future provides, it is apparent that certain past prices were overvalued while others were undervalued. Relative valuation allows us to get a feel for any over or undervaluation in the market not just retrospectively, but in real time. Consider the S&P 500 over the past thirty years. Almost certainly the investor considers the 1999 and 2007 highs to be overvalued. After all, the index collapsed by 40% after the August 2000 high, and 52% in the 16 months following October 2007. But when the investor says “overvalued” the question that should immediately spring to mind is “compared with what?” Furthermore, what is the magnitude of this supposed overvaluation? The measure of relative valuation answers both these questions.
Most investors have in mind a rapid runup in the market´s price as their preferred definition of overvaluation. Alternatively, they might think that a new lofty high that the market has not reached previously signals that a decline is at hand. By this definition, however, it is difficult to see how the S&P 500 was overvalued in late2007. The index
14  David J. Howden had only increased at an annual rate of 11% since the 2002 lows, making it the index´s slowest bull market in over a century. (By contrast, the bull market of 193237 witnessed a 33% annual gain!) The October 2007 high of $1,549 barely bettered the previous alltime high by $30, and even then, maintained it for barely two months. Yet despite the weakness of the advance and the fact that the index was hardly above where it had been nearly 20 years earlier, the market collapsed into a 53% loss. Likewise, the investor could consider the gold market. Since gold´s price was liberated in 1972 its price has had its share of ebbs and flows. In retrospect there were many great buying opportunities, and also times when the investor can now see that it would have been wiser to stay out of the market. Great value was found at the lows in the late 1990s and early 1970s. Between August 1999 and February 2008 the metal´s price increased by 281%. Add to that the 148% advance between October 2008 and August 2011 and one can see that superior performance was found by buying when the price was depressed. Likewise, the 541% gain between August 1976 and September 1980 showed, retroactively, that the metal was undervalued at the start of that advance.
Periods of overvaluation are a little more difficult to identify, but still there are some obvious examples. Buying gold at the September 1980 close would leave the investor at a loss until April 2008, nearly 27 years later. Taking a bird´s eye view, the August 2011 high of $1,814 looks to be another example of an overvalued market. Since the August 1999 low the metal´s price advanced 611%, just shy of 18% annually. Such returns are stellar for any market, and to have a bull market advance of more than a decade surely signals an overvalued market by the run´s end. Still, taking a longerterm look at the metal´s price history shows that the 2011 high was the culmination of a 31year advance since 1980 that resulted in a 2.5% annual gain. Looking at the advance in this way what seems to be a highly overvalued market from a shortrun perspective (or even decadelong perspective) could just be the gold market catching up to some extreme and
Commodities, the Decade Ahead  15 prolonged prior undervaluations. Relative valuation normalizes these market highs and lows relative to other prices in the economy. My prevailing philosophy is that all prices adjust over long periods of time to stay aligned with other prices. The underlying motive is similar to an arbitrage condition. If house prices increased faster than equity prices today, it must mean that the expected return from a real estate investment will diminish relative to equity investments. Investors working on a long enough time horizon will reallocate capital away from housing and into stocks, until their prices adjust to equilibrate their expected returns. The decision as to where to allocate his funds does not limit the investor to real estate versus equities. Bonds too are a potential investment, as is cash, gold, or any number of commodities. But note that the investor does not even have to invest at all. He could choose to consume his savings by buying consumer goods. If the price of a car were sufficiently cheap (relative to stocks) the investor would find himself behind a new steering wheel rather than navigating an enlarged portfolio of equities. Again, this process continues until the price of a car adjusts upwards so that its nonpecuniary return is equilibrated with the purely monetary return of the stock investment. The same arbitrage condition exists with respective to all other goods – both investments and consumer goods – that present themselves to the investor. In formulating the relative valuation measure I gauge the level of a commodity´s price against the price of a large basket of alternative goods that the investor could allocate his funds to. This includes real estate (both commercial and residential), bonds, oil, equities, and a wide array of consumer goods. In this way I can craft a measure that shows periods when a commodity´s price outpaces these other goods´ prices. The result is a market overvaluation. Alternatively, I can also measure periods where the commodity´s price fails to keep up with these other prices, or periods of undervaluation. When a commodity´s price is undervalued, i.e., low relative to other prices, it must “catch up” in the future, implying aboveaverage returns moving forward. Alternatively, when the commodity is overvalued, or expensive relative to other goods, its price must lag these other goods in terms of appreciation, or even fall. There are, however, reasons why some goods´ prices might not equilibrate with other prices, even over longer periods of time. Making interest on mortgages tax deductible, or taxing income earned from interest advantageously to other streams, are important changes that resulted in house and bond prices increasing relative to other goods´ prices. Alternatively, the movement to demonetize gold was a large force in permanently lowering its price relative to other goods (or at least doing so for a prolonged period). To deal with this challenge of regime change and the fact that there are various and varying reasons why prices might not be arbitraged, each valuation measure is calculated by considering the relationship between the value of the commodity and these other prices over the preceding 30year period. In other words, to make the claim that the price of gold is overvalued today by 20% is best interpreted as saying that gold is currently more expensive than it has been relative to these other goods over the past 30 years by 20%. (Note that gold could have always been expensive compared to these goods, but it is 20% more expensive now than it was on average in the past.) Likewise, at gold´s peak in August 2011 its price was overvalued by 83% relative to its average valuation against these prices for the preceding 30year period. Of course, during the thirty years following August 1981 the metal went through periods where it was quite cheap relative to other goods the investor could have purchased (1982, 1985,
16  David J. Howden 1993, and 1999), and other periods where it was quite expensive (1983, 1987, and 1996). But in 2011 gold´s price topped out at 83% more expensive than the average of all these episodes. In the analysis that follows, I never express relative valuation as a percentage variance away from an average previous valuation, but as a normalized zscore. Normalizing the measure as a zscore simplifies several matters and also introduces some complications. We´ll deal with the complications first. First, and most damningly, the average investor does not know what a zscore is, let alone how to interpret it. Statistically speaking, the measure is derived by way of the following equation: ݔെ ߤ ݖൌ ߪ where μ is the mean of the population and σ is the population´s standard deviation. The measure z represents the distance between a raw score x and the population mean μ in units of standard deviation σ. When a zscore is negative the value under examination is less than the population mean, and when it is positive it is higher. The relative valuation of a commodity can therefore be interpreted as the number of standard deviations above or below its fairvalue (or average) level. Admittedly, stating overvaluation in terms of standard deviations above the mean is somewhat more convoluted than stating it in pure percentage terms. (To state that gold´s price is currently +0.5 standard deviations above its longterm mean does not have quite the same ring as saying that “gold is overvalued by 20%.”)
Second, even if the investor does understand what a zscore is, he can´t use it in as direct a way as he could a simple percentage over or undervaluation measure. Gold is currently overvalued by 20%, or +0.5 standard deviations above its mean valuation.
Commodities, the Decade Ahead  17 Since the price of gold is $1,685, your average investor can probably piece together that its fairvalue price should be about onefifth less, or $1,400 to be exact. He would then not only know that the commodity is overvalued, but also by approximately how much. Using the zscore of +0.5 is a more contrived process. To come up with the fairvalue level of gold, the investor would need to know (in addition to the current price) the average of the fairvalue prices (μ) and their variance (σ). These drawbacks notwithstanding, what the zscore lacks in user friendliness it makes up for in analytical usefulness. First, since not all relative valuation measures explain the variance in the underlying commodities equally well, it is impossible to directly compare their relative valuations if expressed as percentages. For example, copper is currently undervalued by 29%, a significantly higher undervaluation than soybean meal (19%). In normalized terms, both copper and soybean meal are 0.9 standard deviations undervalued. There are three reasons for the discrepancy between the two undervaluations in their absolute (percentage) form and normalized (zscore) form. The first is that the valuation model for copper is more accurate than that for soybean meal (though debatably so given an adjusted R2 of 0.61 versus 0.55, though with a somewhat larger standard error of 0.38 versus 0.24). The fact that the goodness of fit of the copper valuation model is different from that of the soybean model makes it difficult to compare their results directly. Normalizing the results by way of the zscore permits the reader to not concern himself with the accuracy of the relative valuation model for a particular commodity, but instead focuses on its standardized results. Second, not all valuation models have equal averages and standard deviations. Over the previous 30 years, copper has been overvalued by an average of 7.2%, with a standard deviation of its valuation of 38.9. In contrast, soybean meal has averaged an overvaluation of 3.1% with a standard deviation of 25.8. The fact that copper has been overvalued by a larger margin when measured in percentage terms can be attributed to specific conditions in the copper market relative to all other markets that elevate its price as a normal course of affairs. The difference in standard deviations is related to the different goodness of fit that each model has. Normalizing the valuation measures allows the reader to directly compare those commodities that have different valuations as a result of normal conditions in their individual markets. Third, not all relative valuation measures can be applied across different time periods without difficulty. Keep in mind that I use a moving 30year period to calculate relative valuation in order to continually adjust for different economic conditions and legal regimes that might favor some prices over others. The last time gold was +0.5 standard deviations overvalued was in March 2006. That month the metal was actually16% undervalued. Keep in mind that the previous 30year period included a nearly 20year period of significantly undervalued prices (in fact, the whole of the previous 30 years was undervalued with the exception of the few years leading up to the 1980 highs). The fact that the previous period was so deeply undervalued on average explains why a market undervalued in absolute terms can still be overvalued when normalized. Just as in the former examples, here the difference is that the valuation model is more accurate for the 30 years between 1990 and 2020 than it was between 1976 and 2006. Again, the use of the zscore detracts from these accuracy considerations and allows the investor to compare them headtohead. (The valuation models for all 30year periods are all statistically significant at the 95% confidence level.)
18  David J. Howden Fourth and finally, the use of a zscore allows the reader to easily compute the percentage of time that a commodity´s price has been as over or undervalued as it is at a given level. This is possible because the relative over and undervaluations are approximately normally distributed, allowing for additional statistical analysis.
For the 360 monthly relative valuations since May 2020, about 40% have been approximately fairly valued, i.e., within ±0.6 standard deviations from the mean. Another 30% have been undervalued by more than 0.6 standard deviations, and the rest (26%) of the monthly periods have been overvalued by more than +0.6 standard deviations. As the histogram makes clear, most valuations are tightly grouped around the mean, and the average undervalued market is less extreme than is the average overvalued market. The fact that the relative valuations are approximately normally distrusted is most useful because I can compute many additional statistics directly from its zscore, for example, what percentage of time the market has been more over or undervalued than it currently is. Given that the price of gold is currently overvalued by +0.5 standard deviations, it is easy to state that this is more overvalued than 68% of all previous periods. Likewise, when gold was +3.1 standard deviations overvalued in September 1980, this implied that the market was more overvalued than more than 99% of all previous monthly periods. Despite superficially looking like a more complex and less applicable measure to express valuation than a pure percentage, the use of a relative valuation zscore allows for different markets to be compared across different time periods easily and without complication. A relatively overvalued market generally yields below average returns in the future and the reverse holds true for relatively undervalued markets. In fact, gold has gone through four valuation cycles since 1970, with each cycle being composed of a longterm
Commodities, the Decade Ahead  19 bull market and a correction in the form of a bear market. Each bull market moved the relative valuation of the metal higher, and these movements are somewhat consistent cycletocycle. Notwithstanding the fact that superior returns are found by investing in undervalued markets, the measure is not a panacea. For starters, the market can be overvalued for a significant time before a correction comes. By 2008 gold had become more overvalued (+3.8) than it had been since 1974. This fact notwithstanding the metal´s price continued to climb for three more years. The investor who sold his gold early may have avoided losses during post2011 collapse, but he also would have missed out on three of the most significant years of the largest bull market in the metal´s history. (Between October 2008 and August 2011 gold´s price increased by nearly 150%, or 38% annually.) Perhaps more important is that some largescale corrections have followed only minor overvaluations or, in some cases, undervaluations. Gold´s 42% decline after January 1983 was the deepest bear market until the 2008 correction. Yet the market in 1983 was actually somewhat undervalued at 0.2 standard deviations below its longterm average. Part of the explanation for the magnitude of the decline between 198385 is not that the market was significantly overvalued to begin with but that the decline brought the metal to deeply undervalued territory. The bear market ended in 1985 by being 1.7 standard deviations undervalued (cheaper, in other words, than 96% of all previous months). In other words, it´s not necessarily that the metal started from unusually lofty heights (gold´s price was, after all, still 25% lower than it was just three years earlier). Rather, the bear market´s severity can be explained by noting that the decline was unusually extreme. In other words, both the starting and ending relative valuations matter when sizing up the extent of a bull or bear market. This discussion might lead the reader to think that relative valuation is of little use to the investor. After all, it matters not whether the bear market is deep because the commodity was originally too overvalued or because it did not end until the commodity was extremely undervalued. A spade is a spade no matter whether you are looking at it from the top down, or the bottom up. Still, valuation swings that define bull and bear markets are somewhat predictable. Over the past five valuation cycles, the average bear market in gold has seen the metal´s relative valuation decreased by 4.6 standard deviations. Relative valuation is a useful tool that tells us much about how cheap or expensive a commodity is relative to other commodities, and relative to other times in its history. It also allows us to make estimates as to the end game for a given bull or bear market. It is not a sufficient measure, however, to judge the potential of all investment opportunities. Its real use, which I outline in the following chapter, is in forming the backbone of the models that forecast the return of a commodity over various time horizons.
20  David J. Howden
Commodities, the Decade Ahead  21
Period Forecasts Relative valuation sheds light on which commodities are undervalued relative to their historical norms, and by how much. The measure does little, however, to translate this information to anything other than a qualitative prospect at the commodity appreciating or depreciating in the future. In other words, it does not inform us about how much the commodity´s price will adjust moving forward. Period forecasts rectify this. Consider a simpler problem: the decision whether to buy a shirt. The decision is informed by some idea of what the current “valuation” of the shirt is, as signaled by its price. Is it over or underpriced relative to some historical standard? You could consider what shirts sold for last year, or maybe put the past prices in context by normalizing them relative to other goods´ prices. It´s one thing to know if you have a good deal on your hands or not, but the future price path is also important. If you suspected that shirts would go on sale for half off in a month´s time, you may well decide to wait to save some money. In terms of markets this is the same as expecting a commodity´s price to decline in the future and remaining on the side lines until better values materialize. Relative valuation is the single most important factor determining a commodity´s future return. The more deeply undervalued a commodity is in the present, the greater the chance will be that it will yield aboveaverage returns in the future. The problem in estimating the future return stems from not knowing at what price the commodity will sell for at a prospective date. There are two ways to approach this problem: one that tries to estimate the exact future value at the point when the commodity is sold, and another that assumes that the future sale is made at some fairvalue price. Both approaches have merits and drawbacks. The interest rate on a bond is a tool the investor can use to compare present and future values. With a riskfree rate of return of 10%, the investor can expect future prices to be 10% higher than those that exist today. The actual rate of return earned on a commodity investment is just another way of stating the difference between its future value (at the date when you sell it) and its present value (at the date you buy it). As a basis for estimating future returns, the riskfree interest rate is a good rule of thumb abstracting from risk factors and valuation swings. We can directly compare the yield on a bond of the same maturity as a prospective commodity investment. The bond´s interest rate determines the increase in your capital over the period, and it is known at the moment the investment is made. Coupled with the relative valuation of the commodity, I can make a statistical forecast to estimate the future return from a commodity investment. Of course, the statistical analysis requires that the relationships (both in terms of their signs and magnitudes) be constant over time, and I know that there is not necessarily a constancy in these relationships. Still, future
22  David J. Howden
Commodities, the Decade Ahead  23
valuations will not be completely unhinged from those of the past. As a starting point to understanding what type of returns are possible in the future, looking at the past is as good a point as any to begin. Consider the case of gold in August 1999. With the benefit of hindsight, we know that gold formed a major bottom that month, closing at $254.80. The yellow metal was not on too many people´s investment radars at the time. On the one hand, equity returns were quite buoyant during the final stages of the dot.com boom. On the other hand, gold had been a poor performer for several decades. In nominal terms that month´s close was the lowest price since May 1979, and in real terms it was still below its June 1972 peak. At the time, August 1999 did not exactly look like the greatest time to buy gold, at least not given the performance it yielded over recent memory at the time.
Rather than rely on a backwards look at the commodity´s performance to form an estimate for its suitability as an investment, using the relative valuation of the metal as the basis for a period forecast would have given the investor the opportunity to see how current conditions historically affected subsequent returns. Let´s see how it would have played out. First, let´s start with the relative valuation in August 1999. We already know that gold was priced well below its historical highs, and also that it had been for quite some time by the end of the millennium. At the very least there was wide agreement that gold had been in a bear market since the mid1980s, though really the yellow metal was in the doldrums since its alltime high in 1980. We also know that the next decade following this vantage point in 1999 would prove to be a historic bull market for the metal, increasing its price by nearly 300% by February 2008. Calculating the relative valuation of the metal at the time would have allowed the investor to see, in real time, just how undervalued it was and also allow him to compare it with other historical prices.
In August 1999 gold was undervalued by 1.2 standard deviations below its longterm average. This made it more undervalued that month than 89% of all previous months (with a price history dating back to December 1791). Indeed, the last time that gold was more undervalued was thirteen years prior, in July 1986. Still, although 1986 had the same relative valuation as 1999, their circumstances differed on one key respect. In 1999 gold reached this low 1.3 relative valuation by seeing its price fall over the preceding years. The 1986 low was actually a valuation high relative to the preceding years: by that date, gold´s price increased to be only 1.3 standard deviations undervalued from an even more undervalued position in late 1985. A more analogous case to gold in 1999 is October 1984. Here the valuation is the same, though in 1984 it was reached by a steady decline in both the metal´s price and valuation since the September 1980 high. The valuation of a commodity matters, but its context also matters, specifically whether the valuation is reached by becoming more overvalued or undervalued over the preceding years. If the investor had bought gold at the 1984 valuation low, he would have participated in a sizable bullmarket rally that lasted through late1987. The preceding was a specific case within the context of the metal´s longer history. I can generalize the importance of relative valuation on future returns and investment opportunities by taking recourse to historical statistical analysis. After all, the data set for gold starts in December 1791 meaning that by August 1999 there were 2,493 monthly periods with price and valuation data that allow us to see how the precious metal performed under similar previous scenarios. Statistically, each standard deviation that gold was undervalued by in August 1999 increased the subsequent 5year price return on the metal by 8.9% annually, statistically speaking. When I say “statistically” I mean it in the sense that over the preceding 30year period each standard deviation of undervaluation had that effect. Furthermore, the relative valuation measure explained 36% of the variance in the 5year returns between 19691999 (as per the model´s adjusted R2). If I stretch out time horizon out to ten years, I find that each standard deviation of undervaluation increased gold´s price by 6.5% annually and that relative valuation explained 67% of the subsequent 10year returns
24  David J. Howden from holding the metal. Based on this one variable (the relative valuation of the commodity) I could build a model forecasting the 5year return that would result from an investment made in August 1999. In the following diagram, the solid black line represents the 5year returns between August 1969 and August 1999. These 300 data points were all that were available when constructing this model in August 1999. The dashed grey line illustrates the forecasted return going forward based on these 300 months of history. The model predicted that by August 2004 gold would have gained 20% annually. I know now with the benefit of hindsight that this forecast would have been somewhat optimistic. Gold did advance, but only by 10% annually over the next five years. The solid grey line shows the actual 5year returns that would have been known in full only by August 2004.
The margin of error narrows as the forecast time horizon lengthens. Taking a 10year perspective in 1999 would have yielded a forecast annual return of 18.3% by August 2009. When the dust settled, the actual realized annual return that month was 14.1%. In general, since there is less volatility over longer time horizons, the accuracy of the forecasting model improves. At this point the reader may be unimpressed with the applicability of the model. It did correctly forecast an advance in the price of gold, but it had been doing so for some time before the price actually bottomed for both the five and tenyear time horizons. On the other hand, when the advance occurred it turned out to be somewhat weaker than expected. It would be perfectly reasonable to doubt the usefulness of the model given this dissonance. The reader should consider three points. First, keep in mind that the interest rate on 5year and 10year bonds was 5.8% and 5.9% in August 1999, and had hovered around that range throughout the mid to late1990s. Gold started outperforming government bonds in August 1998 over a 5year horizon, and in April 1997 for investors with a longer
Commodities, the Decade Ahead  25 10year outlook. Even though the price of gold did not bottom until August 1999, the return from holding gold was positive from a somewhat earlier date.
Second, consider the climate surrounding gold at the end of the 1990s. As an asset class it returned a negative yield for over 20 years and was not highly regarded. My period forecast model, though somewhat optimistic, was able to use past valuations to show that there was reason to be optimistic about the future of gold as an investment. Finally, I have looked at one commodity forecast in isolation of all others. One of the ways that the period forecasts shine is by comparing the expected return of various asset classes. By way of example, I can look at the model´s forecasts for another commodity at the same date. Unlike gold, August 1999 was not the bottom of a severe decline for sugar. The sweet commodity had declined throughout most of the late 1990s, but not to the same extent as the yellow metal and its correction would not be completed for about another year (by July 2000). In terms of relative valuation sugar was undervalued by 0.6 standard deviations (less extreme than gold). The resultant forecasts were 9.3% annually over the next five years, and 4.8% annually over the coming decade. When the dust settled, in August 2004 sugar had returned the investor 5.1% annually and if he held onto the investment until 2009 the soft would have returned an annual 13.5% return. Again, as was the case with gold, there is some margin of error with these forecasts. One of the strengths of these period valuations is that they allow the investor to find times when the commodity is prime for a trend reversal, as was the case in most commodities in the late 1990s. An extension of this strength is that the period valuations give the investor an ability to compare the options headtohead. The model forecast gold to be a superior investment to sugar over both time horizons, and history bore that fact out. My period forecasting models, both for five and ten years, use relative valuation as their basis. They also make use of several other financial and macroeconomic factors to form their forecasts of future returns. These models are probabilistic estimates in nature,
26  David J. Howden and they provide an objective grounding to form expectations of future commodity returns. Furthermore, while a variance from a forecast return will happen, this occurrence has a likelihood that can be quantified at various degrees of confidence given historical price behavior and data. I list the probability of each forecast so the reader can form his own confidence of an event´s likelihood. Forecasting the future return based on past data is not difficult but having a robust model that works well with outofsample data is. The primary problem encountered is that the price that the commodity will be in five or ten years when the sale is made is not known in the present. The return on the investment is as much a function of the selling price as it is of the purchase price. Relative valuation tells us much about how good a deal the present price is but does not inform us on the future selling price. Consider the following: the worst 5year period for gold since 1972 was an investment made in February 1980 (14.7% annually). This has much to do with the fact that the February 1980 closing high (i.e., the start of the 5year period) of $637 was not far off the actual bull market closing high made one month earlier ($850, the intraday high on 21 January 1980 was of course much higher yet). The terrible return also had to do with the fact that the February 1985 closing low of $288 was the end of a major decline. The metal´s price would not edge lower until August 1998. It takes two to tango – a buy and a sell price. In this case, the abysmal return was the product of a near record high price and a multidecade low. In a similar way, gold´s highest 5year return resulted from an investment made in September 1975. This was not an extremely undervalued month (the metal had tripled in price over the preceding three years), but five years later was the bull market high. The point I am trying to impress on the reader is that the future selling price is as much a determinant of the return as the present purchase price, and this creates a problem when trying to make a forecast today. I counter this problem by taking the weighted average of two forecasting models. First, I forecast what the return over the next five or ten years will be given the available returns from the preceding 30year period. Actual commodity data is the least biased estimate of future returns. Yet there are periods of extreme under or overvaluation where the historical data has difficulty estimating future conditions. This should make sense since most of the time the commodity is approximately fairly valued and it is only in relatively few cases that it becomes severely over or undervalued (twothirds of the time the commodity is within ±1.0 standard deviations of its longterm mean). The other model is constructed from nonmarket data. Instead of using as a basis the actual 5 and 10year returns from the previous thirty years, I derive the return that would have been realized if the commodity reverted to its fairvalue level (i.e., a relative valuation of 0) at the investment´s point of sale. This counterfactual investment return thus attributes all the return earned to the initial valuation of the investment and ignores an extreme valuation swings of the selling price (since the selling price is assumed to always be at its fairvalue level). For example, imagine buying gold in August 2006 at its market price of $623. Five years later the investor would have sold it at $1,813 and realized an annual return of 23.8%. Now imagine that gold did not rise to such a lofty valuation (+4.6 standard deviations above its longterm mean) but instead was fairly valued in August 2011. The investor would have received only $591 when he sold his investment in this case and would have realized a “fairvalue” return of 1.1%. This twist of fortunes is a good
Commodities, the Decade Ahead  27 illustration of the importance of the selling price in determining the commodity´s return. If gold had remained fairlyvalued the stellar return would have turned into a loss. From the vantage point of August 2006, the investor had no idea whether the commodity´s price would increase substantially or remain fairly valued by August 2011. To combat this problem, I make use of commodity data to discover historically what variables have been most able to forecast future returns robustly, both the actual and the counterfactual fair value. Each model is then weighted according to its explanatory power (adjusted R2) to provide the forecast given to the reader. This is done for both the 5year and 10year forecasts.
Each commodity report also contains a range of forecasts for the relevant period. This range is a function of both the raw forecast and the fairvalue forecast. The current 10year forecast for gold is an annual gain of 26.8%. The fairvalue estimate calls for a gain of 17.1% annually by April 2030. Historically, since April 1990, the actual forecast model has explained 65% of the variance in the 10year returns of the metal, and the fairvalue forecast model has explained 72% of the variance in the 10year fairvalue returns. The actual forecast I provide is the weighted average of these two estimates (21.7%) with a range of 17.1 to 26.8%. Generally, the tighter the range the more accurate both valuation models are. Each commodity report also illustrates the model graphically. The solid black line always represents the actual 5 or 10year returns of the commodity over the previous 30year period. The grey dashed line illustrates the forecast model so the reader can see how well it fits the past data, and also so that he can judge for himself the model´s prediction of the commodity´s future. I end this chapter with one final note on the use of the period forecasts. Historically, negative 5year returns have started to occur several years prior to the actual decline in the commodity´s price. For example, although gold topped in September 1980 the 5year return was negative as early September 1979. Any investment made after January 1992 yielded a negative 5year return notwithstanding the commodity topping four years later in January 1996. The peaks of both November 1987 and August 2011 were preceded by
28  David J. Howden negative 5year returns starting about a yearandahalf earlier. In other words, the commodity typically continues to rise even after it is priced to offer negative returns over the coming five years. Negative returns over ten years are the exception and not the rule. In fact, of the 460 10year periods since January 1972, only 128 of them (27.8%) have yielded negative returns in the price of gold. This nearly 50year history includes some severe and frequent economic disruptions as well as changes to the gold industry. Notwithstanding the plethora of industry opportunities and threats, and geopolitical calm and turmoil, the return to holding gold, especially over longer periods, meandered through a relatively small, positive band. In this sense, the longrun return to any commodity does not veer far from the anchor provided by inflation. And inflation, at least in the United States, has historically been quite stable and low.
In sum, forecasts for declines in the commodity over the coming 5year period typically presage actual corrections by several months, and forecasts of negative 10year returns only accompany the most significant bear markets.
Commodities, the Decade Ahead  29
Cycle Analysis The period forecasts given in this report are based on 5 and 10year time horizons. On the one hand these are purely arbitrary horizons, chosen mostly because of the ease of finding comparable bond yields necessary for both the valuation models and to compare the forecast returns to. On the other hand, the choice of the periods provides a common denominator to compare all commodities to. The average investor might not demand to hold his investment for this period, but at least it provides him with a means to proxy the return of one commodity relative to another over the holding period of his choice. In other words, if I forecast one commodity to outperform another over a five year horizon, a forecast made possible by using 5year bond yields in the valuation model, then it is also likely that this commodity will also outperform the other over a similar holding period, say four or six years. The forecast periods ignore the fact that sudden and unforeseen events can occur at any time and will disrupt the forecasts. The forecasts themselves are made by averaging out past returns over the same time horizon. Some of these horizons will have consisted exclusively of “normal” markets, without any sudden collapses or surges to the commodity prices either at the beginning or the end of the period. In fact, extreme valuations – both on the upside and downside – are exceptions to the markets and not the rule. The forecast periods take normal, or average, marketing conditions as their starting point and go from there. Still, markets do go through periods of extreme over and undervaluations. The investor can make use of average valuations and trends without difficulty, but he should still recognize that the market does not always follow such a finely tuned pattern. Doing so allows one to realize excess returns by accounting for both the periods of normal market activity as well as those more extreme periods. To shed light on how the investor can benefit from knowledge of nonnormal markets I include in each commodity report a section analyzing the cyclical nature of its price swings. Each commodity goes through price cycles including an appreciation and a depreciation of its price (a bull and a bear market). These cycles are never of the same length, but knowledge of them allows the investor to see what he can expect the average cycle to look like. It also allows him to see how the current cycle fits in the context of the historical norms, for example, whether a current bull market is short or longlived compared to past examples, or how much further in a cycle he can reasonably expect the price to move given the commodity´s history. Although today each commodity is traded on an organized exchange, I have (where possible) augmented these official prices with market prices for as long a period as reliable statistics can be found. The result are very long data series that can be analyzed
30  David J. Howden statistically. For example, my data series for gold extends to the 18th century. Since December 1791 there have been 2,743 monthly periods to be analyzed, and for price and valuation cycles to be recorded. These data sets are invaluable at giving us a glimpse at past patterns in valuation, which we can then use as the basis for understanding how the present cycle fits into these historical precedents. On the one hand there are relatively few clearly repeating exact patterns. On the other hand, the analysis gives us bounds for the most extreme price swings and durations. There is also some strong repetition in one important area – the change in relative valuation over the commodity´s bull and bear market cycles. As a consequence, I can look at the longest or shortest historical extents to a commodity´s cycles to see how far along its current bull or bear market it is. And I can also look at how relative valuation evolved over previous periods so that an understanding of where a commodity´s price will move to in the future can be forecast. Let´s look at gold to see how these analysis works. Although my data set for gold starts in January 1791, for most of this period until today its price has been controlled, as was the case during the gold standard. It was only at the end of the Bretton Woods period in 1971 that the price could be said to swing freely as per supplydemand conditions. Still, in the leadup to the breakdown of Bretton Woods some significant pressures were building in the gold market forcing U.S. officials to change the official price of gold. Although the nominal price was controlled throughout its history, central bankers and government officials had no control over the real, or inflationadjusted price of gold. (Or at the least they had less control and, in any event, they did not explicitly target the real price.) Although I list nominal prices in my cycle analysis, I define the cycles in terms of real prices. This allows for a comparison across different inflation regimes including the deflationary period of the 1930s and the highly inflationary period of the 1970s.
Commodities, the Decade Ahead  31 Although many of the commodities covered within have a price history beginning prior to the 20th century, I include in the cycle analysis only the price history after 1900. There are three reasons for this. The first is simplicity as including the full price history adds additional cycles that serve to mostly inundate the reader with superfluous information. The extra cycles that including the 19th century would provide would be beneficial if doing so resulted in more robust analysis, but it is doubtful that this is the case. The second (somewhat related) reason is that the statistical analysis of the cycles is not very sensitive to additional data. The price and valuation norms are relatively stable across a limited number of cycles and adding more does not necessarily make for a more thorough, or statistically significant, analysis. Finally, one may object that including data from older cycles would include more situations with relatively unusual economic and political situations (e.g., wars, assassinations, treaties, bouts of deflation, etc.). The reader versed in history will immediately recognize that the 20th century alone has a plethora of these periods, including the two only truly global wars in history, assassinations of several key political leaders, the introduction of widespread trade and political treaties, as well as the obvious cases of hyperinflation and deflationary pressures (economic events that, at least in extreme form, were mostly absent in the gold standard era that existed before the 20th century). Gold is a special example, since it is one of the few commodities under examination that endured a period of fixed or managed prices by a central bank or governmental agency. Still, it is useful to use gold as an example of why real prices are a superior way to analyze price and valuation cycles. On 15 August 1971, the United States terminated unilaterally the fixed exchange rate between U.S. dollar and gold. This meant that for the first time the metal´s price was free to be set by supplydemand conditions. (Bretton Woods kept the price of gold tightly fixed since 1944, and in almost all of the prior years some form of gold standard existed to keep the metal price´s controlled by either a central bank or government.) One would think that there were no price cycles operative during this period when gold´s price was fixed and not subject to change. Such a conclusion is wrong once one understands that gold´s nominal price is relatively unimportant to its value relative to other investments, and that its real (inflationadjusted) price is relevant. By focusing on gold´s inflationadjusted price we can see that there were cycles occurring notwithstanding the stability in its nominal price. For example, between December 1934 and July 1970 gold´s real price fell by 65% even though its nominal price actually increased marginally, from $34 to $35 per troy ounce. This real price decline was caused by the fact that the general price index surged by 167% over the same period causing a constant price to decrease relative to the other increasing prices. The bull market from August 1976 to September 1980 of 541% was roughly twice the size of the one that lasted from August 1999 to February 2008, at least in nominal terms. Adjusting these advances to real terms shows a 286% advance in the case of the former, and a 202% advance in the case of the latter, only a twothirds difference. Using inflationadjusted prices allows for a more direct comparison across different inflationary periods. This is especially important in commodities that have a price history dating back over a century. It is also especially important since the primary reason behind swings in relative valuation is monetary policy at the hands of the central bank. Since changes to the supply of money are the prime driver of inflation, using real values allows the investor
32  David J. Howden to compare valuation cycles across different monetary policy regimes. Viewed this way, gold has undergone five complete bullbear market cycles since 1900. Each cycle consists of a significant appreciation in the price of gold, and a subsequent depreciation. The table below, which exists in all reports for the commodities covered, summarizes these price swings, and provides important summary data at the bottom.
The table documents the starting and ending dates of each phase of the cycle, as well as the monthly closing high and low prices that correspond to the phase´s beginning and end. These high and low prices are listed in nominal form, since those are the figures the reader will be most familiar with. The total real change in the price and the relative valuation at the start of the phase are documented also. In general, there is much tighter repetition in the bear market phases of the cycle. This is intuitive since the maximum extent of a bear market decline is a 100% loss, while there is no theoretical limit on the appreciation of a commodity´s price. Over the five bear markets in gold since 1900, the price has declined between 44% and 68% (in real terms). The spread in the bull markets is much wider by comparison, between 57% and 445%. There is not much exact repetition in the nominal changes in a commodity´s price across its cycles. The exercise does, however, give us a basis to see what types of movements occurred in the past. Over gold´s five cycles, the median appreciation has brought the yellow metal´s real price 296% higher, and the median bear market has decreased its real price by 65%. It´s possible that the next bear market in gold will see the metal decline by more than 68%, but this would make it the most extreme price
Commodities, the Decade Ahead  33 collapse in over 120 years. Likewise, the current bull market that started in December 2015 could result in a total advance of more than 445%, but this would set a new record. Records do get broken over time, but not regularly. The same insights hold true for an analysis of the durations of the bull and bear markets. To keep the table concise, I have not included the individual durations of the various cycle phases, but at the bottom of the table the median length of each phase is given. The shortest bull market in gold was just under three years (starting in February 1985). The longest came in at fourteenandahalf years starting in June 1920. These extreme durations are informative and help in setting expectations for the duration of the current phase, but the median value (4.4 years) might be more helpful in guiding the investor. The bottom of the table finishes by noting the median starting relative valuation of each cycle´s phases and, more importantly, the median swing in valuation. In general bull markets almost always start from negative relative valuations. The only exceptions to this rule are advances that start after corrections to very large and extremely overvalued markets. For example, the bull market in gold that started in November 2016 started from an overvaluation of +0.2 standard deviations. This rare occurrence followed the overvalued bull market peak of +4.6 standard deviations in August 2011 (the most extremely overvalued market since December 1974). Even though the gold market was technically overvalued in late 2016, it was from a much higher peak set during its previous bull market high. The median bull market sees its valuation swing by +3.7 standard deviations, and the median bear market erases 4.6 standard deviations of value. Every bull market shares in common an increase in its relative valuation, and usually within a relatively narrow band as signified by the difference between the maximum and minimum changes in relative valuation noted at the bottom of the table. Likewise, every bear market shares in common a decrease in its relative valuation as the correction progresses. These changes in relative valuation are the most dependably repeating measure of the extent of a cycle´s phase. A bull market starting from an extremely undervalued position may end with a less extreme undervaluation, notwithstanding the fact that the commodity has become more highly valued. For example, gold started its bull market in February 1985 undervalued by 1.7 standard deviations. This is the most extreme undervaluation in the metal since the analysis begins in 1900, and statistically makes it more undervalued than 96% of all other monthly closes. Over its bull market, gold increased its valuation by +1.2 standard deviations. This left the yellow metal still undervalued by the start of its next bear market in November 1987. In this case we can understand how a commodity might start a bear market undervalued (or a bull market overvalued) if its previous cycle was of an extreme nature. Using the median change in relative valuation guides us in determining whether this will occur. The final lines of the cycle summary section of the table have three values shaded in gray. These represent the most recent date and values of the commodity (June 2020, when this report was written). From here the reader can gauge how far along in its current cycle a commodity is, relative to the maximum, median and minimum values listed at the bottom of the table for all its cycles. Gold closed June 2020 at a price of a price of $1,779 meaning that it has advanced 55% since its November 2015 low. The median advance in gold is 296%, implying additional upside potential.
34  David J. Howden Likewise, the metal’s median valuation swing of +3.7 standard deviations is also far away from its current situation. Since the start of its current advance, gold has moved from being overvalued by +0.2 to +0.7 standard deviations. This +0.5 increase is still far below what can reasonably be expected given its past history. Finally, each table includes a summary forecast for where I think the present cycle is most likely to end in terms of timing, price, and relative valuation. These forecasts are based on the median values of the commodity’s cycles, applied to the values the commodity had at the start of its current phase. The median advance in gold has taken 4.4 years to complete, and when added to the current bull market’s start date of November 2015 yields a forecasted cycle end date of March 2021. The median gold bull market has seen its price increase by 296%, which implies an ending price for the current cycle of $4,205 when taken from the cycle’s starting price of $1,061. Finally, the median bull market in gold has seen its relative valuation gain +3.7 standard deviations of value. Since gold started overvalued by +0.2 standard deviations, I forecast it to end the present cycle overvalued by +3.9 standard deviations. This cycle analysis allows the reader to form a secondary opinion of the prospects for a commodity. Later these cycle forecasts are compared with the period forecasts for the coming five and ten years to build a greater understanding of where the commodity is in its present cycle. In this way, the investor can hone his investment approach and use market timing to improve his longterm results. Most commodities exhibit a strong degree of covariance. The timing and magnitude of their price cycles are not identical, but in general many experience boom and bust phases in synch with one another. This is especially true within groups of commodities, for example, the industrial metals or energy commodities. Almost all of the 43 commodities are in the early stages of multiyear bull markets. This tendency among the individual commodities is confirmed by the assessment of the S&P GS Commodity Index, and also by the Baltic Dry Index which closely correlates with many commodity trends. It is also confirmed by the forecast that the Chicago Board of Options Exchange´s Volatility Index, better known as the VIX, forecast to remain in a bear market for another three years. Declining volatility is one of the common features of most booms. Every one of the seven energy commodities covered herein is forecast to be in the very early stages of a bull market that uniformly started in March and April of this year. Of these, natural gas is likely to have the longest stretch of price increases left before it fulfils the price target to make this current bull market consistent with its other historical bull markets. We can also see that there are groups of energy commodities whose price cycles closely mirror each other. For example, heating oil, natural gas and coal all have bull markets with median durations of between 2.1 and 2.5 years. On the other hand, crude oil, and gasoline both have cycles of considerably longer median duration, between 6.9 and 7.7 years. This implies that their current bull markets should run much longer, with a forecast completion in 2027. With the exception of rice, which made a significant bull market peak in March 2020, the grains are all forecast to be in the midst of their own bull markets. Most of these are in the early stages, though some like canola, oats, and wheat, are further along in their price cycle advance. Corn should have the most upside potential, though since its median bull market is also of a somewhat longer duration (4.3 years) it is middling on an annualized basis. Some of the grains, such as oats, are much further along in their current
Commodities, the Decade Ahead  35 advance and have less upside potential, but since they are expected to complete their advance sooner are actually forecast to offer higher returns on an annualized basis.
Likewise, the ten industrial metals all look to have formed longterm bottoms earlier this year, apart from lead which looks to be in the late stages of its bear market with some
36  David J. Howden additional downside potential. Owing to its high historical volatility and its relatively short price history under consideration, uranium is forecast to have the most significant bull market ahead of it. Most of the industrial metals are forecast to more than double in price before they complete their current advances. The meats are a bit of a mixed bag. Milk is in the very late stages of its bull market, having already exceeded its median price target. Hogs still have some room to fall to make their bear market consistent with others throughout history. Cattle, both live and feeder, are both analyzed independently of one another and are both expected to continue upward before completing their respective bull markets in mid2026. The precious metals have been fairly uncorrelated over the past couple years. Palladium has continued its bull market that has been in motion since 2002, and which really picked up steam in 2016. It has continued higher making new alltime highs before peaking in February of this year, and now looks to be set for a largescale decline. Gold has been performing well since 2015 and is closing in on its alltime high set in 2011. In contrast silver, which normally moves closely with the yellow metal, has been flat for the past five years. Although strong, gold´s advance is still far below what one can expect given its historical performance over its bull market cycles. Silver looks poised for a large multiyear advance as it starts its bull market. Platinum has performed the worst of the group, having been in continual decline since 2011. Like silver, it too looks poised to start a major advance that should continue for the next twoandahalf years. The softs all look ready to push higher over the next three years to complete their own bull market phases. Cotton, lumber, and sugar are all forecast to peak sometime in mid2023. Cocoa and coffee formed their cycle lows more than a year ago and are both further along to completing their highs. Of the lot, cocoa looks set to offer the best annual return. To put all of the 43 commodities on an even footing for ease of comparison, I rank them according to the annualized return they are expected to yield in order to fulfil their current cycle phase. The median commodity is amid a bull market that should top in May 2023. The median return calls for a little more than a doubling from its present price, which translates to a 31% annualized return. At first glance, many of the median annualized expected returns seem quite farfetched. There are two considerations to keep in mind. The first is that the annualized rates of return over just the bull market phases of the various commodities are, by nature of the fact that they include only positive years, quite high. Across its five bull markets since 1900, gold has had a median annual return of 18%. During its 197680 bull market the annual return reached 56%! Nor are the high annual returns during gold´s bull markets an artifact of its price being fixed for so long, and the accompanying pent up pressure that culminated in the 1980 highs. Wheat, the commodity with the next highest expected annual return, has historically returned even higher yields than gold. With a median annual return of 24% across its six bull markets since 1900, the common grain easily beats gold´s median return. The wheat bull market of 1914 to 1917 resulted in an annualized return of 44%. Cobalt´s median annual return during bull markets has been 62%. It´s bull market of 200204 returned the investor 382% on an annual basis. The other commodities follow a somewhat standard pattern with high annualized returns over their bull markets. The second reason why the reader should not be so surprised with the high annualized returns expected of many commodities as they complete their current bull markets is that
Commodities, the Decade Ahead  37 many commodity advances do not happen as smooth linear events. More commonly the price meanders for a time before surging to complete the cycle. Most cases of the commodities with exceptionally high expected annual returns are cases where the trend is already running long and consequently needs a short price spike to fulfil both its price and time targets. (All of the five highest expected annual returns belong to commodities that have been trending higher in their bull markets slowly for over a year already.) Commodities, annualized return ranking
Trend Gold Up Wheat Up Cobalt Up Uranium Up Cocoa Up Soybean Oil Up Scrap Steel Up Natural Gas Up Sugar (No. 11) Up Coal (Newcastle) Up Palm Oil Up Oats Up Orange Juice Up Cotton (No. 2) Up Soybeans Up Baltic Dry Index Up Heating Oil Up Corn Up Coffee Up Platinum Up Soybean Meal Up Median Commodity Up Silver Up Zinc Up Tin Up Aluminum Up Copper Up Ethanol Up Crude Oil (Brent) Up Feeder Cattle Up RBOB Gasoline Up Lumber Up Live Cattle Up S&P GS Commodity Index Up Crude Oil (West Texas Intermediary) Up Iron Ore (62% Fe) Up Milk (Class III) Topping Bottoming Lean Hogs Lead Bottoming Rough Rice Down CBOE Volatility Index Down Palladium Down Canola Up Nickel Up
Trend Start Date
Trend End Date
Median Real Real Return Trend Return Remaining, Duration, years Remaining, % Annualized %
Dec15 Aug16 Jul19 Nov16 Apr19 Apr20 Feb16 Mar20 Apr20 Apr20 Apr20 Feb16 Oct19 Mar20 Sep18 Jan20 Apr20 Apr20 Apr19 Mar20 May20 Mar20 Mar20 Mar20 Mar20 Apr20 Mar20 Apr20 Apr20 Apr20 Mar20 Mar20 Jun20 Mar20 Apr20 Jul19 Apr20 May19 Jan18 Jun20 Mar20 Feb20 Sep14 Mar16
Mar21 Mar21 Aug21 Jun22 Dec21 Oct21 Jan22 Sep22 Aug23 May22 Aug22 Mar22 Mar22 May23 May22 Mar22 Oct22 Aug24 Aug25 Jan23 Jul23 May23 Jul26 Mar24 Mar25 Feb24 Jul24 Dec21 Dec27 Jun26 Feb27 Mar23 Apr26 Jul23 Jul27 Feb28 Nov23 Jul23 Nov23 Aug25 May23 Mar22 Sep16 Nov17
4.4 4.6 2.1 5.6 2.3 1.5 5.9 2.5 3.3 2.1 2.3 4.5 2.4 3.2 3.7 2.2 2.5 4.3 6.3 2.5 3.2 3.7 6.3 4.0 5.0 3.8 4.3 1.7 7.7 6.2 6.9 3.0 5.8 3.3 7.7 8.6 3.6 4.3 5.8 5.2 3.2 2.1 2.0 1.7
241 172 263 726 190 153 173 200 357 140 147 97 88 186 85 72 96 224 314 101 128 105 275 111 150 76 84 24 175 105 119 33 71 22 48 45 6 14 24 39 34 46 85 131
456 328 224 188 108 107 88 64 63 58 53 49 45 44 39 36 34 33 32 32 31 31 24 22 21 17 16 16 14 13 13 11 10 7 6 5 2 5 8 9 13 30 n.a. n.a.
Expected annual returns cannot be calculated for two of the 43 commodities: canola and nickel. This is because they have already run past the date when their advances should have ended to be consistent with the median duration of their preceding bull markets. In theory this would give them an infinite annual return as they need their prices to surge immediately to satisfy their price targets, but I prefer to categorize them separately as their current advances are problematic in some way (in that they are taking much longer than should be expected).
38  David J. Howden There are many factors that will affect future returns, but one way to look at the investment decision is qualitatively. Without reference to what the specific return is, the top five commodities are expected to yield far superior returns to the last five ranked. This amounts to saying that a portfolio of gold, wheat, cobalt, uranium, and cocoa can be reasonably expected to outperform a portfolio containing palladium, the VIX, rice, lead, and lean hogs. These latter five are all at the early stages of bear markets or their current bull markets are already running long in their legs. Cycle analysis is useful to form an anchor for how “normal” bear and bull markets unfold, as told by the median time, price and valuation targets of the previous advances and declines since 1900. It is not, however, the only tool at our disposal. We also have the statistical period valuation models which forecast returns over the coming five and tenyear periods. When used in conjunction, this additional tool can help confirm whether the cycle analysis seems correct or whether the forecast seems untenable. Besides this there is one additional tool available: the measure of relative valuation. This is the bedrock of the valuation models and tells us whether a given commodity is currently cheap or expensive by historical standards. It is also the most important variable determining the subsequent forecast return over any coming period. Taken together, the commodity´s relative valuation, forecasted return over the coming five or ten years, and cycle forecast combine to give the reader a solid footing on where the investment is in the context of its historical cycles, and as such guides him in forecasting how its price will perform over future periods. Each of the specific commodity reports combines all three of these tools to provide an overview of how I expect the various prices to unfold over the coming decade.
Commodities, the Decade Ahead  39
A Historical Review of the Commodities This report covers 40 commodities, from aluminum to zinc, as well as three commonly traded commodityrelated indexes. Before delving into the analysis of their past price performance, as well as their prospects, it is useful to gain a foundation of the commodity markets in general. Although there are many regional commodity exchanges specializing in local output, almost all major commodities are traded in London (the London Metal Exchange), New York and Atlanta (the Intercontinental Exchange), or Chicago (the Chicago Mercantile Exchange). Founded in 1877, the London Metal Exchange (LME) is the world´s premier hub for base metals. Due to its close relationship with the London Bullion Market, it is also a popular venue for trading precious metals. Since 2012 the LME has been owned by Hong Kong Exchanges and Clearing. Formed in 2000, the Intercontinental Exchange (ICE) now operates 12 financial and commodity exchanges, as well as six central clearing houses. Although it is best known as the owner of world´s largest financial exchange, the New York Stock Exchange, it entered the commodity world in 2001 with the purchase of the International Petroleum Exchange. The IPE was the main trading hub for Brent crude oil contracts, which serve as the benchmark for over twothirds of the world´s crude oil trades. It has since gone on to purchase the New York Board of Trade (2005), giving it control over the markets of many “softs”, as well as the Winnipeg Commodity Exchange (2007) allowing it access to the canola market. More recently, ICE has been at the forefront of emissions trading since its partnership with the Chicago Climate Exchange (2003) and later through its purchase of the European Climate Exchange (2010). Headquartered in Atlanta, ICE reported profits of $2.0 billion on annual revenue of $6.6 billion in 2019. Traditionally the hub of livestock trading owing to Chicago´s strategic location, the Chicago Mercantile Exchange (CME) has since gone on to become the world´s largest futures exchange. A series of mergers and acquisitions has made it the premier market maker for most of the world´s commodities. A 2007 merger with its historic rival, the Chicago Board of Trade, set in motion a series of acquisitions that would see the value of the CME quadruple in a twoyear span. The 2008 purchase of the New York Mercantile Exchange gave the CME access to several key energy markets. As important to its growth was the access to the world´s major precious metal trading hubs through NYMEX´s subsidiary the Commodity Exchange (COMEX). Although precious metals are traded widely throughout the world, COMEX remains the most important market for gold and silver contracts. Finally, the 2012 purchase of the Kansas City Board of
40  David J. Howden
Commodities, the Decade Ahead  41 Commodities, supply overview
Commodities, overview Commodity Contract Market Size Code Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
BDI VIX GI
BE CBOE CME
$1,000 X $250 X
USD USD USD
NCF B CL EH O NG RB
ICE ICE NYMEX NYMEX ICE NYMEX NYMEX
1,000 MT 1,000 bbl 1,000 bbl 29,000 gal. 1,000 bbl 10,000 MMBtu 42,000 gal.
USD/MT USD/bbl USD/bbl USD/gal. USD/gal. USD/MMBtu USD/gal.
RS C O CPO 14 06 07 S KW
ICE CBOT CBOT CME CBOT CBOT CBOT CBOT CBOT
20 MT 5,000 bu. 5,000 bu. 25 MT 2,000 cwt 100 T 60,000 lbs. 5,000 bu. 5,000 bu.
CAD/MT U.S. cents/bu. U.S. cents/bu. USD/MT U.S. cents/cwt USD/T U.S. cents/lb. U.S. cents/bu. U.S. cents/bu.
AH CO CA TIO PB NI SC SN UX ZS
LME LME LME COMEX LME LME LME LME NYMEX LME
25 MT 1 MT 25 MT 500 MT 25 MT 6 MT 10 MT 5 MT 250 lbs. 25 MT
USD/MT USD/MT USD/MT USD/MT USD/MT USD/MT USD/MT USD/MT USD/lb. USD/MT
62 HE LE DA
CME CME CME CME
50,000 lbs. 40,000 lbs. 40,000 lbs. 200,000 lbs.
US cents/lb. US cents/lb. U.S. cents/lb. USD/lb.
GC PA PL SI
COMEX NYMEX NYMEX COMEX
100 oz t 100 oz t 50 oz t 5,000 oz t
USD/oz t USD/oz t USD/oz t USD/oz t
CC KC CT LB OJ SB
ICE ICE ICE CME ICE ICE
10 MT 37,500 lbs. 50,000 lbs. 110,000 FBM 15,000 lbs. 112,000 lbs.
USD/MT U.S. cents/lb. U.S. cents/lb. USD/MFBM U.S. cents/lb. U.S. cents/lb.
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybean Wheat (Hard Red)
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
Livestock and Dairy Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
Since 1999
Since 2009
Change



China United States United States United States United States United States United States
2.8 1.4 1.4 25.1 n.a. 2.8 n.a.
1.4 1.6 1.6 6.1 n.a. 3.1 n.a.
1.4 0.2 0.2 19.0 n.a. 0.3 n.a.
Canada United States Russia Indonesia China China Brazil Brazil European Union
1.1 3.4 0.3 7.1 1.3 n.a. 3.4 4.3 1.1
2.8 3.3 1.3 5.4 1.3 n.a. 3.3 4.1 0.8
1.7 0.1 1.0 1.7 0.0 n.a. 0.1 0.2 0.3
China DR Congo Chile Australia China Indonesia China China Kazakhstan China
5.1 7.7 2.3 4.9 1.9 4.3 4.5 1.8 n.a. 2.5
5.6 6.9 2.3 1.3 1.5 7.0 4.4 2.1 0.0 1.1
0.5 0.8 0.0 3.6 0.4 2.7 0.1 0.3 n.a. 1.4
United States China United States European Union
1.4 1.5 1.4 1.8
1.2 1.6 1.2 1.6
0.2 0.1 0.2 0.2
China Russia South Africa Mexico
5.1 1.4 0.5 2.2
3.0 0.8 0.2 1.9
2.1 0.6 0.7 0.3
Ivory Coast Brazil China European Union Brazil India
3.1 2.2 1.5 0.5 1.1 1.8
2.1 1.9 0.7 2.2 0.9 1.1
1.0 0.3 0.8 1.7 0.2 0.7
Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index

Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybean Wheat (Hard Red)
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
Precious Metals
Softs Cocoa Coffee Cotton No. 2 Lumber Orange Juice Sugar No. 11
Largest Producer
Livestock and Dairy
Precious Metals Gold Palladium Platinum Silver
Annual Growth Rate
Pricing Unit
Gold Palladium Platinum Silver
Softs Cocoa Coffee Cotton No. 2 Lumber Orange Juice Sugar No. 11
42  David J. Howden Trade provided the CME with the dominant trading venue for hard red winter wheat, thus consolidating its grasp on the market (the CBOT has been the traditional exchange for soft red winter wheat). As a consequence of this flurry of acquisitions, the Chicago Mercantile Exchange Group is now owner of four of the world´s most important futures exchanges: CBOT, CME, COMEX, and the NYMEX. In addition to these commodities, CME also trades interestrate and foreignexchange futures. It is now the world´s major venue for bitcoin, and pioneered weather products (futures on rainfall, snowfall, hurricanes, and temperature) in 1999. Headquartered in Chicago, the CME Group earned $2.1 billion of profit in 2019 on annual revenue of $4.9 billion. Three indexes are included because of their importance to the world of commodities. Of these, only the S&P GS Commodity Index, a common benchmark for performance of the whole commodity market, is traded on one of the aforementioned exchanges (the CME). The Baltic Exchange (BE) has been, since 1744, an important source of news and prices for the maritime shipping industry. The Exchange tracks shipping rates by way of seven indexes made up of a suite of wet and dry timecharter and voyage routes. The most followed of these is the Baltic Dry Index, which is commonly seen as a bellwether index for the global shipping industry. Headquartered in London, the BE was bought by the Singapore Exchange in 2016. The benchmark gauge of market volatility is the Chicago Board of Options Exchange´s (CBOE) volatility index (VIX). Located in Chicago, the CBOE was the first exchange to list standardized, exchangetraded options on 26 April 1973. It has remained since then the United States´ largest options exchange. All commodities and indexes covered herein are priced in U.S. dollars, except for canola which is priced in Canadian dollars. Tracing its original market to Winnipeg, Canada, the yellow oilseed remains the only major commodity to be primarily priced in a currency other than U.S. dollars. (Many commodities have concurrent markets in multiple currencies, however.) Futures lot sizes vary considerably, though all are priced on a unitbasis regardless of their denomination of lot size. For example, notwithstanding the standard zinc future being traded in lots of 25 metric tons, the metal is priced on a per metric ton basis. In some cases, mainly with older agricultural commodities that started trading when the purchasing power of the dollar was considerably higher, prices are given in cents per unit. Cotton futures trade in lots of 50,000 pounds (approximately 23 metric tons), though are priced in U.S. cents per pound. Of interest to the reader are the main producing countries of each commodity owing to the correlated factors that stem from the supply side of the price´s determination. While in each commodity report that follows, I give a more detailed overview of these producers, I list here only the commodity´s largest country of origin. Eleven of the forty commodities have China as their largest producer. Nine others have production centered in the United States (mostly in the energy and livestock sectors). Some of the smaller, lower volume commodities are produced primarily in some less obvious places (cocoa in the Ivory Coast; uranium in Kazakhstan), but mostly it is the world´s largest countries that dominate production. The five largest countries in the world by landmass (Russia, Canada, China, the United States and Brazil) are the largest producers of 27 of the 40 commodities covered.
Commodities, the Decade Ahead  43 Growth rates in the supply of the commodity matter, as well as the evolution of this rate over time. To get a feel for the productionside of a given commodity, I include two output growth rates: the annualized growth rate since 1999 and 2009 (20 and 10 years, respectively). All commodities except oats have seen positive growth rates since 1999. Ethanol has grown the most rapidly, though admittedly from a small base. The world´s population has grown by 1.2% annually over both the last decade and 20 years. World population is one baseline that can be used to look at the change in demand. (Since the annual supply growth rates are in physical units, and not U.S. dollar terms, they should be compared with the growth in a similar real quantity, like the number of demanders.) Most commodities are growing by at least as much as the world´s population. This implies that there is a greater resource availability than there was both ten and twenty years ago or, what is the same, that the demand has grown less quickly than the supply. This phenomenon is especially true with the industrial metals and energy commodities. It is also true for the agricultural commodities, particularly the grains. The change between the 20year supply growth rates and those over 10 years is instructive as it points to where future supply changes are heading. If this change is negative, it means that growth rates over the previous decade were below those of the previous twenty years. Since supply changes happen, for most commodities, only slowly over time, it is reasonable to extrapolate these trends to point to the future supply conditions. Production of ethanol, for example, expanded incredibly quickly in the early and mid2000s. In 2007 alone the world´s production of the biofuel increased by 36%. Part of the explanation was growing demand as the world´s tried to wean itself off expensive petroleum, but also because production was nascent as recently as the late 1990s. As the market for ethanol develops and production increases, the high growth rates will fall as indicated by the large negative change between its 20year and 10year output growth. While most commodities are slowing in their production growth, keep in mind that the growth rates are positive in 39 of the 40 cases since 1999, and 38 of the 40 cases since 2009. There is no looming supplyside crunch. “Peak oil” is now an idea long discredited, and crude output has actually been increasing over the past decades as new production technologies make previous uneconomical reserves viable. Understanding the underlying supply and demand conditions are important in understanding future price pressures, but so too are the trading conditions surrounding a commodity. Liquidity matters when trading, and there are two ways that this can be measured. The first is through volume, which measures the number of futures contracts traded over a given period. The second is open interest, which reflects the number of contracts held by traders in active positions. Since open interest reflects all contracts that have not been closed out or expired, it will only decrease if buyers or sellers of contracts close out more positions than were opened in each period. Notional value refers to the actual dollar amounts of a contract traded. It is the product of the number of contracts traded at the given price per unit over however many units the contract trades for. In June 2020, for example, 16,970 futures contracts for coal (Newcastle delivery) traded on the Intercontinental Exchange. Each of those contracts specified 1,000 metric tons, at a price of $61 per metric ton. The resultant notional value of this futures was $1.035 billion. In general, the greater the monthly volume is, the more liquid the underlying commodity is. The commodity with the highest trading volume in June 2020 was gold. Over $787
44  David J. Howden
Commodities, the Decade Ahead  45
Commodities, trading statistics (as at monthend June 2020)
Commodities, trading statistics (as at monthend June 2020)
Monthly Volume
Open Interest
Monthly Volume
Open Interest
Contract Price* Size
Notional Value As % ($mn.) Supply
Contracts
As % Supply
Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
1,823 31 325
$1,000 X $250 X
n.a. 2,067 959
n.a. n.a. n.a.
n.a. 600 436
n.a. n.a. n.a.
1,070 108,043 78,336 4 25 23,038 17,763
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
61 41 39 1.22 1.25 1.75 1.20
1,000 MT 1,000 bbl 1,000 bbl 29,000 gal. 1,000 bbl 10,000 MMBtu 42,000 gal.
1,035 652,776 746,541 21 3,499 168,415 175,954
0 46 55 0 n.a. 68 n.a.
1,070 108,043 78,336 4 25 23,038 17,763
0 8 6 0 n.a. 9 n.a.
157,180 1,559,526 4,292 18,120 10,122 441,205 430,592 811,476 403,108
1,496 27,136 77 241 2 12,751 6,717 35,137 9,130
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybean Wheat (Hard Red)
476 3.48 3.58 533 0.12 289 0.26 8.66 4.53
20 MT 5,000 bu. 5,000 bu. 25 MT 2,000 cwt 100 T 60,000 lbs. 5,000 bu. 5,000 bu.
4,846 178,085 323 49 7 79,757 43,449 240,867 76,316
14 108 6 0 0 n.a. 140 218 62
1,496 27,136 77 241 2 12,751 6,717 35,137 9,130
4 17 1 1 0 n.a. 22 32 7
116 0 0 160 n.a. 644 5 n.a. 0 n.a.
232 59 213,325 2,807 n.a. 192,248 9,743 n.a. 322 n.a.
9 2 32,201 138 n.a. 14,753 26 n.a. 3 n.a.
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
1,602 28,500 6,038 98 1,788 12,790 264 16,847 32 2,056
25 MT 1 MT 25 MT 500 MT 25 MT 6 MT 10 MT 5 MT 250 lbs. 25 MT
116 0 0 160 n.a. 644 5 n.a. 0 n.a.
0 0 0 0 n.a. 2 0 n.a. 0 n.a.
9 2 32,201 138 n.a. 14,753 26 n.a. 3 n.a.
0 0 27 0 n.a. 43 0 n.a. 0 n.a.
179,978 1,046,164 997,269 40,571
11,609 20,505 36,699 178,512
36,744 225,597 275,039 22,489
2,370 4,422 10,121 98,952
Livestock and Dairy Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
1.29 0.49 0.92 22
50,000 lbs. 40,000 lbs. 40,000 lbs. 200,000 lbs.
11,609 20,505 36,699 178,512
6 16 27 1
2,370 4,422 10,121 98,952
1 3 7 1
100 oz t 100 oz t 50 oz t 5,000 oz t
4,427,274 23,542 350,424 1,846,699
787,612 4,548 14,473 167,957
561,628 7,080 47,837 169,418
99,914 1,368 1,976 15,409
Precious Metals Gold Palladium Platinum Silver
1,779 1,932 826 18
100 oz t 100 oz t 50 oz t 5,000 oz t
787,612 4,548 14,473 167,957
417 35 303 1,173
99,914 1,368 1,976 15,409
53 10 41 108
10 MT 37,500 lbs. 50,000 lbs. 110,000 FBM 15,000 lbs. 112,000 lbs.
814,407 1,111,885 631,833 11,808 29,054 3,654,553
18,332 62,127 18,639 560 536 45,024
217,524 268,517 161,481 2,620 10,247 913,150
4,896 15,003 4,764 124 189 11,250
Softs Cocoa Coffee Cotton No. 2 Lumber Orange Juice Sugar No. 11
2,251 1.49 0.59 431 1.23 0.11
10 MT 37,500 lbs. 50,000 lbs. 110,000 FBM 15,000 lbs. 112,000 lbs.
18,332 62,127 18,639 560 536 45,024
154 184 60 0 0 9
4,896 15,003 4,764 124 189 11,250
41 44 15 0 0 2
Contract Price* Size Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
1,823 31 325
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
Contracts
Notional Value ($mn.) Contracts
Notional Value ($mn.)
$1,000 X $250 X
n.a. 66,951 11,805
n.a. 2,067 959
n.a. 19,442 5,362
n.a. 600 436
61 41 39 1.22 1.25 1.75 1.20
1,000 MT 1,000 bbl 1,000 bbl 29,000 gal. 1,000 bbl 10,000 MMBtu 42,000 gal.
16,970 15,921,355 19,142,072 601 2,799,082 9,623,732 3,491,142
1,035 652,776 746,541 21 3,499 168,415 175,954
17,543 2,635,190 2,008,618 118 20,047 1,316,452 352,444
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybean Wheat (Hard Red)
476 3.48 3.58 533 0.12 289 0.26 8.66 4.53
20 MT 5,000 bu. 5,000 bu. 25 MT 2,000 cwt 100 T 60,000 lbs. 5,000 bu. 5,000 bu.
508,999 10,234,753 18,060 3,660 27,150 2,759,751 2,785,221 5,562,754 3,369,375
4,846 178,085 323 49 7 79,757 43,449 240,867 76,316
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
1,602 28,500 6,038 98 1,788 12,790 264 16,847 32 2,056
25 MT 1 MT 25 MT 500 MT 25 MT 6 MT 10 MT 5 MT 250 lbs. 25 MT
2,903 0 0 3,268 n.a. 8,387 1,784 n.a. 36 n.a.
Livestock and Dairy Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
1.29 0.49 0.92 22
50,000 lbs. 40,000 lbs. 40,000 lbs. 200,000 lbs.
Precious Metals Gold Palladium Platinum Silver
1,779 1,932 826 18
Softs Cocoa Coffee Cotton No. 2 Lumber Orange Juice Sugar No. 11
2,251 1.49 0.59 431 1.23 0.11
*
All prices in USD with the exception of canola, which is quoted in Canadian dollars
46  David J. Howden billion of futures contracts traded hands on the COMEX over the course of the month. West Texas Intermediate crude oil took a close second at $746 billion of monthly volume. This also makes gold the most liquid futures traded that month, surpassing even the CBOT´s 10year Tnote futures (monthly trading volume of $614 billion). Open interest is important as it reflects how deep the market is. It is also a more reliable indicator of the interest in the market since it is a cumulative statistic, and not prone to monthly vicissitudes. (An exuberant month might cause volume to surge as many contracts change hands, but open interest reflects the cumulative willingness to trade in the market over time.) Here Brent crude oil dominates with over $108 billion of futures contracts outstanding on the Intercontinental Exchange (note that additional futures can be issued on other exchanges, plus there is the overthecounter market). Most commodity futures are dwarfed by financial futures in terms of open interest. Eurodollar futures trading on the Chicago Mercantile Exchange currently have open interest of over $2.5 trillion. One reason for the large discrepancy is that financial futures are anchored by the whole economy (the Eurozone and the United States, in the case of Eurodollar futures). With a $13.3 trillion economy in the Eurozone and another $21.4 trillion in the United States, it is easy to understand why a large Eurodollar market should be expected. (Nearly $900 billion of goods were traded between the two regions in 2019.) In sum, futures on large markets should have large volume and open interest figures, but that does not necessarily convey information about the interest in the derivative side of the market. One way to make these notional liquidity figures more comparable with each other is to rebase them in terms of the supply of their underlying commodities. While Brent crude oil has the greatest value in contracts outstanding, relative to the value of its supply in 2019 ($1.4 trillion) it only had a relatively small interest in trading futures. Financial contracts made up 8% of this annual supply value. In contrast, there are currently more futures contracts outstanding than the annual production of silver. Not only that, but in the single month of June 2020 there was over ten times more trading done in the futures market than in the physical market over the whole of the previous year. (Admittedly, silver is not used up in the same way that oil is, but one of the primary reasons to buy a future is for the producer to hedge his position.) Taking a longer view it is useful to see where the commodities´ prices are relative to the past, both in nominal and inflationadjusted terms. In general, most nominal highs were made during the boom that peaked in 200708, or the one that culminated more recently in 2014. In exceptional cases some commodities formed their alltime price highs decades ago. Sugar peaked in November 1974 at a price of $0.53 per pound. The current cash price is less than onefifth this level. Likewise, cocoa made its alltime high in July 1977 at a price of $5,184 per metric ton. It came close to reaching this high again in February 2011 at a close of $4,204. At present the cash cocoa price is still less than half the level it was 45 years ago. Looking at the inflationadjusted prices, there are two three broad periods where many commodities peaked simultaneously. The first was during World War I, when corn, milk, soybeans, steel, and zinc all made their alltime real price highs. (All commodities saw elevated inflationadjusted prices during the 1910s, but these five secured their alltime highs during the period.) The 197379 period that accompanied the last great bout
Commodities, the Decade Ahead  47 with inflation was the next time that brought all commodities higher, and some to their alltime highs. Cobalt, cocoa, coffee, canola, cattle, hogs, lumber, rice, soybean meal, sugar, and tin all peaked during this period. (Gold and silver followed not far behind in 1980.) Finally, the most recent commodities boom that peaked in 2008 brought many prices to peak though except for platinum, these were all limited to energyrelated commodities. The exercise is useful for two reasons. First, it grounds the investor´s expectations on what prices are possible. More importantly, it illustrates that longterm price movements do not trend in only one direction (typically assumed to be up). If the history of commodities is any guide, the more usual state of affairs is for prices to fall over time not only in real terms, but in nominal terms also. The second reason is that there are many factors that affect a commodity´s price. The demandside factors are normally subsumed into the factors of income and population growth. The supplyside factors are normally concerned with resource availability, and the related issue of production and extraction technology. Over the past thirty years or longer, both factors have increased. As a baseline, I can compare the returns to holding a commodity (its annual change in price) with the change in the consumer price index over the same period. Since 1990, inflation has averaged 2.3% annually in the United States. Most commodities have seen their returns hover around this level. Energy and the precious metals have performed a little better than this average, while grains and livestock have performed a little worse. Do note, however, that over long periods of time there are almost no outliers to this tendency for the return to mirror the change in the general price index. (Iron and palladium are the only two outliers, the latter most due to the height of its current boom.) The median returns since 1990 show a similar tendency. The median return is the one where half of the subsequent annual returns will be higher, and the other half lower. For example, buying gold in 1990 would have yielded a median return of 5.4% if held until today. This means that buying the yellow metal on half of the dates after June 1990 would have yielded an annual return above this level, and the other half would have left the investor with a lower return. One can think of this as the actual return the investor would have earned by being a longterm investor in a given market. (Since, for example, someone invested in gold probably did not buy his whole holding in June 2020 and keep it until today, but rather he would have bought some in each month or year. Some of those monthly purchases would have higher than the median return, and some would be lower, but the typical month would have earned him the median return.) The median return to the investor has been negative over the past thirty years. In almost all cases, the median return has been lower (in some cases far lower) than the median rate of inflation since 1990. This means that commodities have been a poor bet from a longterm perspective. If there is a benefit to investing in commodities, it is for holding them for short rather than long periods. This is true of all investments, as volatility and the accompanying opportunities for gain or threat of losses are greater over shorter periods. With commodities this effect is somewhat different than it is with investments that offer a cash flow, like with dividends with equities or rents with real estate. It is very unusual for a broadbased equity index to offer a negative return over an extended period thanks to the stream of dividends offsetting any losses of the principle value. A commodity offers
48  David J. Howden
Commodities, the Decade Ahead  49
Commodities, historic highs
Commodities, historic annual returns (since June 1990) Date of Historic Historic High Monthly Nominal Real High
Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
May2008 Oct1987 Jun2008
May2008 N/A Mar2008
178.74 140.42 140.00 3.81 3.91 15.00 136.22
Jul2008 Jun2008 Jun2008 Jun2006 Jun2008 Sep2005 May2007
Jul2008 Jun2008 Jun2008 Jun2006 Jun2008 Sep2005 May2007
957.00* 842.75 497.00 1,145.23 21.48 594.50 65.69 1,778.00 1,239.00
Sep1974 Aug2012 Feb2014 Feb2011 Apr2008 Aug2014 Feb2008 Aug2012 Feb2008
Sep1974 Nov1917 Jul1902 May1984 Dec1973 May1973 Mar1947 Feb1918 Jun1898
3,086.00 96,627.77 9,857.50 183.62 3,691.00 50,900.00 649.35 32,275.00 136.22 4,390.00
Feb2008 Mar2008 Feb2011 Feb2011 Oct2007 May2007 Jul2008 Apr2011 May2007 Nov2006
Aug1995 Jun1979 Jul1964 Feb2011 Oct2007 May2007 Jun1917 Nov1979 May2007 Jun1915
240.00 132.83 172.50 24.06
Nov2014 Jun2014 Nov2014 Sep2014
Apr1979 Jul1973 Jul1948 Jan1918
Livestock and Dairy
1,813.50 2,598.22 2,155.00 47.88
Aug2011 Feb2020 Feb2008 Apr2011
Jan1980 Feb2020 Feb2008 Feb1980
Precious Metals
5,183.53 330.50 195.73 597.10 217.30 53.00
Jul1977 May1997 Mar2011 May2018 Nov2016 Nov1974
Jul1977 Mar1977 Mar1918 Feb1973 Feb1950 Nov1974
Softs
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) Uranium
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybeans Wheat (Hard Red)
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
Livestock and Dairy Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
Consumer Price Index
11,440.00 60.90 862.80
Total Return
Median Return
(if bought on June 1990) 2.3
(since June 1990) 1.8
Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
1.7 2.3 1.9
1.4 3.4 0.2
1.7 3.2 2.8 1.2 3.2 0.6 2.6
1.7 0.2 0.9 1.5 0.2 6.3 0.5
1.3 0.5 3.0 3.2 1.4 1.7 0.1 1.1 1.1
1.1 0.8 3.5 0.6 1.5 1.0 0.2 1.0 0.3
0.1 4.2 2.9 6.8 2.2 1.3 2.2 3.5 3.5 0.5
0.4 0.1 3.2 8.8 3.6 1.7 1.8 3.9 4.1 2.0
1.0 0.6 0.7 2.0
1.3 1.9 0.5 3.1
5.5 9.8 1.8 4.2
5.4 13.1 0.2 5.0
1.6 1.5 1.0 2.5 1.2 0.2
1.1 1.2 0.6 2.8 0.4 0.2
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybean Wheat (Hard Red)
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
Precious Metals Gold Palladium Platinum Silver
Gold Palladium Platinum Silver
Softs Cocoa Coffee Cotton No. 2 Lumber Orange Juice Sugar No. 11 *
Canadian dollars
Cocoa Coffee Cotton No. 2 Lumber Orange Juice Sugar No. 11
50  David J. Howden no cash flow, and as such is not protected by a mitigating factor if its price happens to fall. Over short periods, there have been some incredible returns on record from commodities. The 445% gain in gold between 2001 and 2020 worked out to an annualized 21% return. The lead up to its major peak in 1980 saw a 362% gain in hardly threeandahalf years (71% annualized!). Of course, what commodities giveth in returns they also taketh away. Gold´s collapse of 68% in the five years following its 1980 peak erased 20% of the investor´s wealth annually. Every commodity has a similar story of stellar gains and horrible losses. The problem the investor faces is identifying what periods will offer superior returns, and which periods can be expected to result in losses. The use of cycle analysis in conjunction with period forecasts aid the investor to differentiate heaven from hell. Each of the following country reports is structured to allow the reader to understand where a commodity is relative to its past price evolution, and where its price can reasonably be expected to tend to in the future. In each of the 43 country reports a similar methodology is used to provide a common basis for analysis. Before delving into the reports, it is instructive for the reader to familiarize himself with the general approach used, and how it is useful in forecasting returns. This foundation is provided in the next chapter.
Commodities, the Decade Ahead  51
Introduction to the Commodity Reports Each of the following reports starts with a brief review of the commodity. The opening of each report focuses on the supplyside of its market, as well as on events that have recently affected its price. Next comes a brief overview of the analysis to follow, the “bottom line”. Here the reader can quickly get the information that unfolds in greater detail over the subsequent pages. The commodity´s price is compared with what I refer to as its fairvalue price. Fair value is the price that would make the relative valuation of the commodity equal to zero (neither over nor undervalued). Also listed is its relative valuation expressed, as always, in standard deviations that the spot price is away from the fairvalue price. Next comes a summary of current phase of the commodity´s price cycle. Besides listing the probable direction of the current phase (topping, up, down, bottoming), the cycle´s start date and expected end date are also available. This expected cycle end date corresponds to that which makes the current phase the same duration as the median bull or bear market over the commodity´s history. In the case of aluminum, I expect the commodity to have started a new bull market phase in April 2020. Since the median duration over all the metal´s bull markets is 3.8 years, an expected end date of February 2024 results. Since in almost all cases the commodity will be somewhat advanced along its current cycle phase, I list the expected real return remaining over the duration of the cycle´s expected duration. Aluminum has already advanced 10% from its April 2020 bottom. Since the median bull market advanced the metal´s price by 86%, a 76% price increase would bring the current advance in line with the others. Finally, some commodities have rather long price cycles while others are brief. To make these expected cycle returns comparable I list the annualized return that I expect the commodity to realize over its current cycle. In the case of aluminum, a 76% return spread over the remaining 44 months of its cycle yields an expected annualized return of 17%. Next comes the “meat” of the report: a presentation of the commodity´s analysis in more detail. A historical look at its price and valuation history makes the reader aware of where it is relative to the recent and notsorecent history. This history is achieved via a summary of all the commodity´s cycles (dating to 1900 at a maximum). At the bottom of this table are the maximum, median, and minimum values of the bear and bull markets. The median values are used to forecast the expected extent, in terms of duration, price and valuation, of the commodity´s current phase. For example, aluminum has completed eight bull markets since 1900. The median bull market: 1) lasted 3.8 years, 2) had a price
52  David J. Howden that advanced 86% in real terms, 3) started from a relative valuation of 1.4 standard deviations, and 4) gained +3.3 standard deviations of value over the advance. Applying these median values to aluminum at the start of its current bull market yields the forecast included in the table for the end of the metal´s advance. In this case, if aluminum trades at $2,722 on February 2024 with an overvaluation of +1.9 standard deviations it will have advanced in a manner consistent with its other eight previous bull markets. Two graphs are included to aid the reader in gaining a visual handle on where the commodity is in its price cycles. The first is a 30year look at the price in both nominal and inflationadjusted terms. Aluminum´s nominal high in February 2008 is apparent, as are the vestiges of its high made in December 1988. It is apparent from a quick look at the graph that aluminum is currently trading at a nominal price consistent with its recent 2009 and 2015 lows, and that it has been 20 years since it traded consistently near the $1,500 mark. We can also see that aluminum has not traded at a real price as low as it is currently in over 30 years. (In fact, aluminum has never traded at this low a real price since records begin in 1895.) Seeing the commodity´s price is important, but the evolution of its relative valuation is more important in gauging where the price will tend to in the future. Generally, a bull market swing moves the valuation from negative to positive territory and the opposite for a bear market. (In rare cases a bull market will start from an overvalued position and move to an even more overvalued position.) As relative valuation is mean reverting, pressures start to build as soon as it is negative or positive to return it to the fairvalue price. These pressures intensify as the commodity´s valuation moves into more extreme territory, and often portends of largescale price movements. Aluminum´s overvaluation of +3.3 standard deviations in February 2008, for example, quickly gave way to a 58% loss by February 2009. Along the way we can see that aluminum´s relative valuation also collapsed, moving into negative territory before finding support to start its next advance. Cycle analysis is useful to the extent that it allows the reader to understand the cyclical oscillations around the fairvalue level that define the advances and declines in a commodity´s price over time. One challenge in using this information alone is that we can make statements about the median bull or bear market, but we can say relatively little about less “normal” advances or declines. We know that the median bull market in aluminum has brought the metal´s price 86% higher. But the largest bull market advance (191416) increased its price by more than double that amount, 199%. The weakest bull market (198788) saw aluminum´s price rise by only 47%. I expect the metal´s price to top at $2,722 but given this range of advances I would also accept $2,142 to $4,368 would be within the realm of possibility. Likewise, while I expect aluminum´s bull market to take 3.8 years to complete, the shortest advance (199395) needed only 1.2 years while the longest (192233) took 10.8 years. The median values are nice to set our bearings, but there is also a large range of possibilities to contend with. To deal with more typical scenarios I develop the two period models to statistically forecast the commodity´s price evolution over the next five and tenyear period. In many cases a large set of historical data points is available for each commodity, which serves to create a highly robust model to forecast prices changes from. Since the price history of aluminum starts in June 1895, there have been 1,440 5year investment periods, and 1,380 10year periods. This is useful as we can see how the commodity´s price has evolved over these time periods in the past given similar economic and financial data as exist today.
Commodities, the Decade Ahead  53 Two graphs in this section show the commodity´s 5 and 10year returns since over the past thirty years (the solid gray line). The graphs also show what the forecast model predicts the return will be for the relevant period if the investor purchased the commodity on the date in question (the black dashed line). In general the 10year model is more robust and reliable than the 5year model, and I report the adjusted R2 for each model so that the reader can judge for himself how good a statistical fit the model has for the data in question. With these models, I forecast that aluminum´s price will increase by 6.5% annually until June 2025, and by 3.9% annually through to June 2030. Over the past thirty years, the 5year model has explained 49% of the variation in the 5year returns, and the 10year model explains 63% of the 10year returns. To judge how good or poor an investment a commodity will be what is needed is a forecast of the future return and a measure of the reliability of the forecast. I combine these two elements by giving a probability that the commodity´s price will breakeven over the two periods, and also that it will return more than 10% over the periods. Given the fit of the model over the past thirty years and the fact that I forecast aluminum´s price to increase by 6.5% annually over the next five years, the commodity has a breakeven probability of 90%. In other words, only in 10% of cases would it be statistically possible for aluminum´s price to post a decline. Likewise, even though I forecast a 6.5% return over the next five years, this is only a statistical forecast. There is the possibility (to various degrees, depending on the robustness of the model) that aluminum will provide the investor with much greater or much worse performance. So that all commodities can be compared with each other on a common basis, I include the forecast that the return will be greater than 10%. (The use of 10% is arbitrary and only serves to create a common hurdle for all models to overcome.) In this case, aluminum´s historical 5year annual return exceeded 10% in 15% of cases similar to where it is today. It is reasonable to project this probability into the future and consider there to be a 15% chance that aluminum will yield more than 10% annually over the coming five years. The conclusion brings the full analysis together, and also adds a qualitative ranking to the report. Until now all the forecasts have been quantitative in nature (aluminum´s forecast 5year return is 6.5%; it is expected to breakeven with a 90% probability). Here I conclude by offering a rank that can be used to determine which commodities are expected to offer superior future performance and which will likely offer dismal returns (or even losses). To do this it is necessary to combine the two approaches – the cycle analysis and period forecasts – together into a cohesive whole. Start by just considering the period valuation models and their resultant expectant returns. The most dependable analyses in the report are those determining the relative valuation of the commodity, the forecast returns over the coming five years and decade, and finally the probabilities that the commodity´s return will surpass the hurdle rate of 10% over those periods. The reliability of these analyses stem from the long data set yielding a large number of data points to analyze statistically. (In comparison, the cycle analysis will include not more than a dozen bull and bear markets for most commodities.) Each of these aspects is ranked from 1st to 43rd (since there are 43 commodities and indexes covered). A ranking of 1st indicates the commodity is the most undervalued by relative valuation (lean hogs), while a ranking of 43rd indicates the most overvalued commodity (milk). Similarly, a ranking of 1st for the period returns indicates the highest expected
54  David J. Howden return over the next 5 and 10year period (Brent crude oil, and uranium). Finally, the robustness of the model can be combined with the period forecast and summarized by the probability that the price will increase by more than 10% over the two periods. Again, the ranking of 1st will belong to the commodity with the greatest probability of surpassing this return over the next five years (heating oil) and decade (tin). In the graph that accompanies this concluding section I map out the commodity´s price performance over the past thirty years, as well as the expect future price given the cycle analysis and the two period forecasts. In the case of aluminum, cycle analysis forecasts a price peak of $2,722 in February 2024. The period forecast models call for a price of $2,101 in June 2025 and $2,353 by June 2030. For the dates between these three points I use a linear average to extrapolate the prices. In sum, I forecast that aluminum will see higher prices at all future dates but an immediate price spike as the current bull market runs its course. From this expectation of the commodity´s future price, I calculate the return that is expected to prevail over each period over the next decade. There are 119 expected returns in total. Those shortest assumes the investor buys the commodity today and sells it one month from now, in July 2020. The longest also assumes the investor buys the commodity today but does not sell it until June 2030. Over the short periods the expected annualized returns can be very high. To aid the reader all commodities have their return axis on this graph truncated at 50% since the more interesting (and reliable) returns happen at lower levels and over periods from two to ten years to the future. In this way the reader can translate the graph with the expected future price into information that is more directly useful to his investment choice, and this allows him to compare each commodity on a common basis. Each commodity report ends with a ranking of the expected return over the next five and ten years, as well as its overall rank. The expected returns in this final table differ from those in the previous forecast return table because they include the whole analysis – cycle highs and lows in addition to the forecast returns over the next five and ten years. Since there is a large variance in the expected returns, I use the median values over each period. For example, the expected return of aluminum over the next five years is 16.8%. This figure means that the median return the investor could realize by buying aluminum at any point over the next five years and selling it in June 2025 is 16.8% (half of those holding periods will yield a higher return, and the other half will fare worse). Likewise, to say that aluminum has an expected return of 5.5% over the next decade means that the median return from buying aluminum at any month between now and June 2030 is that figure. The rank again refers to the commodity with the highest expected return (1 st is uranium over five years, and RBOB gasoline over the next decade) to the lowest (43rd place belongs to palladium over the next five years, and the VIX takes this “honor” over the coming decade). The use of these expected returns is on the one hand seemingly irrelevant since the investor would have to buy equal amounts of the commodity every month over each period to structure a portfolio that could mimic these returns. On the other hand, the analysis is performed so that a ranking can be constructed that gives the investor a feeling for which investment will yield superior returns over the next five and ten years. To this end, I conclude each country report with the commodity´s overall rank. This rank is the median value of the commodity´s relative valuation ranking, and its two expected return
Commodities, the Decade Ahead  55 rankings. Broadly stated, the commodity ranked first overall (RBOB gasoline) has a higher chance of offering superior returns to the average commodity than does the 43rd ranked one (palladium). This final step of the analysis thus gives the reader a bird´s eye view of the whole analysis, and allows him to then delve into the details of when these returns are expected to be realized, in what magnitude, and with which likelihood. With this introduction as to the general structure of the analysis done, let´s get on with the 43 country reports!
56  David J. Howden
Commodities, the Decade Ahead  57
Commodity Reports
58  David J. Howden
Commodities, the Decade Ahead  59
Aluminum Aluminum (or Aluminium) is the most abundant metal in the world, and accounts for about 8% of the earth´s crust. The silverygrey metal is used widely by the transportation and distribution industry owing to its light weight and high malleability. China accounts for approximately half of global production of the metal. Global aluminum output reached 64 million tons in 2019, a 72% Aluminum increase over the previous decade. Production This increase came largely as a result (% World) of expanded production from China which smelted almost no aluminum China 56 twenty years ago. Over the past decade China has increased output of India 6 smelted aluminum by 179% (23 Russia 6 million tons per year) and India has Canada 5 increased output by 131% (2 million tons annually). China is by far the United Arab Emirates 4 world´s largest smelter of aluminum, a Rest of World 24 position it has held since overtaking Russia in 2003. Source: USGS, 2020 Recycled scrap remains an important source of aluminum augmenting smelted production. In the United States, approximately 45% of aluminum consumption comes from recycled sources. Since 1999 world output has increased at an annual rate of 5.1%. Most aluminum in the world is mined from bauxite. There are approximately 30 billion tons of bauxite in reserves globally. Over the last decade world bauxite reserves have grown by just 0.8% annually. Guinea maintains the world´s largest bauxite reserves, 7.4 billion tons (25% of global reserves). Although just five countries account for 72% of global reserves, the rock is found widely throughout the world. The United States has
60  David J. Howden
Commodities, the Decade Ahead  61 negligible reserves (less than 1% of global levels) although the ability to recycle large amounts of aluminum compensate for this limitation. The London Metal Exchange launched aluminum contracts in 1978. The metal has since become the exchange´s most liquid contract. It is also traded on the Commodity Exchange. The LME aluminum (AH) cash contract returned 9.7% to the investor over the past year. Futures trade in lots of 25 metric tons and are quoted in U.S. dollars per metric ton.
of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that aluminum´s price will breakeven by June 2025 with a 90% probability, and that there is a 15% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast aluminum´s price to increase by 3.9% annually until June 2030 with a forecast range between 3.8 and 4.2%. This model explains 63% of the metal´s 10year returns since June 1990. As such, there is a 98% probability that aluminum will breakeven over the coming decade, and a less than 1% chance that it will yield a return greater than 10%.
Aluminum: Forecast Summary 1,602 2,086 1.2
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Apr20 Feb24 76 17
5Year Forecast 5Year Annual Forecast Return, % 5.6 5Year Forecast Range, % (5.2, 5.8) 2 0.49 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
90 15
10Year Forecast
The Bottom Line Aluminum closed June 2020 at a price of $1,602 per metric ton. Based on historical valuations dating to June 1895 (1,501 months) I estimate the fairvalue price of the commodity to be $2,087, implying an undervaluation of 1.2 standard deviations. This indicates that it is priced more cheaply today than 88% of all previous months. Analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The April 2020 low of $1,461 looks to be a longterm bottom. Historically, the median bull market in aluminum has lasted for 3.8 years and increased its price by 86% in real terms. Following this pattern, the current bull market phase should be completed in February 2024 after an additional 76% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of aluminum to increase by 5.6% annually, with a forecast range between 5.2 and 5.8%. The forecast model explains 49%
10Year Annual Forecast Return, % 3.9 10Year Forecast Range, % (3.8, 4.2) 2 0.63 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
98 0, % Probability 5Year Forecast Return > 10, %
57 31
10Year Forecast 10Year Annual Forecast Return, % 3.5 10Year Forecast Range, % (1.9, 6.0) 0.55 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
32 4
Historical Analysis Since June 1990, the nominal price of the BDI has increased from $1,089 to the current close of $1,823 for an annual return of 1.7%. The alltime nominal high for the index came in May 2008 at a price of $11,440. In real, inflationadjusted terms the index´s price has mostly fallen throughout its history with the exception of two price spikes in 200304 and 200708. The BDI´s real high was also in May 2008, with its subsequent low forming in January 2016. As of June 2020, the index´s price was lower than 91% of all prior monthly closing prices in real terms. Over longer periods, the BDI´s price has failed to keep pace with general price inflation. This has resulted in a real yield of around 2% for most of the past 35 years.
Since 1985 the index has gone through eight complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the index´s price increase by 349% in real terms, before being corrected by a median decline of 75%. The median bull market has lasted for just two years, and its subsequent correction has taken a little over one year to complete. Owing to the relatively short price history available for the index, it is not possible to track the changes to its relative valuation over a sufficient number of phases to make claims concerning its cyclical norms. Still, with eight completed cycles it is possible to speak of these bull and bear markets in terms of their price action. The most recently completed phase of its cycles was the bull market decline which started in August 2019. From the starting price of $2,378 the index´s price decreased by 80% in real terms. This decline is on par with the median correction of 75% over all recorded BDI bear markets. At the recent January 2020 low of $487 the index was 0.8 standard deviations undervalued. The loss of 1.0 standard deviation of valuation between 2019 and 2020 is broadly
74  David J. Howden
Commodities, the Decade Ahead  75
consistent with what I should expect of a correction based on the median changes in the measure of other commodities and indexes. As such, the balance of cycle evidence points to the January 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. Baltic Dry Index: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Mar88 Sep92
1617
1,041
47
n.a.
Apr95 Dec98
2,347
794
69
n.a.
Oct00 Oct01
1,759
861
52
n.a.
Nov04 Jun05
6,051
1,804
71
n.a.
May08 Nov08 11,440
715
94
n.a.
May10 Jan12
4,078
680
98
n.a.
Dec13
Jan16
2,277
317
86
n.a.
Aug19 Jan20
2,378
487
80
0.2
Date Start End Jul86 Mar88
Price Start End 554
1,617
174
n.a.
Sep92 Apr95
1,041
2,347
110
n.a.
Dec98 Oct00
794
1,759
109
n.a.
Oct01 Nov04
861
6,051
554
n.a.
Jun05 May08
1,804
11,440
472
n.a.
Nov08 May10
715
4,078
5,470
n.a.
Jan12
Dec13
680
2,277
225
n.a.
Jan16
Aug19
317
2,378
594
0.9
Jan20
Jun20
487
1,823
277
0.8
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 4.5 98 n.a. n.a.
Median 1.3 75 0.2 n.a.
Min. 0.4 47 n.a. n.a.
Max. 3.6 5,470 0.9 n.a.
Median 2.2 349 0.9 1.1
Min. 1.5 109 0.8 n.a.
Mar22 0.3 2,185 349 1.1
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
If a new bull market did start in January 2020 what can we expect the future to hold? The median bull market in the BDI has lasted for a little over two years and gained 349% in real terms. The weakest advance, during 19982000, gained 109% in real terms. Since January 2020, the index has already gained 277%. As such, I expect the current cycle to gain an additional 72% in real terms by March 2022. This implies an expected annual return of 36% by the time the present bull market reaches completion. The January 2020 undervaluation of 0.8 standard deviations is more undervalued than 79% of the index´s previous monthly closes. As of June 2020, the index was still undervalued, by 0.1 standard deviations. By the time the current bull market reaches its end, I expect BDI to be trading at a slightly higher relative valuation of +0.3 standard deviations.
In sum, cycle analysis points to the BDI trading at $2,185 on March 2022. This price will likely be consistent with an overvaluation of +0.3 standard deviations, representing a total advance of +1.1 standard deviations.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for the BDI starts in January 1985. This means that to date there have been 366 5year holding periods and 306 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of the BDI is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation.
76  David J. Howden
Commodities, the Decade Ahead  77
Inflation and interest rates also play a role in forecasting future returns, as do expectations of the future.
Conclusion I have developed two models to forecast the return of the BDI over these two different time periods – five years and ten years. Both models use the relative valuation of BDI as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 2.6% annual gain in the BDI over the coming 5year period. The model explains 41% of the variation of the 300 5year returns of the index since June 1990. Given this explanatory power of the model, I estimate that the price of BDI will breakeven by June 2025 with a 57% probability, and that the return will exceed 10% with a 31% probability. Over the next ten years, I expect the BDI to decrease by 3.5% annually. The model explains 55% of the variance in the index´s 240 10year returns since June 1990. As such, I estimate that the BDI will breakeven by June 2030 with a probability of only 32%, and that there is only a 4% chance that its return will exceed 10% over this period.
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. The BDI´s relative valuation of 0.1 standard deviations approximately fairly valued, and overvalued relative to the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations). As such, the BDI is the 37th most overvalued commodity of the group.
Baltic Dry Index Forecast return rankings, out of 43 commodities Relative Valuation th
37 Baltic Dry Index 43 Commodity Avg.
0.1 0.7
Forecast returns: 5Year th
37
2.6 7.6
Probability that return exceeds 10%:
10Year nd
42
3.5 5.9
5Year th
10Year th
27
28
31 39
4 22
78  David J. Howden
I forecast that the index will yield an annual return of 2.6% over the coming five years, and –3.5% over the coming decade. Both returns are significantly lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, the BDI ranks 37 th and 42nd out of the 43 commodities for both the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the index will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 31% probability that the BDI can achieve this return by 2025 and only 4% by the end of the decade, ranking the index 27th and 38th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that the BDI will underperform the average commodity over both the coming 5 and 10year periods.
Commodities, the Decade Ahead  79 term projections are reasonably robust, with 41% of the index´s 5year returns and 55% of its 10year returns explained since June 1990. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying the BDI today and selling it at any date over the coming decade. For example, an expected price of $2,070 in June 2025 implies an annual rate of return of 2.6% over the next five years if the investor buys the index today. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 6.8% by buying the BDI. This expected return is somewhat lower at 2.5% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, the BDI ranks 35th and 37th out of the 43 commodities. This implies that the BDI should yield a much lower return relative to other commodities over both of these time periods. Taking the average of its rankings for these expected returns, the Baltic Dry Index ranks 37th out of the 43 commodities.
Baltic Dry Index Expected return rankings, out of 43 commodities Relative Valuation To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the index is in its current price and valuation cycle. The evidence from the BDI´s price and valuation cycles since 1985 points to a probable advance in the index´s price that will end in March 2022. At a high of $2,185 by that date, the index will have advanced from its January 2020 low in a manner consistent with the other eight advances since 1985. Over this time, the BDI´s relative valuation should increase a little from its current overvalued position of +0.1 standard deviations, ending this bull market advance overvalued by +0.3 standard deviations. Analysis of the BDI´s longerterm price behavior points to somewhat higher prices by 2025, followed by a gradual price decline by 2030. I forecast the BDI to be trading at $2,070 by June 2025, and $1,276 by June 2030. The forecast models for these longer
th
37 Baltic Dry Index 43 Commodity Median
0.1 0.8
Expected average returns: 5Year th
35
6.8 21.2
10Year th
37
2.5 8.1
Overall Rank th
37
80  David J. Howden
Commodities, the Decade Ahead  81
Canola Canola, or rapeseed, is a brightyellow flowering plant valued for its use in making oil. It is the third most common vegetable oil in the world, after soybean and palm oil. It is also the second most common source of protein meal for animals, after soybean meal. Increasingly canola oil is demanded to produce biodiesel, Canola especially in Europe. Although Production historically not consumed widely by humans due to its high levels of toxic (% World) erucic acid, a marketing campaign led by Canadian agricultural scientists in Canada 27 1973 promoted the consumption of European Union 26 canola. Today canola oil is an China 18 important element in food production, though refined to limit its India 11 erucic acid content at less than 2%. Australia 5 Global canola output reached 75 Rest of World 13 million metric tons in 2018, a 32% increase over the previous decade. Source: Food and Agriculture This increase came largely as a result Organization of the United Nations, of both expanded production area and 2018 increased production yields. The increase also came mostly from output growth in Canada, where production grew by 61% (by 7.7 million metric tons) over the last decade. Canada became the world´s largest canola supplier in 2018, overtaking the European Union which held the position since 1980. Since 1999 world output has increased at an annual rate of 1.1%. Globally, there are 37.6 million hectares of land devoted to canola production. This area has steadily increased for over 30 years, notwithstanding some significant
82  David J. Howden yearonyear changes. Yields have also increased continually, further adding to the expanded harvest area to boost global output. Globally, canola yields 2.0 metric tons to the hectare. This represents a 6% increase over the past decade, and 1.3% annually since 1999. The rate of growth for both production area and yields has fallen steadily for the past 30 years. Land use was expanding by 5% annually as recently as the late 1990s, though has slowed to 1.6% annually as of 2018. Likewise, yields were growing in the 2.53% range throughout the 1990s and are now hovering around 1.52% annually. Canola futures and options are traded on the Intercontinental Exchange. The ICE canola (RS) cash contract returned 4.4% to the investor over the past year. Futures trade in lots of 50 metric tons and are quoted in Canadian dollars per metric ton. (All data below are in Canadian dollars.)
Commodities, the Decade Ahead  83
Canola: Forecast Summary Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Trend Median Real Return, % Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
476 507 0.4
Up Sep14 Sep16 96 85 n.a.
5Year Forecast 5Year Annual Forecast Return, % 4.1 5Year Forecast Range, % (3.7, 4.7) 2 0.58 Adjusted R
The Bottom Line Canola closed June 2020 at a price of $476 per metric ton. Based on historical valuations dating to September 1974 (550 months) I estimate the fairvalue price of the commodity to be $507, implying an undervaluation of 0.4 standard deviations. This indicates that it is priced more cheaply today than 66% of all previous months. Analysis of the cereal´s price cycles since 1974 points to the continuation of the secular bull market that started in 2014. The September 2014 low of $395 still looks to be a longterm bottom. Historically, the median bull market in canola has lasted for 2.0 years and increased its price by 96% in real terms. Following this pattern, the current bull market phase is already running long and should be complete after an additional 96% gain in the cereal´s inflationadjusted price. Over the coming 5year period, I forecast the price of canola to increase by 4.1% annually, with a forecast range between 3.7 and 4.7%. The forecast model explains 58% of the variation in the cereal´s 5year returns since June 1990. Consequently, I forecast that canola´s price will breakeven by June 2025 with an 85% probability, and that there is a 7% chance that the cereal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast canola´s price to increase by 3.8% annually until June 2030 with a forecast range between 2.8 and 5.3%. This model explains 71% of the cereal´s 10year returns since June 1990. As such, there is a 98% probability that canola will breakeven over the coming decade, and a less than 1% chance that it will yield a return greater than 10%.
Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
85 7
10Year Forecast 10Year Annual Forecast Return, % 3.8 10Year Forecast Range, % (2.8, 5.3) 0.71 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
98 0, % Probability 5Year Forecast Return > 10, %
11.7 n.a. 0.61 5 0, % Probability 10Year Forecast Price Return > 10, %
5.7 n.a. 0.42 4 0
Historical Analysis Since January 1986, the nominal price of the VIX has increased from $15.50 to the current close of $30.90 for an annual rate of return of 2.3%. The alltime nominal high for the index came in October 1987 at a price of $60.90. In real, inflationadjusted terms the index´s price has mostly fallen throughout its history. The VIX´s real high was also in October 1987, with its subsequent low forming in February 1995. As of June 2020, the index´s price was lower than 47% of all prior monthly closing prices in real terms. Over longer periods, the VIX´s price has just kept pace with general price inflation although with much higher volatility. This has resulted in a real yield of around 0%. Nominal returns have hovered around 2% for most of the index´s history, with real returns averaging 0.2% annually between 1986 and 2010. The highest longterm nominal return the investor could have earned was 7.6% and resulted by buying the VIX in
Since 1986 the index has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the index´s price increase by 271% in real terms, before being corrected by a median decline of 68%. The median bull market has lasted for just over a yearandahalf, and its subsequent correction has taken about three years to complete. Owing to the relatively short price history of the index available, it is not possible to track the changes to its relative valuation over a sufficient number of phases to make claims concerning its cyclical norms. Still, with six completed cycles it is possible to speak of these bull and bear markets in terms of their price action. The most recently completed phase of its cycles was the bull market advance which started in October 2017. From the starting price of $11.30 the index´s price increased by 298% in real terms. This advance is on par with the median rally of 271% over all recorded VIX bull markets. The advance´s starting relative valuation of 1.2 standard deviations was also consistent with what should be expected based on the analyses of other commodities and indexes At the recent March 2020 high of $46.80 the index was +3.8 standard deviations overvalued. The gain of +5.0 standard deviations of valuation between 2017 and 2020 is also consistent with what should be expected of a rally based on the median changes in the
94  David J. Howden
Commodities, the Decade Ahead  95
measure of other commodities and indexes. As such, the balance of cycle evidence points to the March 2020 high marking the end of a bull market advance and the start of a fresh secular bear market. CBOE Volatility Index: Historical Cycle Summary Declines Date Start End Oct87 Jan94
Price Start End
Advances Real Start Rel. Change, % Val, σ
61
146
86
n.a.
Aug98 Mar02
44
17
64
n.a.
Sep02 Oct06
40
11
85
n.a.
Oct08 May11
55
17
40
n.a.
Sep11
Jun14
42
13
72
n.a.
Aug15 Oct17
26
11
59
0.8
Mar20 Jun20
47
31
34
3.8
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jan94 Aug98
146
44
271
n.a.
Mar02 Sep02
17
40
271
n.a.
Oct06 Oct08
11
55
352
n.a.
May11 Sep11
17
42
23
n.a.
Jun14 Aug15
13
26
114
n.a.
Oct17 Mar20
11
47
298
1.2
Current Bear Market Forecast End Date Relative Valuation Price Real Decline, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 6.3 86 3.8 n.a.
Median 3.2 68 2.3 2.0
May23 1.8 15 68 2.0 Min. 2.2 40 0.8 n.a.
Forecasted Returns Max. 4.6 23 n.a. n.a.
Median 1.6 271 1.2 5.0
Min. 0.3 352 n.a. n.a.
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
If a new bear market did start in March 2020 what can we expect the future to hold? The median bear market in the VIX has lasted for a little over three years and lost 68% in real terms. The weakest decline, during 200811, lost 40% in real terms. Since March 2020, the index has already lost 34%. As such, I expect the current cycle to lose an additional 34% in real terms by May 2023. This implies an expected annual return of 13% by the time the present bear market reaches completion. The March 2020 overvaluation of +3.8 standard deviations is extremely high based on the relative valuations at market peaks of other commodities. As of June 2020, the index was still significantly overvalued, by +1.6 standard deviations. By the time the current bull market reaches its end, I expect the VIX to be trading at a significantly lower, and maybe even negative relative valuation. In sum, cycle analysis points to the VIX trading at $15 on May 2023 at a significantly lower, probably negative, relative valuation.
The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for VIX starts in January 1986. This means that to date there have been 354 5year holding periods and 294 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of the VIX is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do expectations of the future.
96  David J. Howden
Commodities, the Decade Ahead  97 I forecast an 11.7% annual loss in the VIX over the coming 5year period. The model explains 61% of the variation of the 300 5year returns of the index since June 1990. Given this explanatory power of the model, I estimate that the price of VIX will breakeven by June 2025 with only a 5% probability, and that the return will exceed 10% with less than a 1% probability. Over the next ten years, I expect the VIX to decrease by 5.7% annually. The model explains 63% of the variance in the index´s 240 10year returns since June 1990. As such, I estimate that the VIX will breakeven by June 2030 with a probability of only 4%, and that there is a 0% chance that its return will exceed 10% over this period.
Conclusion
I have developed two models to forecast the return of the VIX over these two different time periods – five years and ten years. Both models use the relative valuation of VIX as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. The VIX´s relative valuation of +1.6 standard deviations above its longterm mean is higher than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the index is highly overvalued. As such, the VIX is the 41st most overvalued commodity of the group. I forecast that the index will yield an annual return of 11.6% over the coming five years, and 5.7% over the coming decade. Both returns are significantly lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, the VIX ranks last out of the 43 commodities for both the 5 and 10year return forecasts.
CBOE Volatility Index (VIX) Forecast return rankings, out of 43 commodities Relative Valuation st
CBOE VIX 43 Commodity Avg.
Forecast returns: 5Year rd
41
43
+1.6 0.7
11.6 7.6
Probability that return exceeds 10%:
10Year rd
43
5.7 5.9
5Year st
10Year th
41
35
0 39
0 22
Furthermore, I consider the probability that the forecasted return for the index will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 0% probability that the VIX can achieve this return over either period, ranking the index last out of the 43 markets for both probabilities. Given this evidence, it is highly likely that VIX will under
98  David J. Howden perform the average commodity over both the coming 5 and 10year periods.
Commodities, the Decade Ahead  99 To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying the VIX today and selling it at any date over the coming decade. For example, an expected price of $16.62 in June 2025 implies an annual rate of return of 15.4% over the next five years if the investor buys the index today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of the VIX, cycle analysis predicts a swift depreciation bottoming in May 2023, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 17.7% by buying the VIX. This expected return is somewhat less negative at 11.6% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, the VIX ranks 42nd and last out of the 43 commodities. This implies that the VIX should yield a much lower return relative to other commodities over both of these time periods. Taking the average of the index´s rankings for these expected returns, the VIX ranks 42nd out of the 43 commodities.
CBOE Volatility Index (VIX) Expected return rankings, out of 43 commodities To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the metal is in its current price and valuation cycle. The evidence from the VIX´s price and valuation cycles since 1986 points to a probable decline in the index´s price that will end in May 2023. At a low of $15 by that date, the index will have declined from its March 2020 high in a manner consistent with the other six declines since 1986. Analysis of the VIX´s longerterm price behavior points to somewhat constant prices going out to 2030 once the bear market low forms in 2023. These longerterm forecasts are consistent with the sharp collapse predicted by the cycle analysis, though over a longer period. By June 2025, I forecast the VIX to be trading at $16.62, and $17.24 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 61% of the index´s 5year returns and 42% of its 10year returns explained since June 1990. In all cases, the VIX is not expected to rise above its March 2020 high at any time over the coming decade.
Relative Valuation st
41 CBOE VIX 43 Commodity Median
+1.6 0.8
Expected average returns: 5Year nd
10Year rd
17.7 21.2
11.6 8.1
42
43
Overall Rank nd
42
100  David J. Howden
Commodities, the Decade Ahead  101
Coal Coal is a brownishblack to black sedimentary rock, valued for its combustibility. Used primarily as a fuel, coal is the result of dead organic matter enduring millions of years of heat and pressure. Anthracite is the most valuable type of coal. Hard and glossy black, it has the highest carbon content of the various varieties and is used in common heating applications. Bituminous coal is used in steamelectric power generation and to make coke, an important industrial product used mainly in iron smelting. The earliest uses of coal can be traced to the Shenyang area of China. By 4000 BC Neolithic inhabitants carved ornaments from black lignite, a soft form of coal. By 1000 BC, records show coal being used to melt copper in northeastern China. Although it has since come to be commonly associated with the Industrial Revolution, there is no evidence that coal was important in Britain prior to AD 1000. By 1700, over 80% of the world´s coal came from Britain where it was used to fire steam engines powering the Industrial Revolution. The predecessor of the European Union, the European Coal and Steel Community, was formed in 1951 to create a common market for coal to neutralize competition between European nations over natural resources, particularly along the Ruhr valley. Coal contains roughly 24 megajoules of energy per kilogram (by comparison, wood comes in around 16 megajoules per kilogram, and petroleum has about 42). A typical coal power plant will require approximately 325360 kilograms of coal to produce enough electricity to power a 100 W lightbulb for one year.
Due to pollution and health concerns, various international initiatives have focused on reducing the world´s dependence on coal as a fuel. Owing to the increased reliance
102  David J. Howden by China on the energy source, the efficacy of these initiatives has now come under doubt. Global coal output reached 8.1 billion metric tons in 2019, a 15% increase over the previous decade. This increase came largely as a result of expanded production from India and China (36% and 23% increases in coal production over the decade). Global coal output peaked in 2013 and fell until 2016, primarily due to an annual reduction of 500 million tons in Chinese production. At current growth rates, global coal mining should reach a new alltime peak sometime before the end of 2021. China is the world´s largest producer of coal, a position it has held since overtaking the United State in 1985. Since 1999 world output has increased at an annual rate of 2.8%. There are approximately 1.1 trillion metric tons of coal in reserves globally. Since 2016 coal reserves have shrunk by 2.1% annually. At this rate of depletion, world coal reserves will be halved by 2053. Five countries account for 75% of global reserves, though the commodity is found widely in smaller amounts throughout the world. Coal trades primarily on the Intercontinental Exchange, priced for delivery in Newcastle, Australia. (Coal also trades on the ICE for other delivery points, as well as the New York Mercantile Exchange.) The ICE cash contract returned 1.0% to the investor over the past year. Futures trade in lots of 1,000 metric tons and are quoted in U.S. dollars per metric ton.
The Bottom Line Coal closed June 2020 at a price of $61.40 per metric ton. Based on historical valuations dating to January 1906 (1,374 months) I estimate the fairvalue price of the commodity to be $90.75, implying an undervaluation of 1.0 standard deviations. This indicates that it is priced more cheaply today than 85% of all previous months. Analysis of the commodity´s price cycles since 1906 points to the start of a secular bull market that started in April 2020 at the $54 low. Historically, the median bull market
Commodities, the Decade Ahead  103 in coal has lasted for 2.1 years and increased its price by 190% in real terms. Following this pattern, the current bull market should end in May 2022 after an additional 175% gain in the commodity´s inflationadjusted price.
Coal: Forecast Summary 61 91 1.0
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr20 May22 175 70
5Year Forecast 5Year Annual Forecast Return, % 12.7 5Year Forecast Range, % (11.1, 15.6) 2 0.51 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
93 63
10Year Forecast 10Year Annual Forecast Return, % 8.9 10Year Forecast Range, % (7.5, 10.9) 0.66 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 39
Over the coming 5year period, I forecast the price of coal to increase by 12.7% annually, with a forecast range between 11.1 and 15.6%. The forecast model explains 51% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that coal´s price will breakeven by June 2025 with a 93% probability, and that there is a 63% chance that the commodity´s return will be over 10% by that date. The coming decade should see even higher returns. I forecast coal´s price to increase by 8.9% annually until June 2030 with a forecast range between 7.5 and 10.9%. This model explains 66% of the commodity´s 10year returns since June 1990. As such, there
104  David J. Howden is a 99% probability that coal will breakeven over the coming decade, and a 39% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of coal has increased from $37 per metric ton to the current close of $61 for an annual return of 1.7%. The alltime nominal high for the commodity came in July 2008 at a price of $179. In real, inflationadjusted terms the commodity´s price has mostly traded between $50 and $100 per metric ton throughout its history. Coal´s real high was in July 2008, with its low forming in October 1974. As of June 2020, the commodity´s price was lower than 65% of all prior monthly closing prices in real terms. Over longer periods, coal´s price has approximately kept pace with inflation for most of the 20th century resulting in a real yield of around zero. Nominal returns have hovered around 2.8% for most of the commodity´s history, with real returns averaging 0.2% annually between 1906 and 2010. The highest longterm nominal return the investor could have earned was 6.0% and resulted by buying coal in May 2003 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 4.0% per year. More recently the commodity´s price has been in a bull market since April 2020. From that month´s low of $54 a rally of 15% has ensued. The June 2020 close of $61 looks to be a stop along the way of the longterm secular advance.
Commodities, the Decade Ahead  105 bull market advance over these cycles has seen the commodity´s price increase by 190% in real terms, before being corrected by a median decline of 66%. The median bull market has lasted for just over two years, and its subsequent correction has taken three years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the four completed bull markets in coal that the commodity´s relative valuation can be calculated for has started from an undervalued position, with a median value of 1.2 standard deviations below the longterm mean. (With the exception of the 200910 rally that started from a quite overvalued position as a result of the extreme valuation reached at the previous peak in 2008.) From these undervalued starting positions, the median bull market increased its relative valuation by +4.0 standard deviations. Similarly, each of the commodity´s five completed bear markets that have relative valuation data available has started from an overvalued position, with a median value of +3.6 standard deviations above the longterm mean. Over the course of each bear market coal continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.6 standard deviations. Coal (Newcastle): Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Jan17 Mar20
7.01
4
63
n.a.
Aug20 Mar22
16.06
4
73
n.a.
Aug22
10.35
3
70
n.a.
Feb49 Apr66
7
7
22
0.3
Jan75 Aug02
34
22
81
4.0
Jul08
Mar09
179
61
65
8.1
Dec10 Feb16
137
48
68
3.6
118
54
55
0.9
Jul25
Date Start End Jul15 Jan17
Apr20
Real Start Rel. Change, % Val, σ
1.77
7
240
n.a.
Mar20 Aug20
4.36
16
258
n.a.
Mar22 Aug22
3.58
10
190
n.a.
Feb49
3
7
56
n.a.
Apr66 Jan75
7
34
189
1.2
Aug02
Jul08
22
179
568
1.5
Mar09 Dec10
61
137
117
0.9
Feb16
Jul18
48
118
132
1.0
Apr20 Jun20
54
61
15
1.3
Jul25
Jul18
Price Start End
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1906 the commodity has gone through eight complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median
Max. 27.6 81 8.1 7.2
Median 3.0 66 3.6 4.6
Min. 0.7 22 0.3 1.5
Max. 23.6 568 0.9 9.6
Median 2.1 190 1.2 4.0
Min. 0.4 56 1.5 1.9
May22 2.7 155 190 4.0
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market which started in July 2018. From the starting price of $118 the commodity´s price fell by 55% in real
106  David J. Howden terms. This decline is somewhat weak relative to the median decline of 66% over all recorded coal bear markets. The decline´s starting relative valuation of +0.9 standard deviations was also low relative to the median bear market starting relative valuation of +3.6 standard deviations. At the April 2020 low of $54 the commodity was 1.3 standard deviations undervalued, on par with the median starting valuation of a bull market advance. The loss of 2.2 standard deviations of valuation between 2018 and 2020 is somewhat below what would be expected given the median change in the measure during correction phases (4.6 standard deviations). Although the decline was weak by almost all measures, the advance since April 2020 has been strong and the balance of cycle evidence points to that low as marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in coal has lasted for just over two years and gained 190% in real terms. The weakest advance, during 192549, gained 56% in real terms. Since April 2020, the commodity has already gained 15%. As such, I expect the current cycle to gain an additional 175% in real terms by the time this cycle ends. Given that the average bull market in coal lasts for 2.1 years, I expect the current advance to end by May 2022.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, coal has increased its valuation within a band of +7.7 standard deviations (the weakest advance increased its valuation by +1.9 and the strongest increased by +9.6 standard deviations). In other words, never in the 120year price history under examination has coal failed to increase its valuation by less than +1.9 standard deviations over its bull market. Since the April 2020 low the commodity´s relative valuation has increased by +0.3 standard deviations, implying significant upside
Commodities, the Decade Ahead  107 potential. The April 2020 undervaluation of 1.3 standard deviations made the commodity more undervalued than 90% of all previous months. By the time the current bull market reaches its end, I expect coal to be trading at a price which is +2.7 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to coal trading at $155 by May 2022, a price that is +1.7 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for coal starts in January 1906. This means that to date there have been 1,314 5year holding periods and 1,254 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of coal is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of coal over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of coal as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 12.7% annual gain in coal over the coming 5year period. The forecast range is also strictly positive, ranging from 11.1 to 15.6%. The model explains 51% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of coal will breakeven by June 2025 with a 93% probability, and that the return will exceed 10% with a 63% probability.
108  David J. Howden
Commodities, the Decade Ahead  109
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Coal´s relative valuation of 1.0 standard deviations below its longterm mean is more extreme than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued not only in absolute terms, but also relative to the average commodity. As such, coal is the 15th most undervalued commodity of the group. I forecast that the commodity will yield an annual return of 12.7% over the coming five years, and 8.9% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, coal ranks 9th and 12th out of 43 commodities for the 5 and 10year return forecasts.
Over the next ten years, I expect the price of coal to increase by 8.9% annually. The forecast range is clustered around this level, ranging from 7.5 to 10.9%. The model explains 66% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that coal will breakeven by June 2030 with a probability of 99%, and that there is a 39% chance that its return will exceed 10% over this period.
Coal Forecast return rankings, out of 43 commodities Relative Valuation th
15 Coal 43 Commodity Avg.
1.0 0.7
Forecast returns: 5Year th
9
12.7 7.6
Probability that return exceeds 10%:
10Year th
12
8.9 5.9
5Year rd
3
63 39
10Year th
4
39 22
Finally, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 63% and 39% probability that coal can achieve this return over both periods, ranking coal 3rd and 4th out of the 43 markets. Given this evidence, it is highly likely that coal will yield superior returns relative to the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where coal is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1906 suggests that its current bull market should end in May 2022 at a high of $155. Since the commodity closed June 2020 at a price of $61, there is quite a bit of room for the price to advance to complete its current cycle in a manner consistent with the other eight advances since 1906.
110  David J. Howden
Commodities, the Decade Ahead  111 today and June 2025 the investor can expect a median annual return of 40.7% by buying coal. This expected return is somewhat lower at 12.7% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, coal rank 5th and 10th. This implies that the commodity should yield returns far above the average commodity over the next five and ten years. Taking the average of its rankings for these expected returns, coal ranks 7th out of the 43 commodities.
Coal Expected return rankings, out of 43 commodities Relative Valuation th
15 Coal 43 Commodity Median
Analysis of coal´s longerterm price behavior points to a steady price advance out to five years from now, with a continued bull market going out to 2030. By June 2025, I forecast coal to be trading at $112, and $144 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 51% of its 5year returns and 66% of its 10year returns explained since June 1990. In all cases, the price of coal is not expected to fall below its April 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying coal today and selling it at any date over the coming decade. For example, an expected price of $112 in June 2025 implies an annual rate of return of 12.7% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of coal, cycle analysis predicts a swift appreciation as the current bull market completes itself, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between
1.0 0.8
Expected average returns: 5Year th
5
40.7 21.2
10Year th
10
12.7 8.1
Overall Rank th
7
112  David J. Howden
Commodities, the Decade Ahead  113
Cobalt Cobalt has been valued since ancient times as a pigment for jewelry and paints, but it was not until 1735 that the element was isolated. Cobalt is a rare metal and highly toxic, leading industry to shift to cobaltfree alternatives where possible. Most modern applications of the metal surround the production of lithiumion batteries. Small amounts are alloyed for highperformance uses, such as turbines and jet engines. Cobalt is generally produced as a byproduct of copper and nickel mining. Production historically centered in Northern Europe, though the discovery of cobalt ore in New Caledonia in 1864 set in motion the decline of the European production. Discoveries in Canada in 1904 further reinforced this trend, but it was the large deposits in Katanga Province, Congo, in 1914 that all but ended European production.
Cobalt Production
Consumption
(% World)
DR Congo Russia Australia Philippines Cuba Rest of World
71 4 4 3 3 15
(% World)
China European Union Japan United States South Korea Rest of World
46 22 10 9 2 10
Sources: USGS, 2020: Observatory of Economic Complexity, 2020
Global cobalt output reached 140 thousand metric tons in 2019, a 94% increase over the previous decade. This increase came largely as a result of expanded production from the Democratic Republic of Congo, where output has surged by 150% since 2009 (an extra 60 thousand tons of cobalt mined per year). The DR Congo is also the world´s largest producer, a position it has held since surpassing Australia in 1997. Recycled scrap remains an important source of cobalt augmenting mined production. Recycled cobalt accounts for approximately 29% of consumption in the United States. Since 1999 world output has increased at an annual rate of 7.7%.
114  David J. Howden
Commodities, the Decade Ahead  115 There are approximately 7 million metric tons of cobalt in reserves globally. Over the last decade world cobalt reserves have grown by 6%, and 0.6% annually since 1999. The DR Congo maintains the world´s largest cobalt reserves, 3.6 million tons (51% of global reserves). Cobalt is one of the most concentrated metals in terms of reserves, and the top five countries account for 83% of the global amount. The United States has negligible reserves (less than 1% of global levels) although the ability to recycle large amounts of cobalt compensate for this limitation. The London Metal Exchange launched cobalt futures in 2010. The LME cobalt (CO) cash contract returned 1.8% to the investor over the past year. Futures trade in lots of 1 metric ton and are quoted in U.S. dollars per metric ton.
annually, with a forecast range between 9.9 and 13.3%. The forecast model explains 59% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that cobalt´s price will breakeven by June 2025 with an 84% probability, and that there is a 55% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat lower returns. I forecast cobalt´s price to increase by 9.1% annually until June 2030 with a forecast range between 7.6 and 12.1%. This model explains 44% of the metal´s 10year returns since June 1990. As such, there is a 96% probability that cobalt will breakeven over the coming decade, and a 43% chance that it will yield a return greater than 10%.
Cobalt: Forecast Summary 28,500 41,542 0.9
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Jul19 Aug21 263 224
5Year Forecast 5Year Annual Forecast Return, % 11.3 5Year Forecast Range, % (9.9, 13.3) 2 0.59 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, % The Bottom Line Cobalt closed June 2020 at a price of $28,500 per metric ton. Based on historical valuations dating to June 1937 (997 months) I estimate the fairvalue price of the commodity to be $41,543, implying an undervaluation of 0.9 standard deviations. This indicates that it is priced more cheaply today than 80% of all previous months. Analysis of the metal´s price cycles since 1937 points to the continuation of the secular bull market that started in July 2019 at the $26,500 low. Historically, the median bull market in cobalt has lasted for 2.1 years and increased its price by 271% in real terms. Following this pattern, the current bull market phase still has significant upside potential but should end after an additional 263% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of cobalt to increase by 11.3%
84 55
10Year Forecast 10Year Annual Forecast Return, % 9.1 10Year Forecast Range, % (7.6, 12.1) 0.44 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
96 43
116  David J. Howden
Historical Analysis Since June 1990, the nominal price of cobalt has increased from $8,277 per metric ton to the current close of $28,500 for an annual return of 4.2%. The alltime nominal high for the metal came in March 2008 at a price of $96,628. In real, inflationadjusted terms the metal´s price has trended around a price of $30,000 throughout its history. Cobalt´s real high was in June 1979, with its low forming in November 2002. As of June 2020, the metal´s price was lower than 52% of all prior monthly closing prices in real terms. More recently the metal´s price has been in a bull market since July 2019. From that month´s low of $26,500 a rally of 8% has ensued. The June 2020 close of $26,500 looks to be a stop along the way of the longterm secular advance.
Commodities, the Decade Ahead  117 bull market phase of a cycle. Each of the nine completed bull markets in cobalt that the commodity´s relative valuation can be calculated for has started from an undervalued position, with a median value of 1.0 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +1.8 standard deviations. Similarly, each of the metal´s eight completed bear markets that relative valuation data is available for has started from an overvalued position, with a median value of +1.4 standard deviations above the longterm mean (with the exception of the 198486 and 19992002 bear markets which started from a moderately undervalued positions). Over the course of each bear market cobalt continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 1.9 standard deviations. Cobalt: Historical Cycle Summary Declines
1519
1,680
37
n.a.
Mar55 Jun64
2633
1,519
50
n.a.
Jun79
Oct82
33252
4,729
90
4.2
Oct84
Jul86
11,755
4,057
67
0.6
Jan92 Nov93 31,442
11,847
64
0.7
32,210
11,122
68
0.4
Jun99 Nov02 20,929
6,290
72
0.2
Mar04 Feb06 51,018
24,219
55
2.1
Mar08 Mar16 96,628
22,350
79
3.3
94,000
26,500
73
2.2
Dec95 Jan99
Price Start End
Advances
Date Start End Sep40 Jul48
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Jul48
Mar55
1680
2,633
43
n.a.
Jun64
Jun79
1519
33,252
838
n.a.
Oct82 Oct84
4,729
11,755
132
1.4
Jul86
4,057
31,442
514
1.1
Nov93 Dec95 11,847
32,210
158
0.5
Jun99
11,122
20,929
86
0.7
Nov02 Mar04
6,290
51,018
684
1.0
Feb06 Mar08 24,219
96,628
271
0.4
Mar16 Mar18 22,350
94,000
301
1.1
26,500
28,500
8
1.0
Jan99
Mar18
Jul19
Jul19
Jan92
Jun20
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast
Over longer periods, cobalt´s price has failed to keep pace with general price inflation, resulting in a real yield of around zero for most of the past 80 years. Nominal returns have hovered around 3% for most of the metal´s history, with real returns averaging 0.1% annually between 1937 and 2010. The highest longterm nominal return the investor could have earned was 9.0% and resulted from buying cobalt in November 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 7.0% per year. Since 1937 the metal has gone through nine complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 271% in real terms, before being corrected by a median decline of 67%. The median bull market has lasted for just over two years, and its subsequent correction has taken more than three years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and
End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 9.3 90 4.2 5.6
Median 3.2 67 1.4 1.9
Min. 1.3 37 0.6 0.5
Max. 15.0 838 0.4 3.7
Median 2.1 271 1.0 1.8
Min. 0.4 43 1.4 0.5
Aug21 0.8 98,390 271 1.8
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in March 2018. From the starting price of $94,000 the metal´s price fell by 73% in real terms. This decline is on par with the median decline of 67% over all recorded cobalt bear markets. The decline´s starting relative valuation of +2.2 standard deviations was far more extreme than the median bear market starting relative valuation of +1.4
118  David J. Howden standard deviations. At the July 2019 low of $26,500 the metal was 1.0 standard deviations undervalued, right on par with the median starting valuation to a bull market advance. The loss of 3.2 standard deviations of valuation between 2018 and 2019 is more extreme than the median change in the measure during correction phases (1.9 standard deviations). As such, the balance of cycle evidence points to the July 2019 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in July 2019 what can we expect the future to hold? The median bull market in cobalt has lasted for just over two years and gained 271% in real terms. The weakest advance, during 194855, gained 43% in real terms. Since July 2019, the metal has already gained 8%. As such, I expect the current cycle to gain an additional 263% in real terms by the time this cycle ends. The current bear market has already lasted for nearly one year, and the median advance is only 2.1 years long. As such, I expect cobalt to complete its current rally in August 2021.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, cobalt has increased its valuation within a relatively narrow band of +3.2 standard deviations (the weakest advance increased its valuation by +0.5 and the strongest increased by +3.7 standard deviations). In other words, never in the 80year price history under examination has cobalt failed to increase its valuation by less than +0.5 standard deviations over its bull market. Since the July 2019 low the metal´s relative valuation has increased by +0.1 standard deviations, implying significant upside potential. The July 2019 undervaluation of 1.0 standard deviations made the commodity more undervalued than 84% of all previous months. By the time the current bull market reaches its end, I expect cobalt to be trading at a price which is +0.8 standard deviations
Commodities, the Decade Ahead  119 overvalued relative to its longterm average. In sum, cycle analysis points to cobalt trading at $98,390 by August 2021, a price that is +0.8 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for cobalt starts in June 1937. This means that to date there have been 937 5year holding periods and 877 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts.
As we have seen, the future return of cobalt is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of under
120  David J. Howden valuation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of cobalt over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of cobalt as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 11.3% annual gain in cobalt over the coming 5year period. The forecast range is also strictly positive, ranging from 9.9 to 13.3%. The model explains 59% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of cobalt will breakeven by June 2025 with an 84% probability, and that the return will exceed 10% with a 55% probability.
Commodities, the Decade Ahead  121
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future.
Cobalt Forecast return rankings, out of 43 commodities Relative Valuation th
20 Cobalt 43 Commodity Avg.
Over the next ten years, I expect the price of cobalt to increase by 9.1% annually. The forecast range is clustered around this level, ranging from 7.6 to 12.1%. The model explains 44% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that cobalt will breakeven by June 2030 with a probability of 96%, and that there is a 43% chance that its return will exceed 10% over this period.
0.9 0.7
Forecast returns: 5Year th
12
11.3 7.6
Probability that return exceeds 10%:
10Year th
10
9.1 5.9
5Year th
10Year th
13
10
55 39
43 22
Cobalt´s relative valuation of 0.9 standard deviations below its longterm mean is just below the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued not only in absolute terms, but also relative to the average commodity. As such, cobalt is the 20th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 11.3% over the coming five years, and 9.1% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, cobalt ranks 12th and 10th out of 43 commodities for the 5 and 10year return forecasts. Finally, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 42% probability that cobalt can achieve this return over both periods, ranking the commodity 13th and 10th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that cobalt will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where cobalt is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1937 suggests that its current bull market should peak in August 2021 at a high of $98,390. Since the metal closed June 2020 at a price of $28,500, there is quite a bit of room for the price to advance to complete its current cycle in a manner consistent with the other nine advances since 1937.
122  David J. Howden
Commodities, the Decade Ahead  123 Between today and June 2025 the investor can expect a median annual return of 50.5% by buying cobalt. This expected return is a far lower though still a respectable 11.3% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, cobalt ranks 3rd and 11th. This implies that the metal should yield returns far superior to the average commodity over the next five years, and a little better over the coming decade. Taking the average of its rankings for these expected returns, cobalt ranks 9th out of the 43 commodities.
Cobalt Expected return rankings, out of 43 commodities Relative Valuation th
20 Cobalt 43 Commodity Median
Analysis of cobalt´s longerterm price behavior points to a steady price advance out to five years from now, with a continued bull market going out to 2030. By June 2025, I forecast cobalt to be trading at $48,673, and $68,088 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 59% of its 5year returns and 44% of its 10year returns explained since June 1990. In all cases, the price of cobalt is not expected to fall below its July 2019 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying cobalt today and selling it at any date over the coming decade. For example, an expected price of $48,673 in June 2025 implies an annual rate of return of 11.3% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of cobalt, cycle analysis predicts a swift appreciation as the current bull market completes itself, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period.
0.9 0.8
Expected average returns: 5Year rd
3
50.5 21.2
10Year th
11
11.3 8.1
Overall Rank th
9
124  David J. Howden
Commodities, the Decade Ahead  125
Cocoa Cocoa beans form the basis of chocolate and are a common ingredient in regional Mesoamerican foods. The seed of the cacao tree, cocoa was introduced to Europe by the Spanish explorers. By the mid17th century, it had become a popular beverage. Cacao trees grow in a limited geographic zone, roughly 20 degrees on either side of the equator. Although the tree is native to the Amazon basin, it was introduced to the West Indies and the Philippines. Modern production is concentrated in West Africa.
Cocoa Production
Consumption
(% World)
Ivory Coast Ghana Indonesia Nigeria Cameroon Rest of World
37 18 9 6 6 23
(% World)
European Union United States Brazil Japan China Rest of World
46 18 5 4 2 24
Sources: Food and Agriculture Organization of the United Nations, 2018; Statista, 2019
Global cocoa output reached 5.3 million tons in 2018, a 23% increase over the previous decade. This increase came largely as a result of expanded production areas as production yields have fallen steadily over the past few decades. Production has also become increasingly concentrated with the top two producers, the Ivory Coast and Ghana, now accounting for well over half of global output. As recently as the mid1980s the two countries only contributed onethird of the word´s cocoa beans. Global production increases are also largely the result of these two countries, with the Ivory Coast and Ghana producing 42% and 39% more cocoa than they did a decade ago. Indonesia, the world´s third largest producer, has seen a continual decrease in production since 1993. The Ivory Coast is the world´s largest producer, a position it has held since knocking Ghana from the top spot in 1977. Since 1999 world output has increased at an annual rate of 3.1%.
126  David J. Howden
Commodities, the Decade Ahead  127 Globally, there are 11.8 million hectares of land devoted to cocoa production. This area is 23.8% more than there was a decade ago. Since 1999, the area of cocoa the world has harvested has increased by 3.1% annually. Decreasing yields have worked against these strong increases in land use to temper output increases. Globally, cocoa yields 0.4 metric tons to the hectare. Yields have not substantially changed in over 20 years and are far lower than their alltime peak set in 2006. The cocoa tree is highly sensitive to temperature and rain, creating large yearonyear variances in productivity. Cocoa first became exchange traded with the formation of the New York Cocoa Exchange in 1925. After merging with the New York Coffee and Sugar Exchange in 1979 it went on to be acquired by the Intercontinental Exchange. (Cocoa also trades on the New York Mercantile Exchange.) The ICE cocoa contract (CC) is the benchmark for world cocoa prices. The ICE cash contract returned 8.1% to the investor over the past year. Futures trade in lots of 10 metric tons and are quoted in U.S. dollars per metric ton.
The Bottom Line Cocoa closed June 2020 at a price of $2,251 per metric ton. Based on historical valuations dating to July 1959 (732 months) I estimate the fairvalue price of the commodity to be $3,099, implying an undervaluation of 1.3 standard deviations. This indicates that it is priced more cheaply today than 91% of all previous months. Analysis of the bean´s price cycles since 1959 points to the start of a new secular bull market. The August 2019 low of $2,161 looks to be a longterm bottom. Historically, the median bull market in cocoa has lasted for 2.3 years and increased its price by 194% in real terms. Following this pattern, the current bull market phase should be completed in December 2021 after an additional 190% gain in the bean´s inflationadjusted price. Over the coming 5year period, I forecast the price of cocoa to increase by 8.9% annually. The forecast model explains 47% of the variation in the bean´s 5year returns
since June 1990. Consequently, I forecast that cocoa´s price will breakeven by June 2025 with a 96% probability, and that there is a 41% chance that the bean´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast cocoa´s price to increase by 7.8% annually until June 2030 with a forecast range between 5.7 and 10.2%. This model explains 80% of the bean´s 10year returns since June 1990. As such, there is a 99% probability that cocoa will breakeven over the coming decade, and a 14% chance that it will yield a return greater than 10%.
Cocoa: Forecast Summary 2,251 3,100 1.3
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr19 Dec21 190 108
5Year Forecast 5Year Annual Forecast Return, % 8.9 5Year Forecast Range, % (8.9, 8.9) 2 0.47 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
96 41
10Year Forecast 10Year Annual Forecast Return, % 7.8 10Year Forecast Range, % (5.7, 10.2) 0.80 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 14
128  David J. Howden
Historical Analysis Since June 1990, the nominal price of cocoa has increased from $1,390 per metric ton to the current close of $2,251 for an annual return of 1.6%. The alltime nominal high for the bean came in July 1977 at a price of $5,184. In real, inflationadjusted terms the bean´s price has mostly fallen throughout its history. Cocoa´s real high was in July 1977, with its subsequent alltime low forming in November 2000. As of June 2020, the bean´s price was lower than 77% of all prior monthly closing prices in real terms. Over longer periods, cocoa´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the past sixty years. Nominal returns have hovered around 1% for most of the bean´s history, with real returns averaging 1.6% annually between 1959 and 2010. The highest longterm nominal return the investor could have earned was 4.9% and resulted by buying cocoa in November 2000 and holding it until today. Since inflation over that period averaged 2.9%, the investor´s return was somewhat more muted at 2.0% per year. More recently the bean´s price has been in a bull market since August 2019. From that month´s low of $2,161 a gain of 13% has ensued. The August 2019 bottom looks to be the end of a longterm secular decline and the current rally should continue.
Commodities, the Decade Ahead  129 bull market phase of a cycle. Each of the seven completed bull markets in cocoa has started from an undervalued position, with a median value of 1.2 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.1 standard deviations. Similarly, each of the bean´s seven completed bear markets has started from an overvalued position, with a median value of +1.3 standard deviations above the longterm mean. Over the course of each bear market cocoa continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 0.9 standard deviations. Cocoa: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Oct69 Dec71
1057
505
57
n.a.
Apr74 May75
2,444
1,196
56
n.a.
Jul77
Nov82
5,183
1,589
81
n.a.
May84 May92
2,816
1,042
73
n.a.
Aug97 Nov00
1,907
879
58
0.3
Jan03
Oct05
2,686
1,566
47
1.3
Feb11 Aug19
4,204
2,161
56
2.8
Date Start End Jun65 Oct69
Price Start End 279
1,057
221
n.a.
Dec71 Apr74
505
2,444
314
n.a.
May75 Jul77
1,196
5,183
278
n.a.
Nov82 May84
1,589
2,816
68
n.a.
May92 Aug97
1,042
1,907
59
1.1
Nov00 Jan03
879
2,686
194
1.2
Oct05 Feb11
1,566
4,204
141
0.7
Aug19 Jun20
2,161
2,432
13
1.5
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1959 the bean has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the bean´s price increase by 194% in real terms, before being corrected by a median decline of 57%. The median bull market has lasted for just over two years, and its subsequent correction has taken over three years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and
Max. 8.5 81 2.8 4.3
Median 3.3 57 1.3 0.9
Min. 1.1 47 0.3 0.6
Max. 5.3 314 0.7 2.5
Median 2.3 194 1.2 2.1
Min. 1.5 59 1.5 0.8
Dec21 0.6 6,351 194 2.1
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in February 2011. From the starting price of $4,204 the bean´s price fell by 56% in real terms. This decline is on par with the median decline of 57% over all recorded cocoa bear markets. The decline´s starting relative valuation of +2.8 standard deviations was the most overvalued price in cocoa´s history, and far above the median bear market starting relative valuation of +1.3 standard deviations. At the August 2019 low of $2,161 the bean was 1.5 standard deviations undervalued. This made the bean marginally more undervalued than the median start to a bull market advance (1.2 standard deviations). The loss of 4.3 standard deviations of valuation between 2011 and 2019 is also more than the median change in the measure during correction phases (0.9 standard deviations). As such, the balance of cycle evidence
130  David J. Howden points to the August 2019 low marking the end of a bear market decline and the start of a fresh secular bull market which continues to this day. If a new bull market did start in August 2019 what can we expect the future to hold? The median bull market in cocoa has lasted for over two years and gained 194% in real terms. The weakest advance, during 199297, gained 59% in real terms. Since August 2019, the bean has already gained 13%. As such, I expect the current cycle to gain an additional 190% in real terms by December 2021. This implies an expected annual return of 108% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, cocoa has increased its valuation within a relatively narrow band of +1.7 standard deviations (the weakest advance increased its valuation by +0.8 and the strongest increased by +2.5 standard deviations). In other words, never in the 60year price history under examination has cocoa failed to increase its valuation by less than +0.8 standard deviations over its bull market. Since the August 2019 low the bean´s relative valuation has increased by +0.4 standard deviations, implying its current change in valuation is still weaker than the weakest bull market to date. Coupled with the fact that the 13% price gain since 2019 is far less than the previous weakest bull market, there is evidence that there is still upside potential.
The August 2019 undervaluation of 1.5 standard deviations made the commodity more undervalued than 93% of all previous months. By the time the current bull market reaches its end, I expect cocoa to be trading at a price which is +0.6 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to cocoa trading at $6,351 on December 2021, a price that is +0.6 standard deviations overvalued.
Commodities, the Decade Ahead  131
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for cocoa starts in July 1959. This means that to date there have been 672 5year holding periods and 612 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of cocoa is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future.
I have developed two models to forecast the return of cocoa over these two different time periods – five years and ten years. In general, the 10year forecast model is more
132  David J. Howden robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of cocoa as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 8.9% annual gain in cocoa over the coming 5year period. The forecast range is centered on this 8.9% forecast return. The model explains 47% of the variation of the 300 5year returns of the bean since June 1990. Given this explanatory power of the model, I estimate that the price of cocoa will breakeven by June 2025 with a 96% probability, and that the return will exceed 10% with a 41% probability.
Commodities, the Decade Ahead  133 commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Cocoa´s relative valuation of 1.3 standard deviations below its longterm mean is significantly below the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly under. As such, cocoa is the 10th most undervalued commodity of the group.
Cocoa Forecast return rankings, out of 43 commodities Relative Valuation th
10 Cocoa 43 Commodity Avg.
Over the next ten years, I expect the price of cocoa to increase by 7.8% annually. The forecast range is clustered around this level, ranging from 5.7 to 10.2%. The model explains 80% of the variance in the bean´s 240 10year returns since June 1990. As such, I estimate that cocoa will breakeven by June 2030 with a probability of 99%, and that there is a 14% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other
1.3 0.7
Forecast returns: 5Year th
19
8.9 7.2
Probability that return exceeds 10%:
10Year th
16
7.8 5.9
5Year st
21
41 39
10Year
20th 14 22
I forecast that the bean will yield an annual return of 8.9% over the coming five years, and 7.8% over the coming decade. Both returns are marginally higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, cocoa ranks 19th and 16th out of 43 commodities for the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 41% probability that cocoa can achieve this return by June 2025 and 14% by June 2030, ranking it 21st and 20th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that cocoa will offer comparable to marginally higher returns compared with the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the bean is in its current price and valuation cycle. The evidence from cocoa´s price and valuation cycles since 1959 points to a probable surge in the bean´s price that will end in December 2021. At a high of $6,351 by that date, the bean will have advanced from its August 2019 low in a manner consistent with the other seven advances since 1959. Over this time, cocoa´s relative valuation should also increase from its current undervalued position of 1.3 standard deviations, to end this bull market rally overvalued by +0.6 standard deviations. Analysis of cocoa´s longerterm price behavior points to somewhat muted price increases five years from now, at least relative to this forecast cycle high, with a continued advance going out to 2030. These longerterm forecasts imply a sharp collapse after the current bull market completes, followed by a rally taking the grain back to highs near the alltime peaks set in 1977. By June 2025, I forecast cocoa to be trading at $3,449 per metric ton, and $4,754 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 47% of the bean´s 5year returns and 80% of its
134  David J. Howden 10year returns explained since June 1990. In all cases, the price of cocoa is not expected to fall below its August 2019 low at any time over the coming decade.
Commodities, the Decade Ahead  135 returns over the coming 5 and 10year periods, cocoa ranks 4th and 18th out of the 43 commodities. This implies that cocoa should yield a far superior return over the coming five years than the median commodity, though over the next decade its return should be comparable to the average. Taking the average of its rankings for these expected returns, coffee ranks 8th out of the 43 commodities.
Cocoa Expected return rankings, out of 43 commodities Relative Valuation th
10 Cocoa 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying cocoa today and selling it at any date over the coming decade. For example, an expected price of $3,449 in June 2025 implies an annual rate of return of 8.9% over the next five years if the investor buys cocoa today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of cocoa, cycle analysis predicts a swift appreciation peaking in December 2021, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 42.0% by buying cocoa. This expected return falls to 8.9% annually over the coming decade. In comparison to the expected median
1.3 0.8
Expected average returns: 5Year
10Year
th
18
42.0 21.2
8.9 8.1
4
th
Overall Rank th
8
136  David J. Howden
Commodities, the Decade Ahead  137
Coffee The earliest known evidence of coffee drinking appears in 15th century Yemen. From there coffee spread throughout the Arabian Peninsula, quickly reaching Italy by the 16th century due to the thriving trade between Venice and the Ottoman Empire. Despite appeals to ban the “Muslim drink”, its use was widely adopted throughout Europe after it was deemed an acceptable beverage for Christians by Pope Clement VIII in 1600. Long known as social places for intellectual and political movements, the first coffee house was opened in Constantinople in 1475. They soon spread through all regions of the Ottoman Empire. The first European coffee house opened in Rome in 1645. (The oldest still in existence today is Queen´s Lane Coffee House, located in Oxford, established in 1654.) The ubiquitous coffee break has been a part of the informal employment contract since its creation by the wives of Norwegian immigrants in Wisconsin in the late 19th century. Due to its effects as a stimulant, coffee has long competed against alcohol. Upon reaching North America during the Colonial Period, coffee proved to be not as successful as it had been in Europe, with alcoholic beverages or tea being preferred. The Boston Tea Party reduced not only the availability of, but also the demand for British tea and solidified coffee´s place in American dietary and social habits. Coffee declined in Britain during the colonial period owing the greater ease of sourcing tea, and the cheaper tea supplies from India. Several species of shrubs from which coffee can be extracted from their berries exist, with the Robusta and Arabica species being the most common. Arabica is the more highly regarded, and the plant originally stems from the highlands spanning southeastern Sudan, northeastern Ethiopia, and northern Kenya. Production spread away from these areas during the 18th century, moving to the French territory of Martinique in the Caribbean in the 1720s. Almost all Arabica coffee cultivated in the world today derives from this island. SaintDomingue (now Haiti) cultivated half of the world´s coffee by 1734. Having been introduced to Brazil in 1727, the country became the world´s largest producer by 1852, a position it has held to this day. Coffee production is a vital cash crop in many developing countries, and it is estimated that over one hundred million people in developing countries (mainly located in SubSaharan Africa and Central America) are dependent on coffee as their primary source of income. Robusta beans are smaller in size and brew a stronger, more bitter flavor because of their higher caffeine content. They account for approximately onethird of world trade in coffee. The other twothirds of coffee trades in Arabica beans. These larger beans are generally favored by the higher end of the market owing to their sweeter, lighter, and smoother taste.
138  David J. Howden
Commodities, the Decade Ahead  139
Coffee Production
Consumption
(% World)
Brazil Vietnam Colombia Indonesia Ethiopia Rest of World
30 13 6 5 3 43
(% World)
European Union United States Brazil Japan Philippines Rest of World
25 15 13 4 3 41
Source: USDA, 2020
Global coffee output reached 10.3 million tons in 2018, a 21% increase over the previous decade. This increase came largely as a result of increased productivity, and less so by expanded production area. Most of the increase in output is attributable to Vietnam which, at 1.6 million tons or annual production, produces 53% more than a decade ago. Brazil is the world´s largest producer at 3.6 million tons of coffee, a position it has maintained for all but one year (1976) since 1960. Since 1999 world output has increased at an annual rate of 2.2%. Globally, there are 10.6 million hectares of land devoted to coffee production. This area is has remained essentially unchanged for over 30 years, notwithstanding some large yearonyear variations. Increasing yields have more than compensated for the relative constancy in areas harvested to explain the large increase in production. Globally, coffee yields 1.0 metric tons to the hectare. This represents a 31% increase over the past decade, and 2.2% annually since 1999. Over the past 30 years this growth in yields has steadily increased from 1% annually during the 1990s to an average of 2% since then. Coffee first traded on an exchange with the formation of the Coffee Exchange in the City of New York in
1882. It was later absorbed by the New York Board of Trade which has been, since 2007, a subsidiary of the Intercontinental Exchange. Contracts for Arabica coffee are traded on the New York Mercantile Exchange and, in higher volume, on the ICE. (Robusta coffee also trades on the ICE.) The ICE Arabica coffee cash contract (C) returned 8.7% to the investor over the past year. Futures trade in lots of 37,500 pounds and are quoted in U.S. cents per pound.
The Bottom Line Coffee closed June 2020 at a price of $1.49 per pound. Based on historical valuations dating to January 1890 (1,566 months) I estimate the fairvalue price of the commodity
Coffee: Forecast Summary 149 168 0.4
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr19 Aug25 314 32
5Year Forecast 5Year Annual Forecast Return, % 2.9 5Year Forecast Range, % (2.1, 3.5) 2 0.72 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
67 14
10Year Forecast 10Year Annual Forecast Return, % 4.6 10Year Forecast Range, % (2.7, 7.4) 0.62 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
90 7
140  David J. Howden
Commodities, the Decade Ahead  141
to be $1.68, implying an undervaluation of 0.4 standard deviations. This indicates that it is priced more cheaply today than 67% of all previous months. Analysis of the bean´s price cycles since 1900 points to the continuation of its yearold secular bull market. The April 2019 low of $1.23 looks to be a longterm bottom. Historically, the median bull market in coffee has lasted for 6.3 years and increased its price by 333% in real terms. Following this pattern, the current bull market phase should be completed in August 2025 after an additional 314% gain in the bean´s inflationadjusted price. Over the coming 5year period, I forecast the price of coffee to increase by 2.9% annually, with a forecast range between 2.1 and 3.5%. The forecast model explains 72% of the variation in the bean´s 5year returns since June 1990. Consequently, I forecast that coffee´s price will breakeven by June 2025 with a 67% probability, and that there is a 14% chance that the bean´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast coffee´s price to increase by 4.6% annually until June 2030 with a forecast range between 2.7 and 7.4%. This model explains 62% of the bean´s 10year returns since June 1990. As such, there is a 90% probability that coffee will breakeven over the coming decade, and a 7% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of coffee has increased from $0.95 per pound to the current close of $1.49 for an annual return of 1.5%. The alltime nominal high for the bean came in May 1997 at a price of $3.31. In real, inflationadjusted terms the bean´s price has mostly fallen throughout its history with the exception of the price spikes in the 1950s and 1970s. Coffee´s real high was in March 1977, with its subsequent alltime low forming in July 2002. As of June 2020, the bean´s price was lower than 79% of all prior monthly closing prices in real terms. Over longer periods, coffee´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 1% for most of the 20th century. Nominal returns have hovered around 2% for most of the bean´s history, with real returns averaging 1.0% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 5.5% and resulted by buying coffee in July 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor´s return was 3.5% per year. More recently the bean´s price has been in a bull market since April 2019. From that month´s low of $0.23 a gain of 19% has ensued leading up to the recent June 2020 high. The April 2019 bottom looks to be the end of a longterm secular decline and the recent advance should mark the early stages of a multiyear rally. Since 1900 the bean has gone through eight complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the bean´s price increase by 333% in real terms, before being corrected by a median decline of 72%. The median bull market has lasted for just over six years, and its subsequent correction has taken over sixandahalf years to complete.
The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the eight completed bull markets in coffee has started from an undervalued position, with a median value of 1.3 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.8 standard deviations. Similarly, each of the bean´s eight completed bear markets has started from an overvalued position, with a median value of +2.8 standard deviations above the longterm mean. Over the course of each bear market coffee continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.5 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in April 2011. From the starting price of $3.22 the bean´s price fell by 66% in real terms. This decline is on par with the median decline of 72% over all recorded coffee bear markets. The decline´s starting relative valuation of +4.1 standard deviations was the most overvalued price since 1977, and far above the median bear market starting relative valuation of +2.8 standard deviations. At the April 2019 low of $1.23 the bean was 0.9 standard deviations undervalued. This made the bean marginally more undervalued than the median start to a bull market advance (1.3 standard deviations). The loss of 5.0 standard deviations of valuation between 2011 and 2019 is also about on par with the median change in the measure during correction phases (4.5 standard deviations). As such, the balance of cycle evidence points to the April 2019 low marking the end of a bear market decline and the start of a fresh secular bull market which continues to this day. If a new bull market did start in April 2019 what can we expect the future to hold? The median bull market in coffee has lasted for over just over six years and gained 333% in real terms. The weakest advance, during 191819, gained 140% in real terms. Since
142  David J. Howden
Commodities, the Decade Ahead  143
April 2019, the bean has already gained 19%. As such, I expect the current cycle to gain an additional 314% in real terms by August 2025. This implies an expected annual return of 32% by the time the present bull market reaches completion. Coffee: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Nov11 Aug18
15
8
67
n.a.
Jun19
Apr21
23
6
75
3.3
Jan25 Mar31
10
5
75
2.8
Mar34 May38
10
4
58
0.0
Mar54 Jun69
95
40
69
2.0
Mar77 Aug92
315
53
93
7.6
May97 Jul02
330
57
85
1.9
322
123
66
4.1
Date Start End Jan03 Nov11
Apr19
Real Start Rel. Change, % Val, σ
5
15
172
n.a.
Jun19
8
23
140
n.a.
Apr21 Jan25
6
10
312
1.2
Mar31 Mar34
5
10
138
1.9
May38 Mar54
4
95
938
1.5
Jun69 Mar77
40
315
386
1.5
Aug92 May97
53
330
441
1.0
Aug18
Apr11
Price Start End
Jul02
Apr11
57
322
354
1.3
Apr19
Jun20
123
149
19
0.9
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 15.4 93 7.6 8.6
Median 6.5 72 2.8 4.5
Min. 1.8 58 0.0 1.5
Max. 15.8 938 0.9 9.1
Median 6.3 333 1.3 3.8
Min. 0.8 138 1.9 1.9
Aug25 2.9 533 333 3.8
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, coffee has increased its valuation within a band of +7.2 standard deviations (the weakest advance increased its valuation by +1.9 and the strongest increased by +9.1 standard deviations). In other words, never in the 120year price history under examination has coffee failed to increase its valuation by less than +1.9 standard deviations over its bull market. Since the April 2019 low the bean´s relative valuation has increased by +0.5 standard deviations, implying its change in valuation has is still weaker than the weakest bull market in over a century. Coupled with the fact that the 19% price gain since 20019 is far lower than the previous weakest bull market, there is evidence that there is still upside potential. The April 2019 undervaluation of 0.9 standard deviations made the commodity more undervalued than 82% of all previous months. By the time the current bull market reaches its end, I expect coffee to be trading at a price which is +2.9 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to coffee trading at $5.33 on August 2025, a price that is +2.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for coffee starts in January 1890. This means that to date there have been 1,506 5year holding periods and 1,446 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of coffee is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of coffee over these two different time periods – five years and ten years. In general, the 10year forecast model is more
144  David J. Howden
Commodities, the Decade Ahead  145
robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of coffee as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 2.9% annual gain in coffee over the coming 5year period. The forecast range is also strictly positive, ranging from 2.1 to 3.5%. The model explains 72% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of coffee will breakeven by June 2025 with a 67% probability, and that the return will exceed 10% with a 14% probability.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future.
Coffee Forecast return rankings, out of 43 commodities Over the next ten years, I expect the price of coffee to increase by 4.6% annually. The forecast range is clustered around this level, ranging from 2.7 to 7.4%. The model explains 62% of the variance in the bean´s 240 10year returns since June 1990. As such, I estimate that coffee will breakeven by June 2030 with a probability of 90%, and that there is a 7% chance that its return will exceed 10% over this period.
Relative Valuation
Coffee 43 Commodity Avg.
Forecast returns:
Probability that return exceeds 10%:
5Year
10Year
5Year
10Year
32nd
36th
28th
34th
25th
0.4 0.7
2.9 7.6
4.6 5.9
14 39
7 22
Coffee´s relative valuation of 0.4 standard deviations below its longterm mean is less undervalued than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the bean is slightly undervalued
146  David J. Howden in absolute terms, but is actually overvalued relative to the average commodity. As such, coffee is the 32nd most undervalued commodity of the group. I forecast that coffee will yield an annual return of 2.9% over the coming five years, and 4.6% over the coming decade. Both returns are somewhat lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, coffee ranks 36th and 28th out of 43 commodities for the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 14% probability that coffee can achieve this return by June 2025 and 7% by June 2030, ranking the bean 34th and 25th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that coffee will underperform the average commodity over both the coming 5and 10year periods.
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the bean is in its current price and valuation cycle. The evidence from coffee´s price and valuation cycles since 1900 points to a probable surge in the bean´s price that will end in August 2025. At a high of $5.33 by that date, the grain will have advanced from its April 2019 low in a manner consistent with the other eight advances since 1900. Over this time, coffee´s relative valuation should also increase from its current undervalued position of 0.4 standard deviations, to end this bull market rally overvalued by +2.9 standard deviations. Analysis of coffee´s longerterm price behavior points to somewhat muted prices five years from now, at least relative to this forecast cycle high, with a continued advance
Commodities, the Decade Ahead  147 going out to 2030. These longerterm forecasts imply a sharp collapse after the current bull market completes. By June 2025, I forecast coffee to be trading at $1.72 per bushel, and $2.34 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 72% of the bean´s 5year returns and 62% of its 10year returns explained since June 1990. In all cases, the price of coffee is not expected to fall below its March 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying coffee today and selling it at any date over the coming decade. For example, an expected price of $1.72 in June 2025 implies an annual rate of return of 2.9% over the next five years if the investor buys coffee today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of coffee, cycle analysis predicts a swift appreciation peaking in March 2021, and the period valuation models also forecast price increases, but over both shorter and longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 37.8% by buying coffee. This expected return falls to 4.6% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, coffee ranks 8th and 32nd out of the 43 commodities. This implies that coffee should yield a superior return over the coming five years to the median commodity, though over the next decade its return should be lower than the average. Taking the average of its rankings for these expected returns, coffee ranks 33rd out of the 43 commodities.
Coffee Expected return rankings, out of 43 commodities Relative Valuation nd
32 Coffee 43 Commodity Median
0.4 0.8
Expected average returns: 5Year th
8
37.8 21.2
10Year nd
32
4.6 8.1
Overall Rank rd
33
148  David J. Howden
Commodities, the Decade Ahead  149
Copper Copper has been used to advance human civilization since at least 9000 BC. Copper is one of the few metals that can be used directly in its native form, without the use of smelting. This led to very early human uses of the metal. Evidence suggests that only gold and iron (meteoric, not smelted) were used as metals by humans before copper. Smelting copper was first discovered in China around 2800 BC, and this discovery spurred on other smelting discoveries, notably iron. Copper is also the first metal to be cast into a shape (c. 4000 BC) and the first metal to be purposefully alloyed with another metal, tin, to create bronze (c. 3500 BC). This latter discovery gave rise to the Bronze Age. Most uses of copper are confined to electrical wire (60%), roofing and plumbing (20%) and industrial machinery (15%). Bronze production still accounts for 5% of its total use. Copper´s natural antimicrobial properties create very small demands by the textile and jewelry industry, as well as folk medicine. Electric cars use nearly four times the amount of copper as conventional gasolinepowered cars, giving rise to a new, growing source of demand. The United States Geological Survey estimates that 2.8 billion tons of copper have been discovered throughout history. Much of this is still in use, and if melted it would form a cube measuring nearly 700 meters on each side. Because of its widespread use in industrial applications, the demand for copper is closely related to macroeconomic events.
Global copper output reached 20 million metric tons in 2019, a 26% increase over the previous decade. This increase came largely as a result of expanded production from
150  David J. Howden Peru which has more than doubled its annual output from 1.1 million metric tons in 2009 to 2.4 million metric tons last year. Recycled scrap remains an important source of copper augmenting mined production. Globally, 9% of the global copper supply comes from recycled sources, with scrap accounting for 35% of consumption in the United States. Brass and wirerods are the largest sources of scrap copper at over 80% of recycled material. Since 1999 world output has increased at an annual rate of 2.3%. Chile is the world´s largest producer at 5.6 million metric tons in 2019, a position it has held since records begin in 1990. There are approximately 870 million metric tons of copper in reserves globally. Over the last decade world copper reserves have grown by 4.9% annually. Chile maintains the world´s largest copper reserves, 200 million tons (23% of global reserves). Although just five countries account for 56% of global reserves, the metal is found widely in smaller amounts throughout the world. The United States has small reserves (approximately 5.9% of global levels) although the ability to recycle large amounts of copper compensate for this limitation. The London Metal Exchange launched copper contracts at its founding, in 1877. The metal is also traded on the Commodity Exchange. The LME copper (CA) cash contract returned 1.1% to the investor over the past year. Futures trade in lots of 25 metric tons and are quoted in U.S. dollars per metric ton.
The Bottom Line Copper closed June 2020 at a price of $6,038 per metric ton. Based on historical valuations dating to June 1850 (2,041 months) I estimate the fairvalue price of the commodity to be $7,369, implying an undervaluation of 0.6 standard deviations. This indicates that it is priced more cheaply today than 74% of all previous months.
Commodities, the Decade Ahead  151 Analysis of the metal´s price cycles since 1900 points to the continuation of the secular bull market that started in March 2020 at the $4,797 low. Historically, the median bull market in copper has lasted for 4.3 years and increased its price by 111% in real terms. Following this pattern, the current bull market phase should end after an additional 84% gain in the metal´s inflationadjusted price.
Copper: Forecast Summary 6,038 7,369 0.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Mar20 Jul24 84 16
5Year Forecast 5Year Annual Forecast Return, % 10.5 5Year Forecast Range, % (10.1, 11.2) 2 0.47 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
86 52
10Year Forecast 10Year Annual Forecast Return, % 7.5 10Year Forecast Range, % (6.7, 11.7) 2 0.83 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 22
Over the coming 5year period, I forecast the price of copper to increase by 10.5% annually, with a forecast range between 10.1 and 11.2%. The forecast model explains 47% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that copper´s price will breakeven by June 2025 with an 86% probability, and that there is a 52% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat lower returns. I forecast copper´s price to
152  David J. Howden increase by 7.5% annually until June 2030 with a forecast range between 6.7 and 11.7%. This model explains 83% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that copper will breakeven over the coming decade, and a 22% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of copper has increased from $2,623 per metric ton to the current close of $6,038 for an annual return of 2.8%. The alltime nominal high for the metal came in February 2011 at a price of $9,858. In real, inflationadjusted terms the metal´s price has remained somewhat flat throughout its history, mostly trading between $4,500 and $7,500 per metric ton. Copper´s real high was in December 1916, with its low forming in November 1980. As of June 2020, the metal´s price was lower than 52% of all prior monthly closing prices in real terms. Over longer periods, copper´s price has just kept pace with price inflation, resulting in a real yield of around 0.5% for most of the 20th century. Nominal returns have hovered around 3.5% for most of the metal´s history, with real returns averaging 0.4% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 8.4% and resulted by buying copper in September 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 6.5% per year.
Commodities, the Decade Ahead  153 advance. Since 1900 the metal has gone through ten complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 111% in real terms, before being corrected by a median decline of 60%. The median bull market has lasted for just over four years, and its subsequent correction has taken seven years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the ten completed bull markets in copper has started from an undervalued position, with a median value of 1.1 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.0 standard deviations. Copper: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Mar07 Oct14
546
262
57
3.4
Dec16 Aug21
734
267
76
2.8
Mar29 Dec32
490
110
71
1.2
Mar37 Oct46
363
325
39
0.3
Apr56 Feb64
907
655
37
2.1
May74 Oct86
1,858
1,652
61
0.8
Jan89
Oct93
3,300
1,615
59
3.0
Jun95
Oct01
3,093
1,360
62
1.6
Jul07
Dec08
8,159
2,902
65
2.2
Feb11 Mar20
9,857
4,797
58
3.1
Date Start End Oct02 Mar07
Price Start End 258
546
107
1.5
Oct14 Dec16
262
734
144
1.4
Aug21 Mar29
267
490
91
0.6
Dec32 Mar37
110
363
204
2.1
Oct46 Apr56
325
907
115
0.3
Feb64 May74
655
1,858
80
1.0
Oct86 Jan89
1,652
3,300
82
1.6
Oct93 Jun95
1,615
3,093
83
0.9
Oct01
Jul07
1,360
8,159
411
2.1
Dec08 Feb11
2,902
9,857
223
0.3
Mar20 Jun20
4,797
6,038
27
1.1
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
More recently the metal´s price has been in a bear market since February 2011. From that month´s high of $9,857 a decline of 58% has ensued. The March 2020 close of $4,797 looks to be the end of this decline and the start of a new longterm secular
Max. 12.4 76 3.4 4.8
Median 7.0 60 2.2 3.4
Min. 1.4 37 0.3 0.6
Max. 10.3 411 0.3 4.9
Median 4.3 111 1.1 3.0
Min. 1.7 80 2.1 1.8
Jul24 1.9 10,127 111 3.0
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
Similarly, each of the metal´s ten completed bear markets has started from an overvalued position, with a median value of +2.2 standard deviations above the longterm mean. Over the course of each bear market copper continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.4 standard
154  David J. Howden deviations. The most recently completed phase of its cycles was the bear market decline which started in February 2011. From the starting price of $9,857 the metal´s price fell by 58% in real terms. This decline is on par with the median decline of 60% over all recorded copper bear markets. The decline´s starting relative valuation of +3.1 standard deviations was far more extreme than the median bear market starting relative valuation of +2.2 standard deviations. At the March 2020 low of $4,797 the metal was 1.1 standard deviations undervalued, right on par with the median starting valuation to the median bull market advance. The loss of 4.2 standard deviations of valuation between 2011 and 2020 is also consistent with the median change in the measure during correction phases (3.4 standard deviations). As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in copper has lasted for over four years and gained 111% in real terms. The weakest advance, during 196474, gained 80% in real terms. Since March 2020, the metal has already gained 27%. As such, I expect the current cycle to gain an additional 84% in real terms by the time this cycle ends.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, copper has increased its valuation within a relatively narrow band of +3.1 standard deviations (the weakest advance increased its valuation by +1.8 and the strongest increased by +4.9 standard deviations). In other words, never in the 120year price history under examination has copper failed to increase its valuation by less than +1.8 standard deviations over its bull market. Since the March 2020 low the metal´s relative valuation has increased by +0.5 standard deviations, implying significant
Commodities, the Decade Ahead  155 upside potential. The March 2020 undervaluation of 1.1 standard deviations made the commodity more undervalued than 86% of all previous months. By the time the current bull market reaches its end, I expect copper to be trading at a price which is +1.9 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to copper trading at $10,127 by July 2024, a price that is +1.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like.
We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for copper starts in June 1850. This means that to date there have been 1,981 5year holding periods and 1,921 10year periods to use as inputs to make forecasts
156  David J. Howden over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of copper is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of copper over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of copper as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
Commodities, the Decade Ahead  157 I estimate that copper will breakeven by June 2030 with a probability of 99%, and that there is a 22% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Copper´s relative valuation of 0.6 standard deviations below its longterm mean is near the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by roughly the same amount as the average commodity. As such, copper is the 27th most undervalued commodity of the group.
Copper Forecast return rankings, out of 43 commodities Relative Valuation th
27 Copper 43 Commodity Avg.
I forecast a 10.5% annual gain in copper over the coming 5year period. The forecast range is also strictly positive, ranging from 10.1 to 11.2%. The model explains 47% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of copper will breakeven by June 2025 with an 86% probability, and that the return will exceed 10% with a 52% probability. Over the next ten years, I expect the price of copper to increase by 7.5% annually. The forecast range is clustered around this level, ranging from 6.7 to 11.7%. The model explains 83% of the variance in the metal´s 240 10year returns since June 1990. As such,
0.6 0.7
Forecast returns: 5Year th
14
10.5 7.6
Probability that return exceeds 10%:
10Year th
17
7.5 5.9
5Year th
10Year th
14
16
52 39
22 22
I forecast that the metal will yield an annual return of 10.5% over the coming five years, and 7.5% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, copper ranks 14th and 17th out of 43 commodities for the 5 and 10year return forecasts. Finally, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 52% probability that copper can achieve this return over the next five years and 22% by 2030, ranking the metal 14th and 16th out of the 43 markets for both probabilities. Given this evidence, it is likely that copper will yield comparable to mildly better performance than the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where copper is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1900 suggests that its current bull market should end in July 2024 at a high of $10,127. Since
158  David J. Howden the metal closed June 2020 at a price of $4,797, there is quite a bit of room for the price to advance to complete its current cycle in a manner consistent with the other ten advances since 1900.
Commodities, the Decade Ahead  159 horizons during which these changes take place are much less standard. In the case of copper, cycle analysis predicts a swift appreciation as the current bull market completes itself, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 14.8% by buying copper. This expected return is a somewhat more muted at 10.4% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, copper rank 27th and 14th. This implies that the metal should yield returns about on par with the average commodity over the coming decade and a little lower return over the next five years. Taking the average of its rankings for these expected returns, copper ranks 26th out of the 43 commodities.
Copper Expected return rankings, out of 43 commodities Relative Valuation th
27 Copper 43 Commodity Median
Analysis of copper´s longerterm price behavior points to a steady price advance out to five years from now, with a continued bull market going out to 2030 taking the metal to new alltime highs. By June 2025, I forecast copper to be trading at $9,929, and $12,413 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 47% of its 5year returns and 83% of its 10year returns explained since June 1990. In all cases, the price of copper is not expected to fall below its March 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying copper today and selling it at any date over the coming decade. For example, an expected price of $9,929 in June 2025 implies an annual rate of return of 10.5% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time
0.6 0.8
Expected average returns: 5Year th
27
14.8 21.2
10Year th
14
10.4 8.1
Overall Rank th
26
160  David J. Howden
Commodities, the Decade Ahead  161
Corn Corn, or maize as it is known outside North America, is the most widely produced staple food in the world. Little of this production, however, is consumed by humans. The majority is processed into ethanol, animal feed or other corn products such as starch or syrup. Corn was first domesticated by the indigenous peoples of southern Mexico around 8000 BC. It has since spread and is widely cultivated throughout the world, especially in the United States.
Although sweet corn can be consumed directly as kernels, most human consumption comes in the form of corn meal. Corn flour is common in Central America, polenta in Italy, angu in Brazil or grits in the Southern United States. The “Hot Corn Girls” hawking corn on the cob in New York City in the early 19th century have since been replaced by the ubiquitous hot dog carts. Corn is also distilled into grain alcohol, with bourbon being the most common example. Biofuels, such as corn ethanol, are an important new demand for corn and in general ethanol prices track corn
162  David J. Howden prices closely. In the United States, approximately onethird of corn production is processed as ethanol. Nearly half is used as livestock feed, and 15% is exported. The remainder is split between corn starch and syrup production, with human consumption amounting to around 3%. Global corn output reached nearly 1.2 billion tons in 2018, a 38% increase over the previous decade. This increase came largely as twofold result of expanded production areas as well as increased production yields. China has been the largest driver of increased output, with production surging by 55% over the past decade for an additional 91 million tons of corn annually. The United States remains the world´s largest producer, a position it has held since records begin in 1960. Since 1999 world output has increased at an annual rate of 3.4%. Globally, there are 193 million hectares of land devoted to corn production. This area is 22.1% more than there was a decade ago and, since 1999, the area of corn the world has harvested has increased at a rate of 1.8% annually. Increasing yields have augmented the increase in areas harvested to result in the large surge of global output. Globally, corn yields 5.9 metric tons to the hectare. This represents an 18.6% increase over the past decade, and 1.5% annually since 1999. Yields have increased by 1.5% annually since the late 1980s, and this trend shows no signs of reversing soon. Global corn stocks are near their late 1990s highs at 77 million tons in 2018. Over the past decade, the average annual surplus of corn production has been roughly 2.5 million tons, leaving an average ending inventory of 57.5 million tons. Since 2008 corn stocks have increased by 4.8% annually. At 7% of corn output, stocks are down somewhat from their highs relative to output set in the 1990s, though relatively stable since the mid2000s. Corn futures have been traded on the Chicago Board of Trade since 13 March 1851. The CBOT corn (C) cash contract returned 20.0% to the investor over the past year. Futures trade in lots of 5,000 bushels and are quoted in U.S. cents per bushel.
Commodities, the Decade Ahead  163
The Bottom Line Corn closed June 2020 at a price of $3.48 per bushel. Based on historical valuations dating to January 1860 (1,926 months) I estimate the fairvalue price of the commodity to be $4.40, implying an undervaluation of 0.8 standard deviations. This indicates that it is priced more cheaply today than 78% of all previous months. Analysis of corn´s price cycles since 1900 points to the start of a new secular bull market. The April 2020 low of $3.13 looks to be a longterm bottom. Historically, the median bull market in corn has lasted for 4.3 years and increased its price by 235% in real terms. Following this pattern, the current bull market phase should be completed in August 2024 after an additional 224% gain in the commodity´s inflationadjusted price.
Corn: Forecast Summary 348 440 0.8
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr20 Aug24 224 33
5Year Forecast 5Year Annual Forecast Return, % 7.7 5Year Forecast Range, % (7.6, 7.7) 2 0.51 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
87 37
10Year Forecast 10Year Annual Forecast Return, % 6.0 10Year Forecast Range, % (4.5, 8.2) 2 0.68 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
98 10
164  David J. Howden Over the coming 5year period, I forecast the price of corn to increase by 7.7% annually, with a forecast range between 4.6 and 7.7%. The forecast model explains 51% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that corn´s price will breakeven by June 2025 with an 87% probability, and that there is a 37% chance that the commodity´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast corn´s price to increase by 6.0% annually until June 2030 with a forecast range between 4.5 and 8.2%. This model explains 68% of the commodity´s 10year returns since June 1990. As such, there is a 98% probability that corn will breakeven over the coming decade, and a 10% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of corn has increased from $2.97 per bushel to the current close of $3.48 for an annual return of 0.5%. The alltime nominal high for the commodity came in August 2012 at a price of $8.43. In real, inflationadjusted terms the commodity´s price has mostly fallen throughout its history. Corn´s real high was in November 1917, with its subsequent alltime low forming in October 2005. As of June 2020, the commodity´s price was lower than 89% of all prior monthly closing prices in real terms.
Commodities, the Decade Ahead  165 the investor could have earned was 4.5% and resulted by buying corn in October 2005 and holding it until today. Since inflation over that period averaged 2.8%, the investor´s real returns were somewhat more muted at 1.7% per year. More recently the commodity´s price has been in a bear market since August 2012. From that month´s high of $8.43 a loss of 67% ensued until the recent April 2020 low. This bottom looks to be the end of a longterm secular decline which should usher in a multiyear rally. Corn: Historical Cycle Summary Declines Date Start End Jul02 Jan07
Price Start End
Advances Real Start Rel. Change, % Val, σ
72
42
46
2.9
Jan13
80
48
46
2.8
Nov17 Oct21
221
45
84
2.9
Jan25 Dec32
124
23
75
0.1
Apr37 Aug39
135
45
66
0.3
Jan48
Oct71
270
106
77
0.9
Sep74 Oct05
397
182
88
1.1
Aug12 Apr20
843
313
67
3.8
Sep08
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jan07
Sep08
42
80
93
0.6
Jan13
Nov17
48
221
235
1.3
Oct21 Jan25
45
124
177
2.6
Dec32 Apr37
23
135
436
1.9
Aug39 Jan48
45
270
249
1.1
Oct71 Sep74
106
397
201
1.1
Oct05 Aug12
182
843
301
1.2
Apr20 Jun20
313
348
11
1.0
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Over longer periods, corn´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the 20th century. Nominal returns have hovered around 1.5% for most of the commodity´s history, with real returns averaging 1.6% annually between 1900 and 2010. The highest longterm nominal return
Max. 31.1 88 3.8 5.5
Median 6.1 71 2.0 2.9
Min. 2.3 46 0.1 1.4
Max. 8.4 436 0.6 5.0
Median 4.3 235 1.2 2.7
Min. 1.7 93 2.6 2.0
Aug24 1.7 1,046 235 2.7
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the commodity has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the commodity´s price increase by 235% in real terms, before being corrected by a median decline of 71%. The median bull market has lasted for just under fourandahalf years, and its subsequent correction has taken over six years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in corn has started from an undervalued position, with a median value of 1.2 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.7 standard deviations. Similarly, each of the commodity´s eight completed bear markets has started from an
166  David J. Howden overvalued position, with a median value of +2.0 standard deviations above the longterm mean. Over the course of each bear market corn continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.9 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in August 2012. From the starting price of $8.43 the commodity´s price fell by 67% in real terms. This decline is on par with the median decline of 71% over all recorded corn bear markets. The decline´s starting relative valuation of +3.8 standard deviations was the most overvalued in corn´s history, and somewhat higher than the median bear market starting relative valuation of +2.1 standard deviations. At the April 2020 low of $3.13 the commodity was 1.0 standard deviation undervalued. This made corn marginally less undervalued than the median start to a bull market advance (1.2 standard deviations). The loss of 4.8 standard deviations of valuation between 2012 and 2020 is far more than the median change in the measure during correction phases (2.9 standard deviations). As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market which continues to this day. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in corn has lasted for just over four years and gained 235% in real terms. The weakest advance, during 190708, gained 93% in real terms. Since April 2020, the commodity has already gained 11%. As such, I expect the current cycle to gain an additional 224% in real terms by August 2024. This implies an expected annual return of 33% by the time the present bull market reaches completion.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, corn has increased its valuation within a relatively narrow
Commodities, the Decade Ahead  167 band of +3.0 standard deviations (the weakest advance increased its valuation by +2.0 and the strongest increased by +5.0 standard deviations). In other words, never in the 120year price history under examination has corn failed to increase its valuation by less than +2.0 standard deviations over its bull market. Since the April 2020 low the commodity´s relative valuation has increased by +0.2 standard deviations, implying its advance is still far weaker than the weakest bull market in over a century. Coupled with the fact that the 11% price gain since April of this year is far lower than the previous weakest bull market, there is evidence that there is still significant upside potential. The April 2020 undervaluation of 1.0 standard deviation made the commodity more undervalued than 84% of all previous months. By the time the current bull market reaches its end, I expect corn to be trading at a price which is +1.7 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to corn trading at $10.46 on August 2024, a price that is +1.7 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for corn starts in January 1860. This means that to date there have been 1,866 5year holding periods and 1,806 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of corn is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of corn over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run.
168  David J. Howden
Commodities, the Decade Ahead  169
I forecast a 7.7% annual gain in corn over the coming 5year period. The forecast range is also strictly positive, ranging from 7.7 to 7.8%. The model explains 51% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of corn will breakeven by June 2025 with an 87% probability, and that the return will exceed 10% with a 37% probability. Over the next ten years, I expect the price of corn to increase by 6.0% annually. The forecast range is clustered around this level, ranging from 4.5 to 8.2%. The model explains 68% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that corn will breakeven by June 2030 with a probability of 98%, and that there is a 10% chance that its return will exceed 10% over this period.
Conclusion
Both models use the relative valuation of corn as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Corn´s relative valuation of 0.8 standard deviations below its longterm mean is on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by no more than the average commodity. As such, corn is the 25th most undervalued commodity of the group. I forecast that the commodity will yield an annual return of 7.7% over the coming five years, and 6.0% over the coming decade. Both returns are on par with the averages for the 42 other commodities (7.6% and 5.9%). Consequently, corn ranks 25th and 22nd out of 43 commodities for the 5 and 10year return forecasts.
Corn Forecast return rankings, out of 43 commodities Relative Valuation th
25 Corn 43 Commodity Avg.
0.8 0.7
Forecast returns: 5Year th
25
7.7 7.6
Probability that return exceeds 10%:
10Year nd
22
6.0 5.9
5Year th
10Year st
24
21
37 39
10 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the
170  David J. Howden explanatory power of the forecast models I estimate that there is a 37% probability that corn can achieve this return by June 2025 and 10% by June 2030, ranking the grain 24th and 21st out of the 43 markets for both probabilities. Given this evidence, it is highly likely that corn will offer comparable performance to the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the commodity is in its current price and valuation cycle. The evidence from corn´s price and valuation cycles since 1900 points to a probable surge in the commodity´s price that will end August 2024. At a high of $10.46 by that date, the grain will have advanced from its April 2020 low in a manner consistent with the other seven advances since 1900. Over this time, corn´s relative valuation should also increase from its current undervalued position of 0.8 standard deviations, to end this bull market rally overvalued by +1.7 standard deviations.
Commodities, the Decade Ahead  171 To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying corn today and selling it at any date over the coming decade. For example, an expected price of $5.04 in June 2025 implies an annual rate of return of 7.7% over the next five years if the investor buys corn today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of corn, cycle analysis predicts a swift appreciation peaking in August 2024, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 36.9% by buying corn. This expected return falls to 7.7% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, corn ranks 9th and 24th out of the 43 commodities. This implies that corn should yield a far superior return over the coming five years than the median commodity, though over the next decade its return should be comparable to the average. Taking the average of its rankings for these expected returns, cotton ranks 22nd out of the 43 commodities.
Corn Expected return rankings, out of 43 commodities Relative Valuation Analysis of corn´s longerterm price behavior points to somewhat higher prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a sharp collapse after the current bull market completes, followed by a smaller rally taking corn back to a price above $6.00. By June 2025, I forecast corn to be trading at $5.04 per bushel, and $6.24 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 51% of the grain´s 5year returns and 68% of its 10year returns explained since June 1990. In all cases, the price of corn is not expected to fall below its April 2020 low at any time over the coming decade.
th
25 Corn 43 Commodity Median
0.8 0.8
Expected average returns: 5Year
10Year
th
24
36.9 21.2
7.7 8.1
9
th
Overall Rank nd
22
172  David J. Howden
Commodities, the Decade Ahead  173
Cotton The use of cotton can be traced to the development of civilization itself. The earliest known textile uses of cotton date to 6000 BC in Huaca Prieta, Peru. The soft, fluffy fiber has figured centrally in many world powers including the British Empire and, more recently, the United States. Alexander the Great famously changed his army´s uniforms to cotton from wool after invading India, much to the relief of the troops. The boll weevil, an insect detrimental to cotton crops, entered the United States from Mexico in 1892 and is cited as being almost as important as the Civil War in changing the economic and social fabric of the south. Cultivation of the cotton plant requires a long frostfree season with moderate rainfall. The soil does not need to be exceptionally nutrientrich, and the fiber has been grown traditionally in the dry subtropics of the Northern and Southern hemispheres. (More recently cotton production has been moved to more arid climates, aided by irrigation.) Cotton has long faced competition from the synthetic textile industry, starting with the development of rayon in France in the 1890s. Nylon and polyester caused a significant drop in demand throughout the 1960s, though natural fibers have since recovered. While the vast majority of cotton is destined for textile factories, smaller amounts are used in fishing nets, coffee filters, tents, explosives, paper, and bookbinding. Cottonseed oil is consumed as any other vegetable oil, and the cottonseed meal left over in the production process is fed to ruminant livestock.
Approximately 2.5% of the world´s arable land is devoted to cotton cultivation. Cotton growers in the United States are heavily subsidized (around $2 billion per year for
174  David J. Howden the 25,000 growers), although China offers the greatest amount of state support. With new lowcost production, mainly in Africa, becoming more prevalent, the future of these subsidies is uncertain. Global cotton output reached 24 million tons in 2018, a 7% increase over the previous decade. This increase came largely as a result of increased production yields, as production area has remained relatively constant for over thirty years. This production increase is most pronounced in United States, where output has increased by 43% (1.2 million tons) over the previous decade. Offsetting these global increases in output is a sharp dropoff in Chinese production, which has fallen by 19% since 2008 for a total of 1.4 million tons annually. Since 1999 world output has increased at an annual rate of 1.5%. Globally, there are 32 million hectares of land devoted to cotton production. This area is 4.5% more than there was a decade ago and since 1990 the area of cotton the world has harvested has remained essentially unchanged. Increasing yields have more than compensated for the stability in areas harvested and explain the large increase in global output. Globally, cotton yields 2.2 metric tons to the hectare. This yield has been relatively stable since 2006 and represents a 1.5% annual increase since 1999. Over the past 30 years yields have increased between 12% annually. India accounts for nearly 40% of the world´s land dedicated to cotton production. Low yields reduce the overall output though the country is the world´s second largest producer, after China. Production of cotton is highly concentrated with the top five producers accounting for over 70% of global output. Cotton first traded on an organized exchange with the 1870 formation of the New York Cotton Exchange. The NYCE was later acquired by the New York Board of Trade, which later became part of the Intercontinental Exchange where cotton futures are now traded primarily. The ICE cotton no. 2 (CT) cash contract returned 4.1% to the investor over the past year. Futures trade in lots of 50,000 pounds and are quoted in U.S. cents per pound.
Commodities, the Decade Ahead  175
The Bottom Line Cotton closed June 2020 at a price of $0.59 per pound. Based on historical valuations dating to March 1876 (1,732 months) I estimate the fairvalue price of the commodity to be $0.67, implying an undervaluation of 0.5 standard deviations. This indicates that it is priced more cheaply today than 70% of all previous months. Analysis of the commodity´s price cycles since 1900 points to the start of a new secular bull market. The March 2020 low of $0.47 looks to be a longterm bottom. Historically, the median bull market in cotton has lasted for 3.2 years and increased its price by 211% in real terms. Following this pattern, the current bull market phase should be completed in May 2023 after an additional 186% gain in the commodity´s inflationadjusted price.
Cotton: Forecast Summary 59 67 0.5
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Mar20 May23 186 44
5Year Forecast 5Year Annual Forecast Return, % 4.2 5Year Forecast Range, % (3.0, 6.4) 2 0.53 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
76 17
10Year Forecast 10Year Annual Forecast Return, % 3.4 10Year Forecast Range, % (1.8, 5.6) 2 0.68 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
89 1
176  David J. Howden Over the coming 5year period, I forecast the price of cotton to increase by 4.2% annually, with a forecast range between 3.0 and 6.4%. The forecast model explains 53% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that cotton´s price will breakeven by June 2025 with an 76% probability, and that there is a 17% chance that the commodity´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast cotton´s price to increase by 3.4% annually until June 2030 with a forecast range between 1.8 and 5.6%. This model explains 68% of the commodity´s 10year returns since June 1990. As such, there is an 89% probability that cotton will breakeven over the coming decade, and a 1% chance that it will yield a return greater than 10%.
Commodities, the Decade Ahead  177 2001 and holding it until today. Since inflation over that period averaged 2.0%, the investor´s returns were somewhat more muted at 2.1% per year. More recently the commodity´s price has been in a bear market since March 2011. From that month´s high of $1.96 a loss of 79% ensued until the recent March 2020 low. The recent March bottom looks to be the end of a longterm secular decline which should usher in a multiyear rally. Since 1900 the commodity has gone through eight complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the commodity´s price increase by 211% in real terms, before being corrected by a median decline of 73%. The median bull market has lasted for just over three years, and its subsequent correction has taken over six years to complete.
Historical Analysis Cotton (No. 2): Historical Cycle Summary
Since June 1990, the nominal price of cotton has decreased from $0.80 per pound to the current close of $0.59 for an annual return of 1.0%. The alltime nominal high for the commodity came in March 2011 at a price of $1.96. In real, inflationadjusted terms the commodity´s price has mostly fallen throughout its history. Cotton´s real high was in March 1918, with its subsequent alltime low forming in October 2001. As of June 2020, its price was lower than 93% of all prior monthly closing prices in real terms.
Declines
Advances
Date Start End Mar09 Aug14
Price Start End 11.5
6
51
3.2
Mar18 Mar21
33.74
12
73
3.1
Dec23 Mar32
35.92
7
76
1.4
Jan67
38
20
67
0.4
Aug73 Dec74
83
35
63
1.8
Jun76 Aug86
81
28
83
2.9
Jun95
Oct01
104
28
77
1.1
Oct03 Feb09
72
38
56
0.7
Mar11 Mar20
196
47
79
7.8
Sep46
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Aug14 Mar18
6.25
34
290
3.1
Mar21 Dec23
11.74
36
221
3.3
Mar32 Sep46
6.85
38
277
1.9
Jan67 Aug73
20
83
202
2.0
Dec74 Jun76
35
81
112
1.2
Aug86 Jun95
28
104
174
1.4
Oct01 Oct03
28
72
153
2.7
Feb09 Mar11
38
196
400
1.2
Mar20 Jun20
47
59
25
0.7
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Over longer periods, cotton´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 2% for most of the 20 th century. Nominal returns have hovered around 1% for most of the crop´s history, with real returns averaging 2.1% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 4.1% and resulted by buying cotton in October
Max. 20.3 83 7.8 8.5
Median 6.3 73 1.8 3.8
Min. 1.3 51 0.4 1.9
Max. 14.5 400 0.7 9.0
Median 3.2 211 1.9 4.0
Min. 1.5 112 3.3 2.3
May23 3.3 148 211 4.0
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the eight completed bull markets in cotton has started from an undervalued position, with a median value of 1.9 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +4.0 standard deviations. Similarly, each of the commodity´s nine completed bear markets has started from an
178  David J. Howden overvalued position, with a median value of +1.8 standard deviations above the longterm mean. Over the course of each bear market cotton continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.8 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in March 2011. From the starting price of $1.96 the commodity´s price fell by 79% in real terms. This decline is on par with the median decline of 73% over all recorded cotton bear markets. The decline´s starting relative valuation of +7.8 standard deviations was the most overvalued price in cotton´s history (the price was also the commodity´s alltime nominal high), and far above the median bear market starting relative valuation of +1.8 standard deviations. At the March 2020 low of $0.47 the commodity was 0.7 standard deviations undervalued. This made the commodity marginally less undervalued than the median start to a bull market advance (1.9 standard deviations). However, the loss of 8.5 standard deviations of valuation between 2011 and 2020 is far more than the median change in the measure during correction phases (3.8 standard deviations). As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market which continues to this day. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in cotton has lasted for over three years and gained 211% in real terms. The weakest advance, during 197476, gained 112% in real terms. Since March 2020, the commodity has already gained 25%. As such, I expect the current cycle to gain an additional 186% in real terms by May 2023. This implies an expected annual return of 44% by the time the present bull market reaches completion.
More dependable than forecasts of price movements are changes to relative valuation.
Commodities, the Decade Ahead  179 Over its bull markets to date, cotton has increased its valuation within a band of +6.7 standard deviations (the weakest advance increased its valuation by +2.3 and the strongest increased by +9.0 standard deviations). In other words, never in the 120year price history under examination has cotton failed to increase its valuation by less than +2.3 standard deviations over its bull market. Since the March 2020 low the commodity´s relative valuation has increased by +0.2 standard deviations, implying its change in valuation has is still far weaker than the weakest bull market in over a century. Coupled with the fact that the 25% price gain since this year´s low is far lower than the previous weakest bull market, there is evidence that there is still significant upside potential. The March 2020 undervaluation of 0.7 standard deviations made the commodity more undervalued than 76% of all previous months. By the time the current bull market reaches its end, I expect cotton to be trading at a price which is +3.3 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to cotton trading at $1.48 on May 2023, a price that is +3.3 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for cotton starts in March 1876. This means that to date there have been 1,672 5year holding periods and 1,612 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of cotton is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of cotton over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of cotton as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are
180  David J. Howden
Commodities, the Decade Ahead  181
tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
Conclusion I forecast a 4.2% annual gain in cotton over the coming 5year period. The forecast range is also strictly positive, ranging from 3.0 to 6.4%. The model explains 53% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of cotton will breakeven by June 2025 with a 76% probability, and that the return will exceed 10% with a 17% probability. Over the next ten years, I expect the price of cotton to increase by 3.4% annually. The forecast range is clustered around this level, ranging from 1.8 to 5.6%. The model explains 67% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that cotton will breakeven by June 2030 with a probability of 89%, and that there is a 1% chance that its return will exceed 10% over this period.
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future.
Cotton Forecast return rankings, out of 43 commodities Relative Valuation st
31 Cotton 43 Commodity Avg.
0.5 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year 10Year rd th
33
4.2 7.6
34
3.4 5.9
5Year st
10Year nd
17 39
1 22
31
32
Cotton´s relative valuation of 0.5 standard deviations below its longterm mean is a little above the average of the 43 markets analyzed herein (a slight undervaluation of 
182  David J. Howden 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by less than the average commodity. As such, cotton is the 31st most undervalued commodity of the group. I forecast that the commodity will yield an annual return of 4.2% over the coming five years, and 3.4% over the coming decade. Both returns are somewhat lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, cotton ranks 33rd and 34th out of 43 commodities for the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 17% probability that cotton can achieve this return by June 2025 and 1% by June 2030, ranking it 31st and 32nd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that cotton will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the commodity is in its current price and valuation cycle. The evidence from cotton´s price and valuation cycles since 1900 points to a probable surge in its price that will end in May 2023. At a high of $1.48 by that date, the commodity will have advanced from its March 2020 low in a manner consistent with the other eight advances since 1900. Over this time, cotton´s relative valuation should also increase from its current undervalued position of 0.5 standard deviations, to end this bull market rally overvalued by +3.3 standard deviations.
Commodities, the Decade Ahead  183 market going out to 2030. These longerterm forecasts imply a sharp collapse after the current bull market completes. By June 2025, I forecast cotton to be trading at $0.73 per pound, followed by a constant price at that level until June 2030. The forecast models for these longerterm projections are reasonably robust, with 53% of the grain´s 5year returns and 67% of its 10year returns explained since June 1990. In all cases, the price of cotton is not expected to fall below its March 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying cotton today and selling it at any date over the coming decade. For example, an expected price of $0.73 in June 2025 implies an annual rate of return of 4.2% over the next five years if the investor buys cotton today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of cotton, cycle analysis predicts a swift appreciation peaking in May 2023, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 39.1% by buying cotton. This expected return falls to 4.2% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, cotton ranks 6th and 34th out of the 43 commodities. This implies that cotton should yield a far superior return over the coming five years than the median commodity, though over the next decade its return should be somewhat lower than the average. Taking the average of its rankings for these expected returns, cotton ranks 31st out of the 43 commodities.
Cotton Expected return rankings, out of 43 commodities Relative Valuation st
31 Analysis of cotton´s longerterm price behavior points to higher though somewhat muted prices five years from now, at least relative to this forecast cycle high, and a flat
Cotton 43 Commodity Median
0.5 0.8
Expected average returns: 5Year th
10Year th
39.1 21.2
4.2 8.1
6
34
Overall Rank st
31
184  David J. Howden
Commodities, the Decade Ahead  185
Crude Oil: Brent Crude oil, or petroleum, is a yellow to black liquid found within the earth in geological formations. It is most commonly refined into various fuels. Crude oil has traditionally been recovered from the earth by means of drilling, either on land or in seabeds. Increasingly production has shifted to include hydraulic fracturing (“fracking”), which has contributed to the United States becoming the world´s largest producer as of 2018. Roughly 80% of the world´s readily accessible crude oil reserves are located in the Middle East, with nearly twothirds in Saudi Arabia, the United Arab Emirates, Iraq, Qatar, and Kuwait. Important and significant nonconventional reserves exist in the form of bitumen (e.g., the Athabasca oil sands of Canada and Venezuela´s Orinoco Belt). These unconventional sources suffer from significant logistical and technical hurdles in extraction, mostly in the form of the large amounts of heat and water necessary for oil extraction. These challenges reduce the net energy content of these sources below that of conventional oil sources. Brent crude oil refers to the crude oil deposits located between Norway and the Shetland Islands in Europe´s North Sea. Originally Brent crude referred to the sweet light crude oil first extracted from the Brent oilfield in the North Sea in 1976. Since then and in response to declining output from the Brent oilfield, oil blends from other fields have been added to the classification, including Forties (added in 2002), Oseberg (2002), Ekofisk (2007) and Troll (2018). (The Brent oilfield is no longer economically viable, and its ongoing decommissioning will be completed sometime in the early 2020s.) Consequently, the Brent crude oil quotation is now known infrequently as the BFOET quotation.
186  David J. Howden
Commodities, the Decade Ahead  187
Brent is the leading global benchmark for Atlantic basin crude oils and is used to set the price of twothirds of the world´s internationally traded crude oil supplies (the other benchmark, West Texas Intermediate, prices the other third). Historically, price differences between Brent and other crude prices have been minor and due to local demand, and more commonly, supply conditions. Recently these price divergences have grown, both in size and direction. Prior to 2009 Brent traded at a discount of around 5% to West Texas Intermediate. More recently it has traded at a premium of nearly 10% (the current premium is 5%).
Brent crude oil originally traded on the open outcry International Petroleum Exchange in London starting in 1988. Since 2005 it has been moved to the electronic Intercontinental Exchange. The ICE Brent crude oil (B) cash contract returned 35.7% to the investor over the past year. Futures trade in lots of 1,000 barrels and are quoted in U.S. dollars per barrel.
The Bottom Line
Global crude oil output reached 95 million barrels per day in 2019, a 17% increase over the previous decade. This increase came largely as a result of expanded production from the United States, where daily output increased by nearly 10 million barrels since 2009 (a 134% increase). Output growth in Russia and Saudi Arabia has also been reasonably strong, at 14% and 22%, and combined the two countries pump 3.5 million additional barrels daily than they did in 2009. The United States is the world´s largest producer, a position it has held since overtaking Saudi Arabia in 2014. Since 1999 world output has increased at an annual rate of 1.4%. There are approximately 1.7 trillion barrels of crude oil in reserves globally. Over the last decade world reserves have grown by 13%, and at an annual rate of 1.5% since 1999. Although there is some disagreement as to which countries have the highest reserves, Venezuela is widely recognized as maintaining the largest reserve at 300 billion barrels (18% of global reserves). Crude oil is widely distributed throughout the world, with the top five countries accounting for less than twothirds of global reserves.
Brent crude oil closed June 2020 at a price of $41.27 per barrel. Based on historical valuations dating to June 1861 (1,909 months) I estimate the fairvalue price of the commodity to be $91.38, implying an undervaluation of 1.5 standard deviations. This indicates that it is priced more cheaply today than 93% of all previous months. Analysis of the oil´s price cycles since 1900 points to the start of a new secular bull market. The April 2020 low of $25.27 looks to be a longterm bottom. Historically, the median bull market in Brent crude oil has lasted for nearly eight years and increased its price by 238% in real terms. Following this pattern, the current bull market phase should be completed in December 2027 after an additional 175% gain in oil´s inflationadjusted price. Over the coming 5year period, I forecast the price of Brent crude oil to increase by 18.4% annually, with a forecast range between 16.7 and 21.8%. The forecast model explains 48% of the variation in the oil´s 5year returns since June 1990. Consequently, I forecast that Brent crude oil´s price will breakeven by June 2025 with a 98% probability, and that there is an 82% chance that the oil´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast Brent crude oil´s price to increase by 11.9% annually until June 2030 with a forecast range between 10.7 and 13.4%. This model explains 71% of the oil´s 10year returns since June 1990. As such, there is a 99% probability that Brent crude oil will breakeven over the coming decade, and a 67% chance that it will yield a return greater than 10%.
188  David J. Howden
Commodities, the Decade Ahead  189 around 3% for most of the oil´s history, with real returns averaging 0.4% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 6.8% and resulted by buying Brent crude oil in November 1998 and holding it until today. Since inflation over that period averaged 2.1%, the investor would have earned a real return of 4.7% per year. More recently the oil´s price has been in a bear market since April 2011. From that month´s high of $125 a collapse of 82% ensued. The April 2020 bottom of $25.27 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Brent Crude Oil: Forecast Summary 41 91 1.5
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr20 Dec27 175 14
5Year Forecast 5Year Annual Forecast Return, % 18.4 5Year Forecast Range, % (16.7, 21.8) 2 0.48 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
98 82
10Year Forecast 10Year Annual Forecast Return, % 11.9 10Year Forecast Range, % (10.7, 13.4) 0.71 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 67
Historical Analysis Since June 1990, the nominal price of Brent crude oil has increased from $16 per barrel to the current close of $41 for an annual return of 3.2%. The alltime nominal high for the oil came in June 2008 at a price of $140.42. In real, inflationadjusted terms the oil´s price has mostly declined throughout its history with the exception of the bull markets of the late 1970s and mid2000s. Brent crude oil´s real high was in June 2008, with its low forming a decade earlier, in November 1998. As of June 2020, oil´s price was lower than 71% of all prior monthly closing prices in real terms. Over longer periods, Brent crude oil´s price has failed to keep pace with general price inflation, resulting in a real yield of around zero to 0.5%. Nominal returns have hovered
Since 1900 oil has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen Brent crude oil´s price increase by 238% in real terms, before being corrected by a median decline of 71%. The median bull market has lasted for nearly eight years, and its subsequent correction has taken just over six years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in Brent crude oil has started from an undervalued position, with a median value of 2.0 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.8 standard deviations. Similarly, each of the oil´s eight completed bear markets that relative valuation data is available for has started from an overvalued position, with a median value of +0.5 standard deviations above the longterm mean (with the exception of the 199098 bear market which started from an approximately fairlyvalued position). Over the course of each bear market Brent crude oil continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.7 standard deviations.
190  David J. Howden
Commodities, the Decade Ahead  191
Brent Crude Oil: Historical Cycle Summary Declines Date Start End Dec20 Aug21
Price Start End
Advances Real Start Rel. Change, % Val, σ
8
3
60
0.1
5
2
62
0.6
Jan40 Mar46
4
2
68
0.3
Feb57
Jul73
4
5
27
0.2
Jun80
Jul86
46
9
85
1.8
Sep90 Nov98
41
10
80
0.2
Jun08 Dec08
140
35
74
5.5
Apr11 Apr20
125
25
82
2.7
Date Start End
Jul31
Real Start Rel. Change, % Val, σ
3
5
91
2.2
Jan40
2
4
115
2.5
Mar46 Feb57
2
4
73
2.0
Aug21 Apr29 Apr29
Price Start End
Jul31
Jul73
Jun80
5
46
427
1.3
Jul86
Sep90
9
41
263
2.8
Nov98 Jun08
10
140
952
1.1
Dec08 Apr11
35
125
238
0.0
Apr20 Jun20
25
41
63
1.9
Over its bull markets to date, Brent crude oil has increased its valuation within a relatively narrow band of +4.4 standard deviations (the weakest advance increased its valuation by +2.2 and the strongest increased by +6.6 standard deviations). In other words, never in the 120year price history under examination has Brent crude oil failed to increase its valuation by less than +2.2 standard deviations over its bull market. Since the April 2020 low the oil´s relative valuation has increased by +0.4 standard deviations, implying further upside potential.
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 16.4 85 5.5 5.5
Median 6.1 71 0.5 2.7
Min. 0.5 27 0.2 0.9
Max. 10.9 952 0.0 6.6
Median 7.7 238 2.0 2.8
Min. 2.3 73 2.8 2.2
Dec27 0.9 85 238 2.8
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in April 2011. From the starting price of $125, Brent crude oil´s price fell by 82% in real terms. This decline is a little more extreme than the median decline of 71% over all recorded Brent crude oil bear markets. The decline´s starting relative valuation of +2.7 standard deviations was far more extreme than the starting relative valuation to the median bear market (+0.5). The change in relative valuation over the course of the bear market was also extreme at 4.6 standard deviations against a median value of –2.7. The duration also ran somewhat long, taking nine instead of the median value of six years to complete. At the recent April 2020 low of $25 oil was 1.9 standard deviations undervalued, on par with the median starting valuation to a bull market advance. As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in Brent crude oil has lasted for nearly eight years and gained 238% in real terms. The weakest advance, during 194657, gained 73% in real terms. Since April 2020, oil has already gained 63%. As such, I expect the current cycle to gain an additional 175% in real terms by December 2027. This implies an expected annual return of 14% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation.
The April 2020 undervaluation of 1.9 standard deviations made the commodity more undervalued than 97% of all previous months. By the time the current bull market reaches its end, I expect Brent crude oil to be trading at a price which is +0.9 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to Brent crude oil trading at $85 by December 2027, a price that is +0.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is
192  David J. Howden in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for Brent crude oil starts in June 1861. This means that to date there have been 1,849 5year holding periods and 1,789 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of Brent crude oil is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of Brent crude oil over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of Brent crude oil as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
Commodities, the Decade Ahead  193 explanatory power of the model, I estimate that the price of Brent crude oil will breakeven by June 2025 with a 98% probability, and that the return will exceed 10% with an 82% probability.
Over the next ten years, I expect the price of Brent crude oil to increase by 11.9% annually. The forecast range is clustered around this level, ranging from 10.7 to 13.4%. The model explains 71% of the variance in the oil´s 240 10year returns since June 1990. As such, I estimate that Brent crude oil will breakeven by June 2030 with a probability of 99%, and that there is a 67% chance that its return will exceed 10% over this period.
Conclusion
I forecast an 18.4% annual gain in Brent crude oil over the coming 5year period. The forecast range is also strictly positive, ranging from 16.7 to 21.8%. The model explains 48% of the variation of the 300 5year returns of the oil since June 1990. Given this
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Brent crude oil´s relative valuation of 1.5 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, Brent crude oil is the 9th most undervalued commodity of the group. I forecast that Brent crude oil will yield an annual return of 18.4% over the coming five years, and 11.9% over the coming decade. Both returns are double the averages for
194  David J. Howden
Commodities, the Decade Ahead  195
the 42 other commodities (7.6% and 5.9%). Consequently, Brent crude oil ranks 1st and 4th out of 43 commodities for both the 5 and 10year return forecasts.
Brent Crude Oil Forecast return rankings, out of 43 commodities Relative Valuation th
Brent Crude Oil 43 Commodity Avg.
Forecast returns: 5Year st
Probability that return exceeds 10%:
10Year th
9
1
4
1.5 0.7
18.4 7.6
11.9 5.9
5Year rd
3
82 39
10Year th
4
67 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is an 82% probability that Brent crude oil can achieve this return by June 2025 and 67% by June 2030, ranking the oil 3rd and 4th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that Brent crude oil will outperform the average commodity over both the coming 5 and 10year periods.
in December 2027. At a high of $85 by that date, oil will have advanced from its April 2020 low in a manner consistent with the other eight advances since 1900. Over this time, Brent crude oil´s relative valuation should also increase from its current undervalued position of 1.5 standard deviations, to end this bull market rally overvalued by +0.9 standard deviations. Analysis of the oil´s longerterm price behavior points to substantially higher prices over the next five and tenyear periods which will confirm further the forecast cycle highs. By June 2025, I forecast Brent crude oil to be trading at $96 per gallon, and $127 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 48% of the metal´s 5year returns and 71% of its 10year returns explained since June 1990. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying Brent crude oil today and selling it at any date over the coming decade. For example, an expected price of $96 in June 2025 implies an annual rate of return of 18.4% over the next five years if the investor buys Brent crude oil today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
Crude Oil (Brent) Expected return rankings, out of 43 commodities Relative Valuation th
9 Brent Crude Oil 43 Commodity Median
To put the full analysis in context, the evidence from Brent crude oil´s price and valuation cycles since 1900 points to a continued advance in the oil´s price that will end
1.5 0.8
Expected average returns: 5Year st
10Year st
22.5 21.2
18.2 8.1
21
1
Overall Rank th
6
In the case of Brent crude oil, cycle analysis predicts a continued appreciation peaking in December 2027, and the period valuation models also forecast price increases. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 22.5% by buying Brent crude oil. This
196  David J. Howden expected return falls to 18.2% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, Brent crude oil ranks 21st and 1st out of the 43 commodities. This implies that Brent crude oil should yield comparable returns relative to the average commodity over the next five years, and far superior returns over the next decade. Taking the average of its rankings for these expected returns, Brent crude oil ranks 6th out of the 43 commodities.
Commodities, the Decade Ahead  197
Crude Oil: West Texas Intermediate Crude oil, or petroleum, is a yellow to black liquid found within the earth in geological formations. It is most commonly refined into various fuels. Traditionally crude oil has been recovered from the earth by means of drilling, either on land or in seabeds. Increasingly production has shifted to include hydraulic fracturing (“fracking”), which has contributed to the United States becoming the world´s largest producer as of 2018. Roughly 80% of the world´s readily accessible crude oil reserves are located in the Middle East, with nearly twothirds in Saudi Arabia, the United Arab Emirates, Iraq, Qatar, and Kuwait. Important and significant nonconventional reserves exist in the form of bitumen (e.g., the Athabasca oil sands of Canada and Venezuela´s Orinoco Belt). These unconventional sources suffer from significant logistical and technical hurdles in extraction, mostly in the form of the large amounts of heat and water necessary for oil to be extracted. These challenges reduce the net energy content of these sources below that of conventional oil sources. West Texas Intermediate oil, also known as “Texas light sweet” is a common benchmark in crude oil pricing. WTI is light crude oil of a relatively low density, and its sweetness refers to its low sulfur content, both desirable properties that facilitate efficient refining. WTI is superior to other important benchmark oil prices in these two respects: it is somewhat lighter and sweeter than Brent crude oil, and considerably lighter and sweeter than Dubai or Oman crude oils. Unlike these other oil benchmarks, WTI does not refer (any longer) to oil from a particular location but rather a specific grade (between 27 and 42degrees API gravity and under 0.42% sulfur content). That said, the price is set for crude oil on delivery in Cushing, Oklahoma. The town of less than 8,000 residents was the site of the most important oil field of the early 20th century. Although relatively unimportant in terms of current output, it is a vital transshipment point with many intersecting pipelines and storage facilities, linking suppliers with refiners. West Texas Intermediate is used to set the price of onethird of the
198  David J. Howden world´s internationally traded crude oil supplies (the other benchmark, Brent, prices the other two thirds). Global crude oil output reached 95 million barrels per day in 2019, a 17% increase over the previous decade. This increase came largely as a result of expanded production from the United States, where daily output increased by nearly 10 million barrels since 2009 (a 134% increase). Output growth in Russia and Saudi Arabia was also reasonably strong, at 14% and 22%, and combined the two countries pump 3.5 million additional barrels daily than they did in 2009. The United States is the world´s largest producer, a position it has held since overtaking Saudi Arabia in 2014. Since 1999 world output has increased at an annual rate of 1.4%. There are approximately 1.7 trillion barrels of crude oil in reserves globally. Over the last decade world reserves have grown by 13%, and at an annual rate of 1.5% since 1999. Although there is some disagreement as to which countries have the highest reserves, Venezuela is widely recognized as maintaining the largest reserve at 300 billion barrels (18% of global reserves). Crude oil is widely distributed throughout the world, with the top five countries accounting for less than twothirds of global reserves. The New York Mercantile Exchange launched WTI crude oil contracts on 30 March 1983 and they are now the exchange´s most liquid nonfinancial future. The NYMEX WTI crude oil (CL) cash contract returned 32.8% to the investor over the past year. Futures trade in lots of 1,000 barrels and are quoted in U.S. dollars per barrel.
The Bottom Line WTI crude oil closed June 2020 at a price of $39.28 per barrel. Based on historical valuations dating to June 1861 (1,909 months) I estimate the fairvalue price of the commodity to be $83.70, implying an undervaluation of 1.5 standard deviations. This indicates that it is priced more cheaply today than 94% of all previous months.
Commodities, the Decade Ahead  199 Analysis of the oil´s price cycles since 1900 points to the start of a new secular bull market. The April 2020 low of $18.84 looks to be a longterm bottom. Historically, the median bull market in WTI crude oil has lasted for almost eight years and increased its price by 157% in real terms. Following this pattern, the current bull market phase should be completed in December 2027 after an additional 48% gain in the oil´s inflationadjusted price.
West Texas Intermediary: Forecast Summary 39.28 83.70 1.5
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Apr20 Dec27 48 6
5Year Forecast 5Year Annual Forecast Return, % 17.1 5Year Forecast Range, % (15.8, 20.1) 2 0.44 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
97 79
10Year Forecast 10Year Annual Forecast Return, % 12.2 10Year Forecast Range, % (10.5, 14.3) 2 0.75 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 71
Over the coming 5year period, I forecast the price of WTI to increase by 17.1% annually, with a forecast range between 15.8 and 20.1%. The forecast model explains 44% of the variation in the oil´s 5year returns since June 1990. Consequently, I forecast that WTI´s price will breakeven by June 2025 with a 97% probability, and that there is an 79% chance that the oil´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast WTI ´s price to increase by 12.2% annually until June 2030 with a forecast range between 10.2
200  David J. Howden and 14.3%. This model explains 75% of the oil´s 10year returns since June 1990. As such, there is a 99% probability that WTI crude oil will breakeven over the coming decade, and a 71% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of WTI crude oil has increased from $17.05 per barrel to the current close of $39.28 for an annual return of 2.8%. The alltime nominal high for the oil came in June 2008 at a price of $140.00. In real, inflationadjusted terms the oil´s price has been flat for most of its history except for the 19702008 period when it was rose precipitously. WTI crude oil´s real high was in June 2008, with its low forming much earlier, in May 1969. As of June 2020, the oil´s price was lower than 62% of all prior monthly closing prices in real terms. Over longer periods, WTI crude oil´s price has just kept pace with general price inflation, resulting in a real yield of around zero to 0.5%. Nominal returns have hovered around 3% for most of the oil´s history, with real returns averaging 0.3% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 5.9% and resulted by buying WTI crude oil in November 1998 and holding it until today. Since inflation over that period averaged 3.8%, the investor would have earned a real return of 2.1% per year.
Commodities, the Decade Ahead  201 bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen WTI crude oil´s price increase by 157% in real terms, before being corrected by a median decline of 68%. The median bull market has lasted for almost eight years, and its subsequent correction has taken just over six years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the eight completed bull markets in WTI crude oil has started from an undervalued position, with a median value of 2.0 standard deviations below the longterm mean. (The only exceptions to this is the 200911 advance that started from an approximately fairlyvalued position.) From these undervalued starting positions, the median bull market increased its relative valuation by +2.8 standard deviations. West Texas Intermediate: Historical Cycle Summary Declines Date Start End Dec20 Aug21
Price Start End
Advances Real Start Rel. Change, % Val, σ
6
2
59
0.1
4
1
62
0.6
Jan40 Mar46
3
1
68
0.3
Feb57
3
4
27
0.7
Mar80 Mar86
40
10
81
3.4
Sep90 Nov98
40
11
77
0.1
Jun08
Jan09
140
42
69
5.3
Apr11 Apr20
114
19
85
2.4
Date Start End
Jul31
4
91
2.2
Jan40
1
3
116
2.5
Mar46 Feb57
1
3
71
2.0
Mar80
4
40
520
1.4
Mar86 Sep90
10
40
211
1.9
Nov98 Jun08
11
140
819
1.2
Jan09
Apr11
42
114
157
0.2
Apr20 Jun20
19
39
109
2.2
Jul31
Jul73
Real Start Rel. Change, % Val, σ
2
Aug21 Apr29 Apr29
Price Start End
Jul73
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
More recently the oil´s price has been in a bear market since April 2011. From that month´s high of $114 a collapse of 85% ensued. The April 2020 bottom of $19 looks to be the end of a longterm secular decline which should usher in a multiyear rally. Since 1947 oil has gone through eight complete price cycles. Each cycle starts with a
Max. 16.4 85 5.3 5.3
Median 6.1 68 0.7 2.7
Min. 0.6 27 0.1 1.1
Max. 10.9 819 0.2 6.5
Median 7.7 157 2.0 2.8
Min. 2.2 71 2.5 1.8
Dec27 0.6 48 157 2.8
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
Similarly, each of oil´s eight completed bear markets has started from an overvalued position, with a median value of +0.7 standard deviations above the longterm mean (with the exception of the 199098 bear market which started from an approximately fairlyvalued position). Over the course of each bear market WTI crude oil continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.7 standard deviations. The most recently completed phase of its cycles was the bear market decline which
202  David J. Howden started in April 2011. From the starting price of $114, WTI crude oil´s price fell by 85% in real terms. This decline is a more extreme than the median decline of 65% over all recorded WTI bear markets. The decline´s starting relative valuation of +2.4 standard deviations is also far higher than the starting relative valuation to the median bear market (+0.7). The change in relative valuation over the course of the bear market was also quite extreme at 4.6 standard deviations against a median value of –1.9. The decline´s duration ran a little long than most (nine years against a median decline of six years). At the recent April 2020 low of $19 the oil was 2.2 standard deviations undervalued, about on par with the median starting valuation to a bull market advance. As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market.
If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in WTI crude oil has lasted for over nearly eight years and gained 157% in real terms. The weakest advance, during 194657, gained 71% in real terms. Since April 2020, oil has already gained 109%. As such, I expect the current cycle to gain an additional 48% in real terms by December 2027. This implies an expected annual return of 6% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, WTI crude oil has increased its valuation within a relatively narrow band of +4.7 standard deviations (the weakest advance increased its valuation by +1.8 and the strongest increased by +6.5 standard deviations). In other words, never in the 120year price history under examination has WTI crude oil failed to increase its valuation by less than +1.8 standard deviations over its bull market. Since the April 2020 low the oil´s relative valuation has increased by +0.7 standard deviations, implying further upside potential.
Commodities, the Decade Ahead  203 The April 2020 undervaluation of 2.2 standard deviations made the commodity more undervalued than 99% of all previous months. By the time the current bull market reaches its end, I expect WTI crude oil to be trading at a price which is +0.6 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to WTI crude oil trading at $48 by December 2027, a price that is +0.6 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for WTI crude oil starts in June 1861. This means that to date there have been 1,849 5year holding periods and 1,789 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts.
204  David J. Howden As we have seen, the future return of WTI crude oil is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of WTI crude oil over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of WTI crude oil as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 17.1% annual gain in WTI crude oil over the coming 5year period. The forecast range is also strictly positive, ranging from 15.8 to 20.1%. The model explains 44% of the variation of the 300 5year returns of the oil since June 1990. Given this explanatory power of the model, I estimate that the price of WTI crude oil will breakeven by June 2025 with a 98% probability, and that the return will exceed 10% with an 79% probability.
Commodities, the Decade Ahead  205
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. WTI crude oil´s relative valuation of 1.5 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, WTI is the 6th most undervalued commodity of the group. I forecast that WTI crude oil will yield an annual return of 17.1% over the coming five years, and 12.2% over the coming decade. Both returns are double the averages for the 42 other commodities (7.6% and 5.9%). Consequently, WTI crude oil ranks 4th and 2nd out of 43 commodities for the 5 and 10year return forecasts.
Crude Oil (West Texas Intermediate) Forecast return rankings, out of 43 commodities Relative Valuation
Crude Oil (WTI) 43 Commodity Avg.
Over the next ten years, I expect the price of WTI crude oil to increase by 12.2% annually. The forecast range is clustered around this level, ranging from 10.5 to 14.3%. The model explains 75% of the variance in the oil´s 240 10year returns since June 1990. As such, I estimate that WTI crude oil will breakeven by June 2030 with a probability of 99%, and that there is a 71% chance that its return will exceed 10% over this period.
Forecast returns:
Probability that return exceeds 10%:
5Year
10Year
5Year
10Year
6th
4th
2nd
4th
3rd
1.5 0.7
17.1 7.6
12.2 5.9
79 39
71 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is an 79% probability that WTI crude oil can achieve this return by June 2025 and 71% by June 2030, ranking the oil 4th and 3rd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that WTI crude oil will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context, the evidence from WTI crude oil´s price and valuation cycles since 1900 points to a continued increase in the oil´s price that will end in December 2027. At a high of $48 by that date, oil will have advanced from its April 2020 low in a manner consistent with the other seven advances since 1900. Over this time, WTI crude oil´s relative valuation should also increase from its current undervalued position of 1.5 standard deviations, to end this bull market rally overvalued by +0.6 standard deviations. Analysis of the oil´s longerterm price behavior points to substantially higher prices over the next five and tenyear periods which will augment further the forecast cycle
206  David J. Howden highs. By June 2025, I forecast WTI crude oil to be trading at $86 per barrel, and $123 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 44% of the metal´s 5year returns and 75% of its 10year returns explained since June 1990.
Commodities, the Decade Ahead  207 expect a median annual return of 20.7% by buying WTI crude oil. This expected return falls to 16.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, WTI crude oil ranks 23rd and 4th out of the 43 commodities. This implies that oil should yield comparable returns relative to the average commodity over the coming five years, and far greater returns over the next decade. Taking the average of its rankings for these expected returns, WTI crude oil ranks 3rd out of the 43 commodities.
Crude Oil (West Texas Intermediate) Expected return rankings, out of 43 commodities Relative Valuation rd
23 Crude Oil (WTI) 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying WTI crude oil today and selling it at any date over the coming decade. For example, an expected price of $86 in June 2025 implies an annual rate of return of 17.1% over the next five years if the investor buys WTI crude oil today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of WTI crude oil, cycle analysis predicts a slow appreciation peaking in October 2022, and the period valuation models also forecast price increases, but over both shorter and longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can
1.5 0.8
Expected average returns: 5Year rd
23
20.7 21.2
10Year th
4
16.8 8.1
Overall Rank rd
3
208  David J. Howden
Commodities, the Decade Ahead  209
Ethanol Ethanol fuel (or biofuel) is a type of ethyl alcohol derived from the fermentation of crops, typically corn (as is common in the United States), sugar cane (prevalent in Brazil) or, less commonly, sweet sorghum (in Asia and Africa). Sugar cane has a higher sucrose content than does corn, making it a more efficient and easier to produce ethanol base.
Ethanol contains about twothirds the energy content of conventional gasoline and is typically mixed with it resulting in either E10 (10% ethanol content, sometimes known as gasohol) or E85 (85% ethanol content). Despite its reduced energy content, ethanol produces fewer harmful ozoneforming pollutants. In addition to its fuel uses, it also has minor roles as an antiseptic, disinfectant, chemical solvent, and animal food additive. Global ethanol output reached 1.8 million barrels of oil equivalent per day in 2019, an 80% increase over the previous decade. This increase was a global phenomenon,
210  David J. Howden with the three largest biofuel producers (the United States, Brazil, and the European Union) all increasing output by 5561% over the previous decade. The rest of the world has steadily built capacity and now accounts for nearly 500 thousand barrels of oil equivalent daily, up from almost nothing 20 years ago. The United States remains the world´s largest biofuel producer, a position it has held since overtaking Brazil in 2006. Since 1999 world output has increased at an annual rate of 25.1% and shows no sign of slowing down in the near future. Ethanol trades primarily on the New York Mercantile Exchange. The NYMEX ethanol (EH) cash contract returned 19.7% to the investor over the past year. Futures trade in lots of 29,000 gallons and are quoted in U.S. dollars per gallon.
The Bottom Line Ethanol closed June 2020 at a price of $1.22 per gallon. Based on historical valuations dating to December 1973 (559 months) I estimate the fairvalue price of the commodity to be $1.95, implying an undervaluation of 1.5 standard deviations. This indicates that it is priced more cheaply today than 93% of all previous months. Analysis of the fuel´s price cycles since 1973 points to the start of a new secular bull market. The April 2020 low of $0.80 looks to be a longterm bottom. Historically, the median bull market in ethanol has lasted for just under two years and increased its price by 81% in real terms. Following this pattern, the current bull market phase should be completed in December 2021 after an additional 24% gain in the fuel´s inflationadjusted price. Over the coming 5year period, I forecast the price of ethanol to increase by 6.2% annually, with a forecast range between 2.7 and 7.7%. The forecast model explains 42% of the variation in the fuel´s 5year returns since June 1990. Consequently, I forecast that ethanol´s price will breakeven by June 2025 with an 87% probability, and that there is a 24% chance that the fuel´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast ethanol´s price to increase by 4.2% annually until June 2030 with a forecast range between 2.6 and 5.0%. This model explains 53% of the fuel´s 10year returns since June 1990. As such, there is a 92% probability that ethanol will breakeven over the coming decade, and a 3% chance that it will yield a return greater than 10%.
Commodities, the Decade Ahead  211
Ethanol: Forecast Summary 1.22 1.95 1.5
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr20 Dec21 24 16
5Year Forecast 5Year Annual Forecast Return, % 6.2 5Year Forecast Range, % (2.7, 7.7) 2 0.42 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
87 24
10Year Forecast 10Year Annual Forecast Return, % 4.2 10Year Forecast Range, % (2.6, 5.0) 2 0.53 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
92 3
Historical Analysis Since June 1990, the nominal price of ethanol has increased from $0.86 per gallon to the current close of $1.22 for an annual return of 1.2%. The alltime nominal high for the fuel came in June 2006 at a price of $3.82. In real, inflationadjusted terms the fuel´s price has steadily declined throughout its history. Ethanol´s real high was in June 2006, with its low forming in April 2020. As of June 2020, the fuel´s price was lower than 95% of all prior monthly closing prices in real terms. Over longer periods, ethanol´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 2% for most of the 20th century. Nominal returns have hovered around zero for most of the fuel´s history, with real
212  David J. Howden returns averaging 2.1% annually between 1973 and 2010. The highest longterm nominal return the investor could have earned was 3.6% and resulted by buying ethanol in December 1973 and holding it until today. Since inflation over that period averaged 3.8%, the investor earned a real loss of 0.2% per year. More recently the fuel´s price has been in a bear market since November 2014. From that month´s high of $2.41 a collapse of 70% ensued. The April 2020 bottom of $0.80 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  213 Ethanol: Historical Cycle Summary Declines
Advances
Date Start End
Price Start End
Jul80
Mar88
0.76
0.67
46
n.a.
Jan01
Jan02
1.78
0.97
47
3.4
Oct04 Apr05
2.02
1.19
43
0.8
Jun06 Sep07
3.81
1.52
61
7.7
Jun08 Mar10
2.79
1.44
47
2.8
Mar14 Sep14
3.15
1.50
56
2.2
Nov14 Apr20
2.41
0.80
70
0.3
Real Start Rel. Change, % Val, σ
Date Start End Nov78 Jul80
Price Start End 0.52
0.76
33
n.a.
Mar88 Jan01
0.67
1.78
81
n.a.
Jan02
Oct04
0.97
2.02
96
1.5
Apr05 Jun06
1.19
3.81
211
1.0
Sep07
Jun08
1.52
2.79
74
0.2
Mar10 Mar14
1.44
3.15
110
0.9
Sep14 Nov14
1.50
2.41
62
2.1
Apr20 Jun20
0.80
1.22
57
2.3
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1973 the fuel has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the fuel´s price increase by 81% in real terms, before being corrected by a median decline of 47%. The median bull market has lasted for just under two years, and its subsequent correction has taken a little over one year to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the five completed bull markets in ethanol that the commodity´s relative valuation is available for has started from an undervalued position, with a median value of 1.3 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.0 standard deviations. Similarly, each of the fuel´s six completed bear markets that relative valuation data is available for has started from an overvalued position, with a median value of +2.5 standard deviations above the longterm mean. Over the course of each bear market ethanol continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.0 standard deviations.
Max. 7.7 70 7.7 7.9
Median 1.3 47 2.5 4.0
Min. 0.5 43 0.3 1.8
Max. 12.8 211 0.2 8.7
Median 1.7 81 1.3 3.0
Min. 0.2 33 2.3 2.3
Dec21 0.7 1.45 81 3.0
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in November 2014. From the starting price of $2.41 the fuel´s price fell by 70% in real terms. This decline is far greater than the median decline of 47% over all recorded ethanol bear markets. The decline´s starting relative valuation of +0.3 standard deviations is unusual since it is far lower than the starting relative valuation to the median bear market (+2.5). The change in relative valuation over the course of the bear market was also weak at 2.6 standard deviations against a median value of 4.0. The timing was duration of the decline was much longer than expected, lasting nearly fiveandahalf years against 16 months for the median decline. At the recent April 2020 low of $0.80 the fuel was 2.3 standard deviations undervalued, more undervalued than the median starting valuation to a bull market advance. As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in ethanol has lasted for nearly two years and gained 81% in real terms. The weakest advance, during 197880, gained 33% in real terms. Since April 2020, the fuel has already gained 57%, placing it well on its way to completing its advance. As such, I expect the current cycle to gain an additional 24% in real terms by December 2021. This implies an expected annual return of 16% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation.
214  David J. Howden Over its bull markets to date, ethanol has increased its valuation within a band of +6.4 standard deviations (the weakest advance increased its valuation by +2.3 and the strongest increased by +8.7 standard deviations). In other words, never in the nearly 50year price history under examination has ethanol failed to increase its valuation by less than +2.3 standard deviations over its bull market. Since the April 2020 low the fuel´s relative valuation has increased by +0.8 standard deviations, implying further upside potential.
Commodities, the Decade Ahead  215 in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for ethanol starts in December 1973. This means that to date there have been 499 5year holding periods and 439 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of ethanol is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of ethanol over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of ethanol as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
The April 2020 undervaluation of 2.3 standard deviations made the commodity more undervalued than all previous months. By the time the current bull market reaches its end, I expect ethanol to be trading at a price which is +0.7 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to ethanol trading at $1.45 by December 2021, a price that is +0.7 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is
I forecast a 6.2% annual gain in ethanol over the coming 5year period. The forecast range is also strictly positive, ranging from 2.7 and 7.7%. The model explains 42% of the variation of the 300 5year returns of the fuel since June 1990. Given this explanatory
216  David J. Howden power of the model, I estimate that the price of ethanol will breakeven by June 2025 with an 87% probability, and that the return will exceed 10% with a 24% probability.
Commodities, the Decade Ahead  217 30th out of 43 commodities for the 5 and 10year return forecasts.
Ethanol Forecast return rankings, out of 43 commodities Relative Valuation th
7 Ethanol 43 Commodity Avg.
1.5 0.7
Forecast returns: 5Year th
29
6.2 7.6
Probability that return exceeds 10%:
10Year th
30
4.2 5.9
5Year th
10Year th
29
30
24 39
3 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 24% probability that ethanol can achieve this return by June 2025 and 3% by June 2030, ranking the fuel 29th and 30th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that ethanol will underperform the average commodity over both the coming 5and 10year periods.
Over the next ten years, I expect the price of ethanol to increase by 4.2% annually. The forecast range is clustered around this level, ranging from 2.6 to 5.0%. The model explains 53% of the variance in the fuel´s 240 10year returns since June 1990. As such, I estimate that ethanol will breakeven by June 2030 with a probability of 92%, and that there is a 3% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Ethanol´s relative valuation of 1.5 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, ethanol is the 7th most undervalued commodity of the group. I forecast that ethanol will yield an annual return of 6.2% over the coming five years, and 4.2% over the coming decade. Both returns are somewhat lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, ethanol ranks 29th and
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the fuel is in its current price and valuation cycle. The evidence from ethanol´s price and valuation cycles
218  David J. Howden
Commodities, the Decade Ahead  219
since 1973 points to a probable increase in the fuel´s price that will end in December 2021. At a high of $1.45 by that date, ethanol will have advanced from its April 2020 low in a manner consistent with the other seven advances since 1930. Over this time, ethanol´s relative valuation should also increase from its current undervalued position of 1.5 standard deviations, to end this bull market rally overvalued by +0.7 standard deviations. Analysis of ethanol´s longerterm price behavior points to somewhat higher prices over the next five and ten years. By June 2025, I forecast ethanol to be trading at $1.65 per gallon, and $1.83 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 42% of the fuel´s 5year returns and 53% of its 10year returns explained since June 1990. In all cases, the price of ethanol is not expected to fall below its April 2020 low at any time over the coming decade.
Ethanol Expected return rankings, out of 43 commodities Relative Valuation th
7 Ethanol 43 Commodity Median
1.5 0.8
Expected average returns: 5Year
10Year
st
28
8.7 21.2
6.1 8.1
31
th
Overall Rank th
28
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying ethanol today and selling it at any date over the coming decade. For example, an expected price of $1.65 in June 2025 implies an annual rate of return of 6.2% over the next five years if the investor buys ethanol today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of ethanol, cycle analysis predicts an appreciation peaking in December 2021, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June
2025 the investor can expect a median annual return of 8.7% by buying ethanol. This expected return falls to 6.1% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, ethanol ranks 31st and 28th out of the 43 commodities. This implies that ethanol should yield a return inferior to the average commodity over both the coming five and ten years. Taking the average of its rankings for these expected returns, ethanol ranks 28th out of the 43 commodities.
220  David J. Howden
Commodities, the Decade Ahead  221
Feeder Cattle Cattle are the most common type of large domesticated animals. They are commonly raised as livestock for meat, hides, and, less commonly, dung. “Feeder” cattle refer to those that have reached the necessary weight for slaughter (approximately 1,250 pounds or 550 kilograms). The United States accounts for onefifth of global beef production and, along with Brazil and the European Union, produces nearly half of global output. Beef consumption is traditionally a habit of the developed world, though in recent years China has increased demand and is now the world´s second largest consumer.
Beef Production
Consumption
(% World)
United States Brazil European Union China India Rest of World
20 15 13 11 7 34
(% World)
United States China Brazil European Union Argentina Rest of World
21 14 13 13 4 35
Source: USDA, 2020
Global beef production reached 67 million tons in 2019, a 13% increase over the previous decade. This increase came largely as a result of expanded production from the developing world as increased demand has spurred on production. The United States increased production by 10% since 2009 for an additional 0.9 million tons of beef annually. The next two largest producers, Brazil and the European Union, saw very little change in their output levels. The rest of the world, in contrast, produced over 4 million tons of additional beef in 2018 compared to the decade prior, explaining the majority of the production increase. The United States remains the world´s top beef producer, a position it has held every year since records begin in 1961 (except for 1991 when the European Union eked it out). Since 1999 world output has increased at an annual rate of
222  David J. Howden
Commodities, the Decade Ahead  223 1.4%, and his increase in output has held fairly constant since the mid1990s. Globally, there are 302 million head of beef cattle. This number is approximately the same as there was a decade ago and, since 1999, the number of beef cattle has grown by only 0.6% annually. The growth rate of global beef herds has trended around 0.5% annually since the mid1990s. Increasing yields since the mid1990s have added to these relative stable beef herds and contributed to total supply growth. Globally, beef cattle yield an average 223 kg of meat per animal. Yields are not appreciably higher than they were a decade ago, and since 1999 they have increased by only 0.5% annually. Since 2008 there has been a turnaround in beef productivity with yields increasing at a faster rate. While productivity growth slowed for most of the 1990s and early 2000s, since 2008 it has increased by over 0.3 percentage points, from 0.2 to 0.5% annually. The Chicago Mercantile Exchange launched feeder cattle contracts in 1964 as its first nonstorable contract. The CME feeder cattle (62) cash contract returned 16.2% to the investor over the past year. Futures trade in lots of 50,000 pounds and are quoted in U.S. cents per pound.
Historically, the median bull market in feeder cattle has lasted for 6.2 years and increased its price by 116% in real terms. Following this pattern, the current bull market phase should be completed in June 2026 after an additional 105% gain in the commodity´s inflationadjusted price.
Feeder Cattle: Forecast Summary 129 150 0.8
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Apr20 Jun26 105 13
5Year Forecast 5Year Annual Forecast Return, % 6.4 5Year Forecast Range, % (4.8, 8.4) 2 0.77 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
98 12
10Year Forecast 10Year Annual Forecast Return, % 3.5 10Year Forecast Range, % (2.8, 5.2) 0.40 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
98 0
The Bottom Line Feeder cattle closed June 2020 at a price of $1.29 per pound. Based on historical valuations dating to January 1858 (1,950 months) I estimate the fairvalue price of the commodity to be $1.50, implying an undervaluation of 0.8 standard deviations. This indicates that it is priced more cheaply today than 79% of all previous months. Analysis of the commodity´s price cycles since 1900 points to the start of a new secular bull market. The June 2020 low of $1.19 looks to be a longterm bottom.
Over the coming 5year period, I forecast the price of feeder cattle to increase by 8.3% annually, with a forecast range between 6.8 and 10.4%. The forecast model explains 73% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that feeder cattle´s price will breakeven by June 2025 with a 99% probability, and that there is a 26% chance that the commodity´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast feeder
224  David J. Howden cattle´s price to increase by 5.0% annually until June 2030 with a forecast range between 3.9 and 6.6%. This model explains 58% of the commodity´s 10year returns since June 1990. As such, there is a 99% probability that feeder cattle will breakeven over the coming decade, and a less than 1% chance that they will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of feeder cattle has increased from $0.75 per pound to the current close of $0.92 for an annual return of 0.7%. The alltime nominal high for the commodity came in November 2014 at a price of $1.73. In real, inflationadjusted terms the commodity´s price has mostly fallen throughout its history. Feeder cattle´s real high was in July 1948, with its subsequent low forming in August 1998. As of June 2020, the commodity´s price was lower than 93% of all prior monthly closing prices in real terms. Over longer periods, feeder cattle´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the 20th century. Nominal returns have hovered around 2% for most of the commodity´s history, with real returns averaging 1.2% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 3.4% and resulted by buying feeder cattle in January 1933 and holding them until today. Since inflation over that period averaged 3.5%, the investor earned a real loss of around 0.1% per year. More recently the commodity´s price has been in a bear market since November 2014. From that month´s high of $1.73 a collapse of 50% ensued. The June 2020 bottom of $0.92 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  225
Since 1900 the commodity has gone through ten complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the commodity´s price increase by 116% in real terms, before being corrected by a median decline of 56%. The median bull market has lasted for just over six years, and its subsequent correction has taken four years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the ten completed bull markets in feeder cattle has started from an undervalued position, with a median value of 1.2 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.9 standard deviations. Feeder Cattle: Historical Cycle Summary Declines
Advances
Date Start End Jul02 Dec04
Price Start End 7.1
4
41
3.4
Jun18
Dec21
15.85
7
62
0.1
Sep28 Feb33
15.91
5
59
1.9
Jun36
8
8
35
1.3
Aug37 Feb38
8
8
41
1.9
Jul48 May64
39
24
56
2.1
Aug73 Jan75
59
25
64
2.2
Apr79 May86
97
60
61
4.9
Mar88 Apr96
93
55
56
1.0
Jun04 Feb09
125
92
35
0.6
Oct14 Apr20
240
119
55
4.9
Apr35
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Dec04 Jun18
4.4
16
109
0.1
Dec21 Sep28
7
16
124
2.9
Feb33 Apr35
4.8
8
129
2.1
Jun36 Aug37
7.8
8
71
0.7
Feb38
7.91
39
184
0.8
May64 Aug73
24
59
70
0.2
Jan75
Apr79
25
97
192
2.2
May86 Mar88
60
93
47
1.2
Apr96 Jun04
55
125
90
2.3
Feb09 Oct14
92
240
133
0.7
Apr20 Jun20
119
129
11
1.2
Jul48
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 15.8 64 4.9 6.1
Median 4.4 56 1.9 3.3
Min. 0.5 35 0.1 1.3
Max. 13.5 192 0.1 7.1
Median 6.2 116 1.2 2.9
Min. 1.2 47 2.9 0.2
Jun26 1.7 257 116 2.9
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
Similarly, each of the commodity´s eleven completed bear markets has started from an overvalued position, with a median value of +1.9 standard deviations above the longterm mean. Over the course of each bear market feeder cattle continued to shed valuation
226  David J. Howden as its price fell. The median price decline caused the relative valuation to fall by 3.3 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in October 2014. From the starting price of $2.40 the commodity´s price fell by 55% in real terms. This decline is on par with the median decline of 56% over all recorded feeder cattle bear markets. The decline´s starting relative valuation of +4.9 standard deviations was much more extreme than the median bear market starting relative valuation of +1.9 standard deviations. At the recent April 2020 low of $1.19 the commodity was 1.2 standard deviations undervalued, square on the median starting valuation to a bull market advance. The loss of 6.1 standard deviations of valuation between 2014 and 2020 is also quite extreme compared with the median change in the measure during correction phases (3.3 standard deviations). In fact, it is tied with the 197985 decline as the most extreme bearmarket valuation swing on record. As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market.
If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in feeder cattle has lasted for over six years and gained 116% in real terms. The weakest advance, during 198688, gained 47% in real terms. As such, I expect the current cycle to gain an additional 105% in real terms by June 2026. This implies an expected annual return of 13% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, feeder cattle have increased their valuation within a band of +6.9 standard deviations (the weakest advance increased its valuation by +0.2 and the
Commodities, the Decade Ahead  227 strongest increased by +7.1 standard deviations). The +0.4 standard deviation increase in valuation since April 2020 still leaves much upside potential. The April 2020 undervaluation of 1.2 standard deviations made the commodity more undervalued than 88% of all previous months. By the time the current bull market reaches its end, I expect feeder cattle to be trading at a price which is +1.7 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to feeder cattle trading at $2.57 by June 2026, a price that is +1.7 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for feeder cattle starts in January 1858. This means that to date there have been 1,1890 5year holding periods and 1,830 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of feeder cattle is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of feeder cattle over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of feeder cattle as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 8.3% annual gain in feeder cattle over the coming 5year period. The forecast range is also strictly positive, ranging from 6.8 to 10.4%. The model explains 73% of the variation of the 300 5year returns since June 1990. Given this explanatory power of the model, I estimate that the price of feeder cattle will breakeven by June 2025 with a 99% probability, and that the return will exceed 10% with a 26% probability.
228  David J. Howden
Commodities, the Decade Ahead  229
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Feeder cattle´s relative valuation of 0.8 standard deviations below its longterm mean is on part with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by not much more than the average commodity. As such, feeder cattle are the 23rd most undervalued commodity of the group. I forecast that the commodity will yield an annual return of 6.4% over the coming five years, and 3.5% over the coming decade. Both returns are about on par with the averages for the 42 other commodities (7.6% and 5.9%). Consequently, feeder cattle rank 28th and 23rd out of 43 commodities for the 5 and 10year return forecasts.
Over the next ten years, I expect the price of feeder cattle to increase by 5.0% annually. The forecast range is clustered around this level, ranging from 3.9 to 6.6%. The model explains 58% of the variance in the meat´s 240 10year returns since June 1990. As such, I estimate that feeder cattle will breakeven by June 2030 with a probability of 99%, and that there is a less than 1% chance that its return will exceed 10% over this p period.
Feeder Cattle Forecast return rankings, out of 43 commodities Relative Valuation rd
23 Feeder Cattle 43 Commodity Avg.
0.8 0.7
Forecast returns: 5Year th
28
6.4 7.6
Probability that return exceeds 10%:
10Year rd
33
3.5 5.9
5Year th
10Year th
35
35
12 39
0 22
Finally, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 12% probability that feeder cattle can achieve this return by June 2025 and 0% by June 2030, ranking the meat 35th and last out of the 43 markets for both probabilities. Given this evidence, it is highly likely that feeder cattle will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the meat is in its current price and valuation cycle. The evidence from cattle´s price and valuation cycles since 1900 points to a probable surge in the meat´s price that will end in June 2026. At a high of $2.57 by that date, the meat will have advanced from its June 2020 low in a manner consistent with the other thirteen advances since 1900. Over this time, cattle´s relative valuation should also increase from its current undervalued position of 0.8 standard deviations, to end this bull market rally overvalued by +1.7 standard deviations.
230  David J. Howden
Commodities, the Decade Ahead  231 models also forecast for similar price increases, but over different time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 6.9% by buying cattle. This expected return falls to 7.0% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, cattle rank 34th and 27th out of the 43 commodities. This implies that cattle should yield a return comparable to the average commodity over the next decade, but far inferior over the next five years. Taking the average of its rankings for these expected returns, feeder cattle rank 27th out of the 43 commodities.
Feeder Cattle Expected return rankings, out of 43 commodities Relative Valuation rd
23 Analysis of cattle´s longerterm price behavior points to marginally lower prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a minor correction after the current bull market completes. By June 2025, I forecast cattle to be trading at $1.37 per pound, and $1.97 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 73% of the meat´s 5year returns and 58% of its 10year returns explained since June 1990. In all cases, the price of cattle is not expected to fall below its April 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying cattle today and selling them at any date over the coming decade. For example, an expected price of $1.37 in June 2025 implies an annual rate of return of 8.3% over the next five years if the investor buys cattle today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of cattle, cycle analysis predicts an appreciation peaking in June 2026, and the period valuation
Feeder Cattle 43 Commodity Median
0.8 0.8
Expected average returns: 5Year
10Year
th
27
6.9 21.2
7.0 8.1
34
th
Overall Rank th
27
232  David J. Howden
Commodities, the Decade Ahead  233
Gold Though valued since ancient times as a form of money, the majority of gold mined today is used in the manufacture of jewelry. The precious metal is highly resistant to corrosion, and is also malleable and ductile, qualities which create important industrial demands. The current supply of gold that exists above ground is around 200,000 tons, which could be contained in a cube with sides measuring 22 meters across. Approximately half of the annual gold mined is used in jewelry production, with an additional 10% used for industrial purposes. The remainder is held as a store of value to satisfy investment portfolio demands, alongside stocks, bonds, real estate, or other commodities. Approximately 85% of all gold produced since the beginning of civilization remains in use today. China has been, since 2007, the world´s largest gold producer. Production is distributed widely around the globe, although consumption is largely concentrated in China and India. The two Asian countries account for over half of all gold used globally, mostly in the form of jewelry. Official government and central bank gold holdings continue to be a significant centralized stockpile of the precious metal. The United States is the world´s largest public holder of gold with 8,133 metric tons in reserve, more than a quarter of the global total.
Gold Production
Consumption
(% World)
(% World)
China Australia Russia United States Canada Rest of World
12 9 8 6 5 59
China India United States Germany Thailand Rest of World
28 24 6 4 3 36
Official Reserves (% World)
United States Germany Italy France Russia Rest of World
26 11 8 8 7 40
Source: World Gold Council, 2020
Global gold output reached 3.3 million kilograms in 2019, a 34% increase over the previous decade. This increase came largely as a result of expanded production from China which produces 100,000 kilograms more gold annually than it did a decade ago (a 31% increase). Production growth has also been strong in Australia and Russia with each producing 100,000 extra kilograms of the yellow metal annually (47% and 61% increases over the past decade). China remains the world´s largest producer, a position it has held since overtaking Australia in 2007.
234  David J. Howden
Commodities, the Decade Ahead  235 Recycled scrap remains an important source of gold augmenting newly mined production. In the United States, approximately 87% of gold consumption comes from recycled sources. Since 1999 world output has increased at an annual rate of 5.1%. There are approximately 50 million metric tons of unmined gold in reserves globally. Over the last decade world gold reserves have grown by just 0.6% annually. Australia maintains the world´s largest reserves at 10 million metric tons (20% of global reserves). The top five countries for estimated reserves account for just half of the global total, illustrating the wide availability of the metal throughout the world. The Commodity Exchange launched gold futures in 1974 in the wake of the demise of the Bretton Woods system that fixed gold´s price. The precious metal is also traded on the International Exchange and the London Metal Exchange. The COMEX gold (GC) cash contract returned 26.3% to the investor over the past year. Futures trade in lots of 100 troy ounces and are quoted in U.S. dollars per troy ounce.
The Bottom Line Gold closed June 2020 at a price of $1,779 per troy ounce. Based on historical valuations dating to December 1791 (2,743 months) I estimate the fairvalue price of the commodity to be $1,401, implying an overvaluation of +0.7 standard deviations. This indicates that it is priced more cheaply today than only 24% of all previous months. Analysis of the metal´s price cycles since 1900 points to the continuation of its secular bull market. The November 2015 low of $1,061 looks to be a longterm bottom from which new highs will proceed from. Historically, the median bull market in gold has lasted for 4.4 years and increased its price by 296% in real terms. Following this pattern, the current bull market phase should be completed in March 2021 after an additional 241% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of gold to increase by 1.2%
annually, with a forecast range between 0.5 and 4.1%. The forecast model explains 60% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that gold´s price will breakeven by June 2025 with a 58% probability, and that there is an 8% chance that the metal´s return will be over 10% by that date. The coming decade should see negative returns. I forecast gold´s price to decrease by 2.0% annually until June 2030 with a forecast range between 2.4 and 1.6%. This model explains 91% of the metal´s 10year returns since June 1990. As such, there is only a 17% probability that gold will breakeven over the coming decade, and virtually no chance that it will yield a return greater than 10%.
Gold: Forecast Summary 1,779 1,401 +0.7
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Dec15 Mar21 241 456
5Year Forecast 5Year Annual Forecast Return, % 1.2 5Year Forecast Range, % (0.5, 4.1) 2 0.60 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
58 8
10Year Forecast 10Year Annual Forecast Return, % 2.0 10Year Forecast Range, % (2.4, 1.6) 2 0.91 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
17 0
236  David J. Howden
Historical Analysis Since June 1990, the nominal price of gold has increased from $352 per troy ounce to the current close of $1,779 for an annual return of 5.5%. The alltime nominal high for the metal came in August 2011 at a price of $1,814. In real, inflationadjusted terms the metal´s price has gently increased throughout its history. Gold´s real high was in January 1980, with its low forming July 1970. Over the past 120 years, there have only been 25 months with higher real prices than gold is currently priced at, all of them in 1980 and 201112. Over longer periods, gold has served as an excellent inflation hedge, resulting in a real yield of around 23% for most of the 20th century. Nominal returns have hovered around 6% for most of the metal´s history, with real returns averaging 2.7% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 10.6% and resulted by buying gold in March 2001 and holding it until today. Since inflation over that period averaged 2.0%, the investor earned a real gain of 8.6% per year. More recently the metal´s price has been in a bull market since November 2015. From that month´s low of $1,061 a rally of 55% has ensued. The June 2020 high of $1,779 looks to be the stop on the road higher for this longterm secular rally.
Commodities, the Decade Ahead  237 market has lasted for just over four years, and its subsequent correction has taken five years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the five completed bull markets in gold has started from an undervalued position, with a median value of 0.8 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.7 standard deviations. Similarly, each of the metal´s five completed bear markets has started from an overvalued position, with a median value of +3.5 standard deviations above the longterm mean (with the exception of the and 193470 and 19872001 bear markets which started from a mildly undervalued positions). Over the course of each bear market gold continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.6 standard deviations. Gold: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
34
35
65
0.3
Dec74 Aug76
186
104
50
4.9
Jan80 Feb85
653
287
68
3.5
Nov87 Mar01
492
257
66
0.5
Aug11 Nov15
1,813
1,061
44
4.6
Dec34
Jul70
Date Start End Jun20 Dec34
Price Start End
Real Start Rel. Change, % Val, σ
20
34
165
0.7
Dec74
35
186
296
0.8
Aug76 Jan80
104
653
362
0.2
Feb85 Nov87
287
492
57
1.7
Mar01 Aug11
257
1,813
445
1.3
Nov15 Jun20
1,061
1,779
55
0.2
Jul70
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the metal has gone through five complete price cycles. For much of this time, gold´s price was controlled tightly under the Bretton Woods system. Still, even in this pre1971 period, gold´s real price fluctuated in a manner similar to those cycles that occurred when it´s price has been set as per market supply and demand conditions. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 296% in real terms, before being corrected by a median decline of 65%. The median bull
Max. 35.6 68 4.9 5.2
Median 5.1 65 3.5 4.6
Min. 1.7 44 0.5 0.5
Max. 14.5 445 0.2 5.9
Median 4.4 296 0.8 3.7
Min. 2.7 57 1.7 0.4
Mar21 3.9 4,205 296 3.7
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The current phase of its cycles was the bull market advance which started in November 2015. From the starting price of $1,061 the metal´s price has increased by 55% in real terms. This advance is still weak by historical standards (i.e., the median 296% advance over all recorded gold bull markets). The advance´s starting relative valuation of +0.2 standard deviations was high relative to the median bull market starting relative valuation of 0.8 standard deviations. However, the preceding bear market between 2011 and 2015 shed 4.6 standard deviations of value, on par with the historical valuation change for gold during its corrective phases. At the recent June 2020 high of $1,779 the metal was +0.7 standard deviations overvalued, which is quite weakly overvalued relative to the starting valuation of historical
238  David J. Howden bear markets. The gain of +0.5 standard deviations of valuation between 2015 and 2020 is also quite low compared with the median change in the measure during advancing phases (+3.7 standard deviations). As such, the balance of cycle evidence points to the June 2020 high being a stop on the path to higher prices as the metal completes its current bull market. If a new bull market that started in November 2015 is still in force, what can we expect the future to hold? The median bull market in gold has lasted for nearly fourandahalf years and gained 296% in real terms. The weakest advance, during 198587, gained 57% in real terms. This is not far off the gain in the current advance, though in between 1985 and 1987 gold´s valuation increased by +1.2 standard deviations, more than twice as much as the metal has since 2015. Since November 2015, the metal has already gained 55%. As such, I expect the current cycle to gain an additional 241% in real terms by March 2021. This implies an expected annual return of 456% by the time the present bull market reaches completion.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, gold has increased its valuation within a band of +5.5 standard deviations (the weakest advance increased its valuation by +0.4 and the strongest increased by +5.9 standard deviations). In other words, never in the 120year price history under examination has gold failed to increase its valuation by less than +0.4 standard deviations over its bull markets. Since the November 2015 low the metal´s relative valuation has increased by +0.5 standard deviations, implying further upside potential. The June 2020 overvaluation of +0.7 standard deviations made the commodity more overvalued than 76% of all previous months. Although this overvalued price raises questions as to how much higher gold can advance, historically this valuation is not
Commodities, the Decade Ahead  239 consistent with the end of bull markets. By the time the current bull market reaches its end, I expect gold to be trading at a price which is +3.9 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to gold trading at $4,205 by March 2021, a price that is +3.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for gold starts in December 1791. This means that to date there have been 2,683 5year holding periods and 2,623 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts.
240  David J. Howden As we have seen, the future return of gold is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of gold over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of gold as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 1.2% annual gain in gold over the coming 5year period. The forecast range ranges from 0.5 to 4.1%. The model explains 60% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of gold will breakeven by June 2025 with a 58% probability, and that the return will exceed 10% with an 8% probability.
Commodities, the Decade Ahead  241
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Gold´s relative valuation of +0.7 standard deviations above its longterm mean is far higher than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is significantly overvalued. As such, gold is only the 39th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 1.2% over the coming five years, and 2.0% over the coming decade. Both returns are far lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, gold ranks 39th and 40th out of 43 commodities for the 5 and 10year return forecasts.
Gold Forecast return rankings, out of 43 commodities Relative Valuation th
39 Gold 43 Commodity Avg.
Over the next ten years, I expect the price of gold to decrease by 2.0% annually. The forecast range is also strictly negative and clustered around this level, ranging from 2.4 to 1.6%. The model explains 91% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that gold will breakeven by June 2030 with only a probability of 17%, and that there is virtually no chance that its return will exceed 10% over this period.
+0.7 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year 10Year th th
39
1.2 7.6
40
2.0 5.9
5Year th
10Year th
8 39
0 22
37
35
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is an 8% probability that gold can achieve this return by June 2025 and no chance by June 2030, ranking the metal 37th and last out of the 43 markets for both probabilities. Given this evidence, it is highly likely that gold will significantly underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context, the evidence from gold´s price and valuation cycles since 1900 points to a probable surge in the metal´s price that will end in March 2021. At a high of $4,205 by that date, the precious metal will have advanced from its November 2015 low in a manner consistent with the other five advances since 1900. Over this time, gold´s relative valuation should also increase from its current overvalued position of +0.7 standard deviations, to end this bull market rally overvalued by +3.9 standard deviations.
242  David J. Howden
Commodities, the Decade Ahead  243 coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, gold ranks 15th and 38th out of the 43 commodities. This implies that gold should yield returns comparable to the average commodity over the next five years, and significantly lower returns over the next decade. Taking the average of its rankings for these expected returns, gold ranks 39th out of the 43 commodities.
Gold Expected return rankings, out of 43 commodities Relative Valuation th
39 Gold 43 Commodity Median
Analysis of gold´s longerterm price behavior points to relatively stable prices over the next five and tenyear periods, but which will represent significant price collapses from the forecast cycle highs. By June 2015, I forecast gold to be trading at $1,893 per troy ounce, and $1,460 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 60% of the metal´s 5year returns and 91% of its 10year returns explained since June 1990. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying gold today and selling it at any date over the coming decade. For example, an expected price of $1,893 in June 2025 implies an annual rate of return of 1.2% over the next five years if the investor buys the metal today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of gold, cycle analysis predicts a continued appreciation topping in March 2021, and the period valuation models forecast relatively stable prices, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 26.4% by buying gold. This expected return is barely better than breakeven at 1.2% annually over the
+0.7 0.8
Expected average returns: 5Year th
15
26.4 21.2
10Year th
38
1.2 8.1
Overall Rank th
39
244  David J. Howden
Commodities, the Decade Ahead  245
Heating Oil Most heating oils are chemically similar to diesel fuel. The liquid petroleum product is generally of a low viscosity and commonly used as a fuel oil in furnaces or boilers in buildings. Heating oil differs from other energy products in that it its retail supply chain is dominated by smaller businesses rather than large oil companies. Heating oil is the second most common product derived from crude oil, after gasoline. Including diesel fuel distillates, the European Union is the world´s largest producer and consumer. Together with the United States and China, it produces half of the world distillates.
Distillate Oil* European Union United States China India Brazil Rest of World
Production
Consumption
(% World)
(% World)
21 15 14 6 4 41
European Union United States China India Russia Rest of World
19 17 13 7 5 38
Source: United States Energy Information Administration, 2020 * Includes No. 1, No. 2., and No. 4 diesel and fuel oils
Heating oil trades on the Intercontinental Exchange, and also on the New York Mercantile Exchange. The ICE heating oil (O) cash contract returned 35.7% to the investor over the past year. Futures trade in lots of 1,000 barrels and are quoted in U.S. dollars per gallon.
The Bottom Line Heating oil closed June 2020 at a price of $1.25 per gallon. Based on historical valuations dating to February 1973 (569 months) I estimate the fairvalue price of the commodity to be $2.64, implying an undervaluation of 1.5 standard deviations. This indicates that it is priced more cheaply today than 94% of all previous months.
246  David J. Howden
Commodities, the Decade Ahead  247
Analysis of the oil´s price cycles since 1947 points to the start of a new secular bull market. The April 2020 low of $0.88 looks to be a longterm bottom. Historically, the median bull market in heating oil has lasted for twoandahalf years and increased its price by 138% in real terms. Following this pattern, the current bull market phase should be completed in October 2022 after an additional 96% gain in the oil´s inflationadjusted price.
oil´s price to increase by 12.2% annually until June 2030 with a forecast range between 10.7 and 14.2%. This model explains 74% of the oil´s 10year returns since June 1990. As such, there is a 99% probability that heating oil will breakeven over the coming decade, and a 72% chance that it will yield a return greater than 10%.
Historical Analysis
Heating Oil: Forecast Summary 1.25 2.64 1.5
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Apr20 Oct22 96 34
5Year Forecast 5Year Annual Forecast Return, % 18.3 5Year Forecast Range, % (16.7, 21.3) 2 0.48 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
98 84
10Year Forecast 10Year Annual Forecast Return, % 12.2 10Year Forecast Range, % (10.7, 14.2) 0.74 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 72
Over the coming 5year period, I forecast the price of heating oil to increase by 18.3% annually, with a forecast range between 16.7 and 21.3%. The forecast model explains 48% of the variation in the oil´s 5year returns since June 1990. Consequently, I forecast that heating oil´s price will breakeven by June 2025 with a 98% probability, and that there is an 84% chance that the oil´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast heating
Since June 1990, the nominal price of heating oil has increased from $0.49 per gallon to the current close of $1.25 for an annual return of 3.2%. The alltime nominal high for the oil came in June 2008 at a price of $3.91. In real, inflationadjusted terms the oil´s price has meandered between $1 and $3 throughout its history. Heating oil´s real high was in June 2008, with its low forming much earlier, in March 1979. As of June 2020, the oil´s price was lower than 94% of all prior monthly closing prices in real terms. Over longer periods, heating oil´s price has just kept pace with general price inflation, resulting in a real yield of around zero to 0.5% for most of the past 70 years. Nominal returns have hovered around 4% for most of the oil´s history, with real returns averaging 0.3% annually between 1947 and 2010. The highest longterm nominal return the investor could have earned was 5.7% and resulted by buying heating oil in July 1969 and holding it until today. Since inflation over that period averaged 3.9%, the investor would have earned a real return of 1.8% per year. More recently the oil´s price has been in a bear market since September 2018. From that month´s high of $2.35 a collapse of 63% ensued. The April 2020 bottom of $0.88 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
248  David J. Howden
Commodities, the Decade Ahead  249
Since 1947 the oil has gone through ten complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen heating oil´s price increase by 138% in real terms, before being corrected by a median decline of 54%. The median bull market has lasted for twoandahalf years, and its subsequent correction has taken nearly two years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the ten completed bull markets in heating oil that the commodity´s relative valuation is available for has started from an undervalued position, with a median value of 1.4 standard deviations below the longterm mean. (The only exceptions to this are the 200308 and 200911 advances that both started from approximately fairlyvalued positions.) From these undervalued starting positions, the median bull market increased its relative valuation by +2.3 standard deviations. Heating Oil: Historical Cycle Summary Declines
standard deviations above the longterm mean (with the exceptions of the 198990, 199098 and 201820 bear markets which all started from approximately fairlyvalued positions). Over the course of each bear market heating oil continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 1.9 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in September 2018. From the starting price of $2.35, heating oil´s price fell by 63% in real terms. This decline is a little more extreme than the median decline of 54% over all recorded heating oil bear markets. The decline´s starting relative valuation of 0.4 standard deviations is unusual since it is not only far lower than the starting relative valuation to the median bear market (+0.9) but was actually mildly undervalued. The change in relative valuation over the course of the bear market was also somewhat weak at 1.5 standard deviations against a median value of –1.9. The timing was spot on, however, as the decline was completed in 19 months which is also the median duration for all eleven bear markets.
Advances
Date Start End Mar48 Jun49
Price Start End 0.11
0.05
52
n.a.
Feb57 Oct69
0.12
0.08
53
n.a.
Jan75
Sep78
0.50
0.40
38
n.a.
Jan81
Jul86
1.03
0.32
75
1.0
Dec89 Jun90
1.02
0.49
54
0.1
Sep90 Nov98
1.05
0.31
76
0.2
Nov00 Jan02
1.05
0.52
51
0.8
Feb03 May03
1.26
0.75
40
2.2
Jun08 Feb09
3.91
1.27
67
5.4
Apr11
Jan16
3.28
1.09
68
2.6
Sep18
Apr20
2.35
0.88
63
0.4
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jun49 Feb57
0.05
0.12
94
n.a.
Oct69
Jan75
0.08
0.50
369
n.a.
Sep78
Jan81
0.40
1.03
97
0.4
Jul86
Dec89
0.32
1.02
177
2.5
Jun90 Sep90
0.49
1.05
111
1.5
Nov98 Nov00
0.31
1.05
217
1.4
Jan02 Feb03
0.52
1.26
132
0.9
May03 Jun08
0.75
3.91
335
0.2
Feb09
Apr11
1.27
3.28
144
0.3
Jan16
Sep18
1.09
2.35
102
1.6
Apr20 Jun20
0.88
1.25
42
1.9
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 12.7 76 5.4 5.1
Median 1.6 54 0.9 1.9
Min. 0.2 38 0.4 1.2
Max. 7.7 369 0.3 5.2
Median 2.5 138 1.4 2.3
Min. 0.3 94 2.5 1.2
Oct22 0.4 2.09 138 2.3
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
Similarly, each of the oil´s eleven completed bear markets that have relative valuation data available for has started from an overvalued position, with a median value of +0.9
At the recent April 2020 low of $0.88 the oil was 1.9 standard deviations undervalued, more extreme than the median starting valuation to a bull market advance. As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in heating oil has lasted for over twoandahalf years and gained 138% in real terms. The weakest advance, during 194957, gained 94% in real terms. Since April 2020, the oil has already gained 42%. As such, I expect the current cycle to gain an additional 96% in real terms by October 2022. This implies an expected annual return of 34% by the time the present bull market reaches completion.
250  David J. Howden More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, heating oil has increased its valuation within a relatively narrow band of +4.0 standard deviations (the weakest advance increased its valuation by +1.2 and the strongest increased by +5.2 standard deviations). In other words, never in the 73year price history under examination has heating oil failed to increase its valuation by less than +1.2 standard deviations over its bull market. Since the April 2020 low the oil´s relative valuation has increased by +0.4 standard deviations, implying further upside potential. The April 2020 undervaluation of 1.9 standard deviations made the commodity more undervalued than 97% of all previous months. By the time the current bull market reaches its end, I expect heating oil to be trading at a price which is +0.4 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to heating oil trading at $2.09 by October 2022, a price that is +0.4 standard deviations overvalued.
Commodities, the Decade Ahead  251 over past data, as well as their expected ability to estimate future values.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for heating oil starts in February 1973. This means that to date there have been 509 5year holding periods and 449 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of heating oil is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of heating oil over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of heating oil as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power
I forecast an 18.3% annual gain in heating oil over the coming 5year period. The forecast range is also strictly positive, ranging from 16.7 to 21.3%. The model explains 48% of the variation of the 300 5year returns of the oil since June 1990. Given this explanatory power of the model, I estimate that the price of heating oil will breakeven by June 2025 with a 98% probability, and that the return will exceed 10% with an 84% probability. Over the next ten years, I expect the price of heating oil to increase by 12.2% annually. The forecast range is clustered around this level, ranging from 10.7 to 14.2%. The model explains 74% of the variance in the oil´s 240 10year returns since June 1990. As such, I estimate that heating oil will breakeven by June 2030 with a probability of 99%, and that there is a 72% chance that its return will exceed 10% over this period.
252  David J. Howden
Commodities, the Decade Ahead  253
I forecast that heating oil will yield an annual return of 18.3% over the coming five years, and 12.2% over the coming decade. Both returns are nearly double the averages for the 42 other commodities (7.6% and 5.9%). Consequently, heating oil ranks 2nd out of 43 commodities for both the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is an 84% probability that heating oil can achieve this return by June 2025 and 72% by June 2030, ranking the oil 1st and 2nd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that heating oil will outperform the average commodity over both the coming 5and 10year periods.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Heating oil´s relative valuation of 1.5 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, heating oil is the 5th most undervalued commodity of the group.
Heating Oil Forecast return rankings, out of 43 commodities Relative Valuation th
Heating Oil 43 Commodity Avg.
Forecast returns: 5Year nd
Probability that return exceeds 10%:
10Year rd
5
2
3
1.5 0.7
18.3 7.6
12.2 5.9
5Year st
1
84 39
10Year nd
2
72 22
To put the full analysis in context, the evidence from heating oil´s price and valuation cycles since 1947 points to a probably surge in the oil´s price that will end in October 2022. At a high of $2.09 by that date, the oil will have advanced from its April 2020 low in a manner consistent with the other ten advances since 1947. Over this time, heating oil´s relative valuation should also increase from its current undervalued position of 1.5 standard deviations, to end this bull market rally overvalued by +0.4 standard deviations. Analysis of the oil´s longerterm price behavior points to substantially higher prices over the next five and tenyear periods which will augment further the forecast cycle highs. By June 2025, I forecast heating oil to be trading at $2.90 per gallon, and $3.97 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 48% of the metal´s 5year returns and 74% of its 10year returns explained since June 1990.
254  David J. Howden
Commodities, the Decade Ahead  255
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying heating oil today and selling it at any date over the coming decade. For example, an expected price of $2.90 in June 2025 implies an annual rate of return of 18.3% over the next five years if the investor buys heating oil today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of heating oil, cycle analysis predicts a swift appreciation peaking in October 2022, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 23.9% by buying heating oil. This expected return falls to 18.2% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, heating oil ranks 18th and 1st out of the 43 commodities. This implies that heating oil should yield superior returns relative to the average commodity over both the coming five years, and especially over the next decade. Taking the average of its rankings for these expected returns, heating oil ranks 2nd out of the 43 commodities.
Heating Oil Expected return rankings, out of 43 commodities Relative Valuation th
5 Heating Oil 43 Commodity Median
1.5 0.8
Expected average returns: 5Year th
10Year st
23.9 21.2
18.2 8.1
18
1
Overall Rank nd
2
Iron Iron ore is the primary source of iron for the world´s steel industry. Nearly all (approximately 98%) of iron is used in steel making. The rocks and minerals from which iron can be extracted are, along with oil, among the most important commodities to the global economy. Iron is the most abundant element on earth, though it is not commonly Iron Ore found in the crust. While ironrich Production deposits are not uncommon (% World) throughout the world, oregrade mining operations are concentrated in Australia 37 relatively few countries since it is a highvolume, lowmargin business. Brazil 19 Global iron output reached 2,500 China 14 million metric tons in 2019, a 14% India 8 increase over the previous decade. This increase came largely as a result of Russia 4 expanded production from Australia Rest of World 17 which has increased its mined ore by 530 million metric tons annually since Source: USGS, 2020 2009 (a 136% increase). Brazil and China have also seen large production gains, with output up by 181% and 252% since 2009 for an additional 61 and 258 million tons of ore annually. The big trend of the past decade has been the continuation of the trend towards increased concentration in iron ore production. Outside of the top three producers the rest of the world now produces nearly 500 million tons of ore less annually than it did in 2009, a 40% drop. While a decade ago nearly 40% of the world´s iron ore was sourced outside of the big three
256  David J. Howden
Commodities, the Decade Ahead  257 producers, today that figure is less than 30%. Australia remains the world´s largest producer, a position it has held since overtaking Brazil in 2009. Since 1999 world output has increased at an annual rate of 4.9%.
There are approximately 170 billion metric tons of iron ore in reserves globally. Over the last decade world iron ore reserves have grown by just 0.6% annually. Australia maintains the world´s largest iron reserves 48 billion tons (28% of global reserves). Although just five countries account for 76% of global reserves, the ore is found widely throughout the world and mined in about 50 countries. Iron is traded on the Commodity Exchange, and also on the Intercontinental Exchange. The COMEX iron (TIO) cash contract returned 9.5% to the investor over the past year. Futures trade in lots of 500 metric tons and are quoted in U.S. dollars per metric ton.
The Bottom Line Iron closed June 2020 at a price of $98.85 per metric ton. Based on historical valuations dating to January 1873 (1,770 months) I estimate the fairvalue price of the commodity to be $103.68, implying an undervaluation of 0.3 standard deviations. This indicates that it is priced more cheaply today than 61% of all previous months. Analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The February 2020 low of $80 looks to be a longterm bottom. Historically, the median bull market in iron has lasted for three years and increased its price by 68% in real terms. Following this pattern, the current bull market phase should be completed in February 2023 after an additional 45% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of iron to increase by 14.1% annually, with a forecast range between 11.2 and 18.6%. The forecast model explains 59% of the variation in the ore´s 5year returns since June 1990. Consequently, I forecast that iron´s price will breakeven by June 2025 with a 90% probability, and that there is a 64% chance that the ore´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast iron´s price to increase by 8.8% annually until June 2030 with a forecast range between 7.2 and 10.9%. This model explains 65% of the metal´s 10year returns since June 1990. As such, there is a 92% probability that iron will breakeven over the coming decade, and a 42% chance that it will yield a return greater than 10%.
Iron: Forecast Summary 98 104 0.3
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Feb20 Feb23 45 5
5Year Forecast 5Year Annual Forecast Return, % 14.1 5Year Forecast Range, % (11.2, 18.6) 2 0.59 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
90 64
10Year Forecast 10Year Annual Forecast Return, % 8.8 10Year Forecast Range, % (7.2, 10.9) 2 0.65 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
92 42
Historical Analysis Since June 1990, the nominal price of iron has increased from $13.78 per metric ton to the current close of $98.85 for an annual return of 6.8%. The alltime nominal high for the metal came in February 2011 at a price of $183.62. In real, inflationadjusted terms iron´s price had, until the 2000s, mostly fallen throughout its history. Its real high was in February 2011, with its low forming in October 2002. As of June 2020, the metal´s price was lower than only 2% of all prior monthly closing prices in real terms. Over longer periods, iron´s price has kept pace with general price inflation, resulting in a real yield of around 23% for most of the 20th century. Nominal returns have hovered
258  David J. Howden around 5% for most of the metal´s history, with real returns averaging 2.5% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 12.8% and resulted by buying iron in December 2003 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 10.8% per year. More recently the iron´s price has been in a bear market since July 2019. From that month´s high of $120 a collapse of 33% ensued. The February 2020 bottom of $80 looks to be a major low and should usher in a multiyear secular bull market.
Commodities, the Decade Ahead  259 valuation to fall by 2.6 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in July 2019. From the starting price of $120 iron´s price fell by 33% in real terms. This decline was somewhat weak relative to the median decline of 45% over all recorded the metal´s bear markets. Iron: Historical Cycle Summary Declines Date Start End Apr01 Dec04
Price Start End
Advances Real Start Rel. Change, % Val, σ
2
1
45
n.a.
Feb08 Nov15
2
1
42
2.2
Dec16 Nov25
3
2
46
0.7
Jun39
Jan48
2
3
30
1.0
Feb57 Apr74
6
6
46
1.9
Apr77 Oct02
10
12
58
1.4
Feb11
Jan16
184
42
79
14.6
Feb17 May17
92
56
39
0.0
Jul19
120
80
33
0.1
Feb20
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Dec04 Feb08
1
2
58
0.2
Nov15 Dec16
1
3
60
1.3
Nov25 Jun39
2
2
52
1.6
Jan48 Feb57
3
6
76
0.6
Apr74 Apr77
6
10
39
1.5
Oct02 Feb11
12
184
1,107
1.5
Jan16
Feb17
42
92
114
0.8
May17
Jul19
56
120
104
0.7
Feb20 Jun20
80
99
23
0.6
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Since 1900 the metal has gone through eight complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 68% in real terms, before being corrected by a median decline of 45%. The median bull market has lasted for three years, and its subsequent correction has taken over just under eight years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the eight completed bull markets in iron that the commodity´s relative valuation can be calculated for has started from an undervalued position, with a median value of 0.8 standard deviations below the longterm mean (with the exception of the 19041908 and 194857 advances, which both started from mildly overvalued positions). From these undervalued starting positions, the median bull market increased its relative valuation by +2.0 standard deviations. Similarly, each of the metal´s nine completed bear markets that have relative valuation data available for has started from an overvalued position, with a median value of +1.2 standard deviations above the longterm mean. Over the course of each bear market iron continued to shed valuation as its price fell. The median price decline caused the relative
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 25.5 79 14.6 15.4
Median 7.8 45 1.2 2.6
Min. 0.2 30 0.0 0.4
Max. 13.6 1,107 0.6 16.1
Median 3.0 68 0.8 2.0
Min. 0.3 39 1.6 0.8
Feb23 1.4 135 68 2.0
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
At the recent February 2020 low of $80 the metal was 0.6 standard deviations undervalued, near to the median starting valuation of iron´s eight bull market advances. The loss of 0.7 standard deviations of valuation between 2019 and 2020 is also weak compared with the median change in the measure during correction phases (2.6 standard deviations). However, the current undervaluation is roughly on par with the median value of 0.8 standard deviations. As such, the balance of cycle evidence points to the February 2020 low being a major low that should usher in a longterm secular bull market. If a new bull market started in February 2020, what can we expect the future to hold? The median bull market in iron has lasted for three years and gained 68% in real terms. The weakest advance, during 197477, gained 39% in real terms. Since February 2020, the metal has already gained 23%. As such, I expect the current cycle to gain an additional 45% in real terms by February 2023. This implies an expected annual return of 5% by the time the present bull market reaches completion.
260  David J. Howden More dependable than forecasts of price movements are changes to relative valuation. Iron experienced, in valuation terms, the largest bull market of any commodity ever between 2002 and 2011. In those nine years, the metal´s price gained 1,107% and 16.1 (!) standard deviations of value. In some ways, this 16sigma event skews the results when comparing changes in iron´s valuation over time. At the same time, the use of median values mitigates the effect of extreme events, such as this one. Excluding this extreme event, the median bull market in iron has gained +2.0 standard deviations of value, within a narrow range of +2.1 standard deviations (the weakest advance increased its valuation by +0.8 and the strongest (excluding 201116) increased by +2.9 standard deviations). Since the February 2020 low the ore´s relative valuation has increased by +0.3 standard deviations, implying further upside potential.
The June 2020 undervaluation of 0.3 standard deviations made the commodity more undervalued than 61% of all previous months. By the time the current bull market reaches its end, I expect iron to be trading at a price which is +1.4 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to iron trading at $135 by February 2023, a price that is +1.4 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure
Commodities, the Decade Ahead  261 historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like.
We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for iron starts in January 1873. This means that to date there have been 1,710 5year holding periods and 1,650 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of iron is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of iron over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of iron as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power
262  David J. Howden over past data, as well as their expected ability to estimate future values. I forecast a 14.1% annual gain in iron over the coming 5year period. The forecast range is also strictly positive, ranging from 11.2 to 18.6%. The model explains 59% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of iron will breakeven by June 2025 with a 90% probability, and that the return will exceed 10% with a 64% probability.
Commodities, the Decade Ahead  263 valued in absolute terms, but is actually overvalued relative to other commodities. As such, iron is the 36th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 14.1% over the coming five years, and 8.8% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, iron ranks 7 th and 13th out of 43 commodities for the 5 and 10year return forecasts.
Iron Forecast return rankings, out of 43 commodities
Relative Valuation th
36 Iron Ore 43 Commodity Avg.
Over the next ten years, I expect the price of iron to increase by 8.8% annually. The forecast range is clustered around this level, ranging from 7.2 to 10.9%. The model explains 65% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that iron will breakeven by June 2030 with a probability of 92%, and that there is a 42% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Iron´s relative valuation of 0.3 standard deviations below its longterm mean is less undervalued than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is approximately fairly
0.3 0.7
Forecast returns
Probability that return exceeds 10%
5Year th
10Year th
5Year th
10Year th
14.1 7.6
8.8 5.9
65 39
42 22
7
13
8
11
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 65% probability that iron can achieve this return by June 2025 and 42% by June 2030, ranking the metal 8 th and 11th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that iron will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the metal is in its current price and valuation cycle. The evidence from iron´s price and valuation cycles since 1900 points to a probable surge in the metal´s price that will end in February 2023. At a high of $135 by that date, iron will have advanced from its February 2020 low in a manner consistent with the other nine advances since 1900. Over this time, its relative valuation should also increase from its current undervalued position of 0.3 standard deviations, to end this bull market rally overvalued by +1.4 standard deviations. Analysis of iron´s longerterm price behavior also points to higher prices five years from now. These longerterm forecasts imply a continuation of the bull market to reach price levels above the 2011 highs. By June 2025, I forecast iron to be trading at $191 per metric ton, and $229 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 59% of the metal´s 5year returns and 65% of its 10year returns explained since June 1990. In all cases, the price of iron is not expected to fall below its February 2020 low at any time over the coming decade.
264  David J. Howden
Commodities, the Decade Ahead  265 iron ranks 29th out of the 43 commodities.
Iron Expected return rankings, out of 43 commodities Relative Valuation th
36 Iron 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying iron today and selling it at any date over the coming decade. For example, an expected price of $191 in June 2025 implies an annual rate of return of 14.1% over the next five years if the investor buys iron today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of iron, cycle analysis and the period forecast models confirm each other and suggest a prolonged advance throughout the next decade. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 13.7% by buying iron. This expected return falls to 12.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, iron ranks 28th and 9th out of the 43 commodities. This implies that iron should yield returns superior to the median commodity over the next ten years, but far lower returns by 2025. Taking the average of its rankings for these expected returns,
0.3 0.8
Expected average returns: 5Year th
10Year th
13.7 21.2
12.8 8.1
28
9
Overall Rank th
29
266  David J. Howden
Commodities, the Decade Ahead  267
Lead Lead is a heavy metal used extensively in construction, plumbing, batteries, solder, and alloys. The soft and malleable metal has a relatively low melting point, making it ideal for alloying. The bluegrey metal has been used for at least 5,000 years. Historically it was used primarily for ammunition and glass and ceramic making. After the electrical age, and especially after World War I, lead became more common in solder and, especially, gasoline and battery production. Today leadacid batteries provide the largest source of demand (88% of lead consumption in the United States goes to this purpose). Ammunition, casting metals and glass and ceramic making still comprise important roles for the metal. Global lead mine output reached 4.5 million metric tons in 2019, a 16% Lead increase over the previous decade. Production This increase came largely as a result of expanded production from smaller (% World) world producers and offset a decline in China 46 mine production in China. Output peaked in 2014 and has since fallen by Australia 9 15%. This increase came Peru 6 notwithstanding some large drops in United States 6 Australian and Peruvian production (of 24% and 4%). China´s lead Mexico 5 output has surged by 31% during the Rest of World 27 past decade, with the 0.5 metric ton annual increase more than offsetting Source: USGS, 2020 the declines elsewhere in the world. China remains the world´s large producer by a large margin, a position it has held since overtaking Australia in 2003. Recycled scrap remains an important source of lead augmenting production. In the United States, approximately 73% of lead consumption comes from recycled sources, mostly leadacid batteries. Since 1999 world output has increased at an annual rate of 1.9%. There are approximately 90 million tons of lead reserves globally. Over the last decade world lead reserves have grown by 1.3% annually. China maintains the world´s largest
268  David J. Howden
Commodities, the Decade Ahead  269 lead reserves, 18 million tons (20% of global reserves). Although just five countries account for 80% of global reserves, the metal is found widely throughout the world. The United States has negligible reserves (around 5% of global levels) although the ability to recycle large amounts of lead compensate for this limitation. Lead contracts are first launched on the London Metal Exchange in 1920, and now also trade on the Commodity Exchange. The LME lead (PB) cash contract returned 6.6% to the investor over the past year. Futures trade in lots of 25 metric tons and are quoted in U.S. dollars per metric ton.
Over the coming 5year period, I forecast the price of lead to increase by 11.4% annually, with a forecast range between 11.0 and 12.1%. The forecast model explains 46% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that lead´s price will breakeven by June 2025 with an 88% probability, and that there is a 56% chance that the metal´s return will be over 10% by that date. The coming decade should see mildly more subdued returns. I forecast lead´s price to increase by 10.2% annually until June 2030 with a forecast range between 38.2 and 12.8%. This model explains 71% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that lead will breakeven over the coming decade, and a 52% chance that it will yield a return greater than 10%.
Lead: Forecast Summary Current Price FairValue Price Relative Valuation, σ
1,788 2,424 0.8
Cycle Forecast Forecast Trend Bottoming Trend Start Date Jan18 Expected Trend End Date Nov23 Expected Real Return Remaining, % 24 8 Expected Real Return Remaining, annualized % 5Year Forecast 5Year Annual Forecast Return, % 11.4 5Year Forecast Range, % (11.0, 12.1) 2 0.46 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
88 56
10Year Forecast
The Bottom Line Lead closed June 2020 at a price of $1,788 per metric ton. Based on historical valuations dating to June 1890 (1,333 months) I estimate the fairvalue price of the commodity to be $2,424, implying an undervaluation of 0.8 standard deviations. This indicates that it is priced more cheaply today than 80% of all previous months. Analysis of the metal´s price cycles since 1900 points to the continuation of the longterm secular bear market that started at the January 2018 high of $2,624. Historically, the median bear market in lead has lasted for 5.8 years and decreased its price by 58% in real terms. Following this pattern, the current bear market phase should be completed in November 2023 after an additional 24% loss in the metal´s inflationadjusted price.
10Year Annual Forecast Return, % 10.2 10Year Forecast Range, % (8.2, 12.8) 2 0.71 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 52
270  David J. Howden
Historical Analysis Since June 1990, the nominal price of lead has increased from $918 per metric ton to the current close of $1,789 for an annual return of 2.2%. The alltime nominal high for the metal came in October 2007 at a price of $3,691. In real, inflationadjusted terms the metal´s price has been flat, trading between $2,000 and $4,000 for most of its history. Lead´s real high was in October 2007, with its low forming in September 2002. As of June 2020, the metal´s price was lower than 69% of all prior monthly closing prices in real terms. Over longer periods, lead´s price has just kept pace with general price inflation, resulting in a real yield of around negative zero for most of the 20th century. Nominal returns have hovered around 3% for most of the metal´s history, with real returns averaging 0.2% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 8.7% and resulted by buying lead in September 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 6.7% per year. More recently the metal´s price has been in a bear market since January 2018. From that month´s high of $2,624 a collapse of 34% has ensued. The June 2020 bottom of $1,788 looks to be the stop along the way of the longterm secular decline which should continue to new lows over the coming years.
Commodities, the Decade Ahead  271 The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the nine completed bull markets in lead that the commodity´s relative valuation can be calculated for has started from an undervalued position, with a median value of 1.1 standard deviations below the longterm mean (with the exception of the 200811 bull market that started from an approximately fairvalued position). From these undervalued starting positions, the median bull market increased its relative valuation by +2.2 standard deviations. Similarly, each of the metal´s nine completed bear markets that with available relative valuation data has started from an overvalued position, with a median value of +1.5 standard deviations above the longterm mean (with the exception of the 196571 bear market which started from an approximately fairlyvalued position). Over the course of each bear market lead continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.6 standard deviations. Lead: Historical Cycle Summary Declines
Advances
Date Start End Mar17 Jun21
Price Start End 190
103
63
n.a.
Jun25
Jun32
206
73
54
n.a.
Jun48
Jun62
411
219
58
2.1
Jun65
Jun71
365
317
32
0.1
Jun79 Mar85
1201
338
81
3.2
Jun90 Sep93
919
364
64
0.8
May96 Sep02
828
405
58
0.7
Oct07 Dec08
3,691
949
74
7.0
Mar11 Nov15
2,720
1,630
43
2.3
Jan18
2,624
1,788
34
0.5
Jun20
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jun21
Jun25
103
206
102
n.a.
Jun32
Jun48
73
411
216
n.a.
Jun62
Jun65
219
365
60
2.2
Jun71
Jun79
317
1,201
112
1.1
Mar85 Jun90
338
919
123
1.9
Sep93 May96
364
828
108
1.3
Sep02 Oct07
405
3,691
690
1.0
Dec08 Mar11
949
2,720
167
0.1
2,624
54
0.3
Nov15
Jan18
1,630
Max. 16.0 690 0.1 8.0
Median 4.0 112 1.1 2.2
Min. 2.2 54 2.2 0.8
Current Bear Market Forecast End Date Relative Valuation Price Real Decline, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the metal has gone through nine complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 112% in real terms, before being corrected by a median decline of 58%. The median bull market has lasted for four years, and its subsequent correction has taken nearly six years to complete.
Max. 14.0 81 7.0 6.9
Median 5.8 58 1.5 2.6
Nov23 2.1 1,102 58 2.6 Min. 1.2 32 0.1 1.0
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The current phase of its cycles is the bear market decline which started in January 2018. From the starting price of $2,624 the metal´s price has thus far fallen by 34% in real terms. This decline is far lower than the median decline of 58% over all recorded lead bear markets. The decline´s starting relative valuation of +0.5 standard deviations
272  David J. Howden was also weak relative to the median bear market starting relative valuation of +1.5 standard deviations. At the recent June 2020 low of $1,788 the metal was 0.8 standard deviations undervalued, not especially cheap relative to the median starting valuation to a bull market advance (1.1 standard deviations). The loss of 1.3 standard deviations of valuation between 2018 and 2020 is also quite weak compared with the median change in the measure during correction phases (2.6 standard deviations). As such, the balance of cycle evidence points to the June 2020 low as a stop along the current bear market, with further lows probable as the metal completes its decline. If the bear market that started in January 2018 is still in force, what can we expect the future to hold? The median bear market in lead has lasted for nearly six years and lost 56% in real terms. The weakest decline, during 196571, lost 32% in real terms. Since January 2018, the metal has already lost 34%. As such, I expect the current cycle to lose an additional 24% in real terms by November 2023. This implies an expected annual return of 8% by the time the present bear market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bear markets to date, lead has decreased its valuation within a band of 5.9 standard deviations (the weakest decline decreased its valuation by 1.0 and the strongest decreased by 6.9 standard deviations). In other words, never in the 120year price history under examination has the metal failed to decrease its valuation by less than 1.0 standard deviations over its bear market. Since the January 2018 low the metal´s relative valuation has decreased by 1.3 standard deviations, implying further downside potential.
The June 2020 undervaluation of 0.8 standard deviations made the commodity more undervalued than 79% of all previous months. By the time the current bear market reaches its end, I expect lead to be trading at a price which is 2.1 standard deviations
Commodities, the Decade Ahead  273 undervalued relative to its longterm average. In sum, cycle analysis points to lead trading at $1,102 by November 2023, a price that is 2.1 standard deviations undervalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for lead starts in June 1909. This means that to date there have been 1,273 5year holding periods and 1,213 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts.
As we have seen, the future return of lead is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver
274  David J. Howden far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of lead over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of lead as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 11.4% annual gain in lead over the coming 5year period. The forecast range is also strictly positive, ranging from 11.0 to 12.1%. The model explains 46% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of lead will breakeven by June 2025 with an 88% probability, and that the return will exceed 10% with a 56% probability.
Commodities, the Decade Ahead  275
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Lead´s relative valuation of 0.8 standard deviations below its longterm mean is roughly on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by no more than the average commodity. As such, lead is the 21st most undervalued commodity of the group. I forecast that the metal will yield an annual return of 11.4% over the coming five years, and 10.2% over the coming decade. Both returns are higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, lead ranks 11th and 8th out of 43 commodities for the 5 and 10year return forecasts.
Lead Forecast return rankings, out of 43 commodities Relative Valuation st
21 Lead 43 Commodity Avg.
Over the next ten years, I expect the price of lead to increase by 10.2% annually. The forecast range is clustered around this level, ranging from 8.2 to 12.8%. The model explains 71% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that lead will breakeven by June 2030 with a probability of 99%, and that there is a 52% chance that its return will exceed 10% over this period.
0.8 0.7
Forecast returns: 5Year th
11
11.4 7.6
Probability that return exceeds 10%:
10Year
5Year
th
11
10.2 5.9
56 39
8
th
10Year th
8
52 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 56% probability that lead can achieve this return by June 2025 and 52% by June 2030, ranking the metal 11th and 8th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that lead will overperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the metal is in its current price and valuation cycle. The evidence from lead´s price and valuation cycles since 1909 points to a probable continuation in the metal´s bear market that will end in November 2023. At a low of $1,102 by that date, lead will have declined from its January 2018 low in a manner consistent with the other nine declines since 1909. Analysis of lead´s longerterm price behavior points to somewhat higher prices five years from now, with a subsequent surge going out to 2030. These longerterm forecasts
276  David J. Howden imply a sharp rally once the current bear market completes, taking the metal above its current alltime high set in 2007. By June 2025, I forecast lead to be trading at $3,068 per metric ton, and $4,728 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 46% of the metal´s 5year returns and 71% of its 10year returns explained since June 1990.
Commodities, the Decade Ahead  277 coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 11.2% by buying lead. This expected return is improved at 10.2% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, lead ranks 41st and 16th out of the 43 commodities. This implies that lead should yield far lower returns than the average commodity over both the coming five years, and comparable returns over the next decade. Taking the average of its rankings for these expected returns, lead rank 20th out of the 43 commodities.
Lead Expected return rankings, out of 43 commodities Relative Valuation st
21 Lead 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying lead today and selling it at any date over the coming decade. For example, an expected price of $3,068 in June 2025 implies an annual rate of return of 11.4% over the next five years if the investor buys the metal today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of lead, cycle analysis predicts a continued depreciation bottoming in November 2023. In contrast, the period valuation models forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the
0.8 0.8
Expected average returns: 5Year st
41
11.2 21.2
10Year th
16
10.2 8.1
Overall Rank th
20
278  David J. Howden
Commodities, the Decade Ahead  279
Lean Hogs Despite being taboo in several major world religions, pork is the most widely eaten animal meat globally. Hogs are raised primarily for pork, with smaller demands stemming from their skin. The most common source of pork meat in the United States is lean hogs. Hogs are ready for market at a weight of approximately 270 pounds (125 kilograms) and yield an average carcass of around 200 pounds (90 kilograms). China is by far the world´s largest producer and consumer of pork. Together with the European Union and the United States, it produces 75% of the world´s pork and nearly as much consumption.
Swine Production
Consumption
(% World)
China European Union United States Vietnam Brazil Rest of World
45 20 10 3 3 18
(% World)
China European Union United States Russia Brazil Rest of World
40 22 11 4 3 20
Source: Food and Agriculture Organization of the United Nations; USDA, 2020
Global pork production reached 121 million tons in 2019, a 17% increase over the previous decade. This increase came largely as a result of expanded production in China, where annual output has increased by 7.8 million tons over the past decade (17%). Output increases have also been strong in smaller pork producing countries. China remains the world´s top producer by a large margin, a position it has held since overtaking the European Union in 1987. Since 1999 world output has increased at an annual rate of 1.5%. This change in output has continued to decrease, down from a peak around 4% annually in the 1970s. Globally, there are 1.5 billion head of hogs. This number is a 14% increase from where it was a decade ago and, since 1999, the number of hogs has grown by only 1.6% annually. This growth rate in the number of hogs mirrors the changes to the growth rate of pork production in general. Although still growing there has been a steady decline in the rate of increase of the world´s herd size for over 40 years, from a peak of 4% annually in the 1970s to the current rate.
280  David J. Howden
Commodities, the Decade Ahead  281 Yields have been mostly stagnant over longer periods. Over the past decade pork yields have increased by 2.1%, from 79.7 kilograms per animal to 81.4. Indeed, since 1999 yields have actually decreased by 0.1% annually. In general, the longterm decrease in yields has been in place since the mid1990. Yields have slowly picked up over the last decade, though it must still be noted that the rate of change continues to be near zero and no quick turnaround seems likely. Of the world´s 1.5 billion hogs, nearly half reside in China. The European Union and the United States make up another quarter of the global passel. Lean hogs trade on the Chicago Mercantile Exchange. The CME lean hogs (HE) cash contract returned 35.5% to the investor over the past year. Futures trade in lots of 40,000 pounds and are quoted in U.S. cents per pound.
of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that the price of hogs will breakeven by June 2025 with a 99% probability, and that there is a 45% chance that the commodity´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast the price of hogs to increase by 4.8% annually until June 2030 with a forecast range between 3.5 and 5.2%. This model explains 34% of the commodity´s 10year returns since June 1990. As such, there is a 99% probability that lean hogs will breakeven over the coming decade, and only a 1% chance that it will yield a return greater than 10%.
Lean Hogs: Forecast Summary Current Price FairValue Price Relative Valuation, σ
49 80 2.1
Cycle Forecast Bottoming Forecast Trend Trend Start Date May19 Expected Trend End Date Jul23 14 Expected Real Return Remaining, % 5 Expected Real Return Remaining, annualized % 5Year Forecast 5Year Annual Forecast Return, % 9.5 5Year Forecast Range, % (9.1, 10.1) 2 0.60 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
99 45
10Year Forecast
The Bottom Line Lean hogs closed June 2020 at a price of $0.49 per pound. Based on historical valuations dating to January 1858 (1,950 months) I estimate the fairvalue price of the commodity to be $0.80, implying an undervaluation of 2.1 standard deviations. This indicates that it is priced more cheaply today than 98% of all previous months. Analysis of the commodity´s price cycles since 1900 points to the nearing of the bottom of the bear market that started in May 2019. Historically, the median bear market in lean hogs has lasted for 4.3 years and decreased its price by 59% in real terms. Following this pattern, the current bear market phase should be completed in July 2023 after an additional 14% loss in the commodity´s inflationadjusted price. Over the coming 5year period, I forecast the price of lean hogs to increase by 9.5% annually, with a forecast range between 9.1 and 10.1%. The forecast model explains 60%
10Year Annual Forecast Return, % 4.8 10Year Forecast Range, % (3.5, 5.2) 0.34 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 1
282  David J. Howden
Historical Analysis Since June 1990, the nominal price of lean hogs has decreased from $0.58 per pound to the current close of $0.49 for an annual return of 0.6%. The alltime nominal high for the commodity came in June 2014 at a price of $1.33. In real, inflationadjusted terms the commodity´s price has mostly fallen throughout its history. The real high in lean hogs was in July 1973, with its subsequent low forming in August 2002. As of June 2020, the commodity´s price was lower than 94% of all prior monthly closing prices in real terms. Over longer periods, the price of lean hogs has failed to keep pace with general price inflation, resulting in a real yield of around negative 2% for most of the last 120 years. Nominal returns have hovered around zero to 1% for most of the commodity´s history, with real returns averaging 2.0% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 3.5% and resulted by buying hogs in December 1932 and holding it until today. Still, since inflation over that period also averaged 3.5%, the investor earned a real annual return of zero. More recently the commodity´s price has been in a bear market since March 2019. From that month´s high of $0.89 a collapse of 45% has ensued. The June 2020 bottom of $0.49 looks to be near the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  283 The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the fourteen completed bull markets in lean hogs has started from an undervalued position, with a median value of 1.6 standard deviations below the longterm mean. (With the exception of the 197475 advance that started from a fairlyvalued level.) From these undervalued starting positions, the median bull market increased its relative valuation by +3.4 standard deviations. Lean Hogs: Historical Cycle Summary Declines Date
Price
Advances Real Start Rel. Change, % Val, σ
Start
End
Start
End
Jul02
Jan08
8
4
46
2.8
Mar10 Dec15
11
7
39
3.0
Sep17 Dec21
18
6
73
2.1
Mar25 Dec32
13
3
75
0.1
Aug37 Mar40
11
5
57
0.6
Oct47 Dec55
26
9
70
0.5
Jun58 Dec59
21
10
52
0.4
Feb66 Oct70
26
16
49
1.0
Jul73 May74
56
29
54
5.0
Sep75 Nov94
64
34
80
3.4
Apr97 Dec98
84
33
62
2.0
Apr00 Aug02
77
31
61
1.7
Mar05 Aug09
79
48
45
2.4
Jun14
Sep16
133
44
68
3.8
Mar19 Jun20
89
49
45
0.4
Date Start
End
Price
Real Start Rel. Change, % Val, σ
Start
End
Jan08 Mar10
4
11
106
0.9
Dec15 Sep17
7
18
114
1.3
Dec21 Mar25
6
13
104
2.7
Dec32 Aug37
3
11
310
2.2
Mar40 Oct47
5
26
233
1.3
Dec55 Jun58
9
21
112
2.2
Dec59 Feb66
10
26
129
1.8
Oct70
Jul73
16
56
209
1.3
May74 Sep75
29
64
99
0.1
Nov94 Apr97
34
84
129
1.8
Dec98 Apr00
33
77
123
1.9
Aug02 Mar05
31
79
138
2.5
Aug09 Jun14
48
133
150
1.4
Sep16 Mar19
44
89
92
0.9
Current Bear Market Forecast End Date Relative Valuation Price Real Decline, % Change in Rel. Val., σ
Since 1900 the commodity has gone through fourteen complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the commodity´s price increase by 126% in real terms, before being corrected by a median decline of 59%. The median bull market has lasted for twoandahalf years, and its subsequent correction has taken just over four years to complete.
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 19.2 80 5.0 5.2
Median 4.3 59 2.0 3.9
Jul23 3.5 36 59 3.9 Min. 0.8 39 0.4 1.4
Max. 7.6 310 0.1 6.3
Median 2.5 126 1.6 3.4
Min. 1.3 92 2.7 1.3
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
Similarly, each of the commodity´s fourteen completed bear markets has started from an overvalued position, with a median value of +2.0 standard deviations above the longterm mean. (Except for the decline of 195859 which started from a fairlyvalued level.)
284  David J. Howden Over the course of each bear market lean hogs continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.9 standard deviations. The current phase is the bear market decline that started in May 2019. From the starting price of $0.89 the commodity´s price has fallen by 45% in real terms. This decline is not far from the median decline of 59% over all recorded bear markets. The decline´s starting relative valuation of +0.4 standard deviations was also very weak relative to the median bear market starting relative valuation of +2.0 standard deviations. At the June 2020 low of $0.49 the commodity was 2.1 standard deviations undervalued, more extreme than the median starting valuation to a bull market advance. The loss of 2.5 standard deviations of valuation between 2019 and 2020 is quite weak compared with the median change in the measure during correction phases (3.9 standard deviations). In fact, it is the weakest bearmarket valuation swing since 196670. As such, the balance of cycle evidence points to the bear market that started in March 2019 as still in force, though nearing its bottom. If a bear market that started in March 2019 is still ongoing, what can we expect the future to hold? The median bear market in hogs has lasted for just over four years and lost 59% in real terms. The weakest decline, during 191015, lost 39% in real terms. As such, I expect the current cycle to lose an additional 14% in real terms before finishing its cycle. In terms of duration, the median bear market has lasted 4.3 years. If the present bear market matches this median length of time it will be complete in July 2023.
More dependable than forecasts of price movements are changes to relative valuation. Over its bear markets to date, hogs have decreased their valuation within a relatively narrow band of 3.8 standard deviations (the weakest decline decreased its valuation by 1.4 and the strongest lost 5.2 standard deviations). At the June 2020 low hogs have lost
Commodities, the Decade Ahead  285 2.5 standard deviations over the bear market, implying further downside potential. The June 2020 undervaluation of 2.1 standard deviations made the commodity more undervalued than 98% of all previous months. This is the fourth most undervalued the commodity has ever been, beaten only by the bear market bottoms in 1921, 1932, 1955, and 2002. That fact notwithstanding, the current decline has lost less valuation than the median bear market, and I forecast hogs to be trading at a price which is 3.5 standard deviations undervalued relative to its longterm average by the time the current decline is over. In sum, cycle analysis points to lean hogs trading at $0.36 by July 2023, a price that is 3.5 standard deviations undervalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like.
We can minimize these doubts by choosing a specific duration to provide estimates
286  David J. Howden of the returns by taking recourse in the large number of similar periods in the past. The price history for lean hogs starts in January 1858. This means that to date there have been 1,890 5year holding periods and 1,818 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of lean hogs is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of lean hogs over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of lean hogs as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 9.5% annual gain in lean hogs over the coming 5year period. The forecast range is also strictly positive, ranging from 9.1 to 10.1%. The model explains 60% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of lean hogs will breakeven by June 2025 with a 99% probability, and that the return will exceed 10% with a 45% probability.
Commodities, the Decade Ahead  287 Over the next ten years, I expect the price of lean hogs to increase by 4.8% annually. The forecast range is clustered around this level, ranging from 3.5 to 5.2%. The model explains 34% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that lean hogs will breakeven by June 2030 with a probability of 99%, and that there is only a 1% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Lean hog´s relative valuation of 2.1 standard deviations below its longterm mean is significantly more undervalued than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, lean hogs are the most undervalued commodity of the group. I forecast that the commodity will yield an annual return of 9.5% over the coming five years, and 5.8% over the coming decade. This fiveyear return is higher than the average commodity´s but is somewhat lower over ten years (7.6% and 5.9%). Consequently, lean hogs rank 17th and 27th out of 43 commodities for the 5 and 10year return forecasts.
Lean Hogs Forecast return rankings, out of 43 commodities Relative Valuation st
1 Lean Hogs 43 Commodity Avg.
2.1 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year nd
9.5 7.6
4.8 5.9
45 39
1 22
17
27
18
32
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 45% probability that lean hogs can achieve this return by June 2025 and only 1% by June 2030, ranking the meat 18th and 32nd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that lean hogs will offer comparable performance to the average commodity over the next five years, though lower over the
288  David J. Howden longer tenyear period.
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the meat is in its current price and valuation cycle. The evidence from the price and valuation cycles in hogs since 1900 points to a continued decline in the meat´s price that will end in July 2023. At a price of $0.36 by that date, hogs will have declined further from their March 2019 low in a manner consistent with the other fourteen declines since 1900. Over this time, the relative valuation of hogs should also decrease from its current undervalued position of 2.1 standard deviations, to end this bear market correction undervalued by 3.5 standard deviations. Analysis of hog´s longerterm price behavior points to somewhat higher prices five years from now, followed by a gentle continuation of these gains going out to 2030. These longerterm forecasts imply a sharp rally after the current bear market completes, followed by continued advance taking the meat back to its 2019 highs. By June 2025, I forecast hogs to be trading at $0.77 per pound, and $0.78 by June 2030. The forecast models for
Commodities, the Decade Ahead  289 these longerterm projections are reasonably robust, with 60% of the meat´s 5year returns and 34% of its 10year returns explained since June 1990. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying hogs today and selling them at any date over the coming decade. For example, an expected price of $0.77 in June 2025 implies an annual rate of return of 9.5% over the next five years if the investor buys hogs today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
In the case of hogs, cycle analysis predicts the continuation of its present decline, and the period valuation models forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 8.5% by buying hogs. This expected return increases to 5.2% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, hogs rank 40th and 31st out of the 43 commodities. This implies that hogs should yield a far inferior return over the coming five years than the median commodity, though over the next decade its return should be comparable to the average. Taking the average of its rankings for these expected returns, lean hogs rank 32nd out of the 43 commodities.
290  David J. Howden
Commodities, the Decade Ahead  291
Live Cattle Cattle are the most common type of large domesticated animals. They are commonly raised as livestock for meat, hides, and, less commonly, dung. “Live” cattle refer to those that have reached the necessary weight for slaughter (approximately 1,250 pounds or 550 kilograms). The United States accounts for onefifth of global beef production and, along with Brazil and the European Union, accounts for nearly half of global output. Beef consumption is traditionally a habit in the developed world, though in recent years China has increased demand and is now the world´s second largest consumer.
Global beef production reached 67 million tons in 2019, a 13% increase over the previous decade. This increase came largely as a result of expanded production from the developing world as increased demand has spurred on production. The United States increased production by 10% since 2009 for an additional 0.9 million tons of beef annually. The next two largest producers, Brazil and the European Union, saw very little change in their output levels. The rest of the world, in contrast, produced over 4 million tons of additional beef in 2018 compared to the decade prior, explaining the majority of the production increase. The United States remains the world´s top beef producer, a position it has held every year since records begin in 1961 (except 1991 when the European Union eked it out). Since 1999 world output has increased at an annual rate of 1.4%. This change in output has held fairly constant since the mid1990s in the 11.5% range.
292  David J. Howden
Commodities, the Decade Ahead  293 Globally, there are 302 million head of beef cattle. This number is approximately the same as there was a decade ago and, since 1999, the number of beef cattle has grown by only 0.6% annually. The growth rate of global beef herds has trended near 0.5% annually since the mid1990s. Increasing yields since the mid1990s have added to these gradually increasing beef herds and contributed to total supply growth. Globally, beef cattle yield an average 223 kg of meat to the animal. Yields are not appreciably higher than they were a decade ago, and since 1999 they have increased by only 0.5% annually. Since 2008 there has been a turnaround in beef productivity with yields increasing at a faster rate. While productivity growth slowed for most of the 1990s and early 2000s, since 2008 it has increased by over 0.3 percentage points, from 0.2 to 0.5% annually. The Chicago Mercantile Exchange launched live cattle contracts in 1964. The LME live cattle (LE) cash contract returned 16.2% to the investor over the past year. Futures trade in lots of 50,000 pounds and are quoted in U.S. cents per pound.
The Bottom Line Live cattle closed June 2020 at a price of $0.92 per pound. Based on historical valuations dating to January 1858 (1,950 months) I estimate the fairvalue price of the commodity to be $1.22, implying an undervaluation of 1.6 standard deviations. This indicates that it is priced more cheaply today than 95% of all previous months. Analysis of the commodity´s price cycles since 1900 points to the start of a new secular bull market. The June 2020 low of $0.92 looks to be a longterm bottom. Historically, the median bull market in live cattle has lasted for 5.8 years and increased its price by 71% in real terms. Following this pattern, the current bull market phase should be completed in April 2026 after an additional 71% gain in the commodity´s inflationadjusted price.
Over the coming 5year period, I forecast the price of live cattle to increase by 8.3% annually, with a forecast range between 6.8 and 10.4%. The forecast model explains 73% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that live cattle´s price will breakeven by June 2025 with a 99% probability, and that there is a 26% chance that the commodity´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast live cattle´s price to increase by 5.0% annually until June 2030 with a forecast range between 3.9 and 6.6%. This model explains 58% of the commodity´s 10year returns since June 1990. As such, there is a 99% probability that live cattle will breakeven over the coming decade, and a less than 1% chance that it will yield a return greater than 10%.
Live Cattle: Forecast Summary 92 122 1.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Jun20 Apr26 71 10
5Year Forecast 5Year Annual Forecast Return, % 8.3 5Year Forecast Range, % (6.8, 10.4) 2 0.73 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
99 26
10Year Forecast 10Year Annual Forecast Return, % 5.0 10Year Forecast Range, % (3.9, 6.6) 0.58 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 0, % Probability 5Year Forecast Return > 10, %
The Bottom Line Lumber closed June 2020 at a price of $431 per MBFM. Based on historical valuations dating to January 1890 (1,566 months) I estimate the fairvalue price of the commodity to be $317, implying an overvaluation of +1.4 standard deviations. This indicates that it is priced more cheaply today than only 9% of all previous months. This overvaluation notwithstanding, analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The March 2020 low of $279 looks to be a longterm bottom. Historically, the median bull market in lumber has lasted for three years and increased its price by 89% in real terms. Following this pattern, the current bull market phase should be completed in March 2023 after an additional 33% gain in lumber´s inflationadjusted price. Over the coming 5year period, I forecast the price of lumber to decrease by 6.4%
9 0, % Probability 10Year Forecast Price Return > 10, %
13 0
306  David J. Howden
Historical Analysis Since June 1990, the nominal price of lumber has increased from $205 per thousand board feet to the current close of $432 for an annual return of 2.5%. The alltime nominal high for the metal came in May 2018 at a price of $597. In real, inflationadjusted terms lumber´s price has mostly fallen over the past fifty years. Lumber´s real high was in February 1973, with its subsequent low forming in February 2009. As of June 2020, its price was lower than 52% of all prior monthly closing prices in real terms. Over longer periods, lumber´s price has just kept pace with general price inflation, resulting in a real yield of around zero for most of the 20th century. Nominal returns have hovered around 3% for most of the commodity´s history, with real returns averaging 0.0% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 10.0% and resulted by buying lumber in February 2009 and holding it until today. Since inflation over that period averaged 1.7%, the investor would have earned a real return of 8.3% per year. More recently lumber´s price has been in a bear market since May 2018. From that month´s high of $597 a collapse of 55% ensued. The March 2020 bottom of $279 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  307 started from an undervalued position, with a median value of 1.9 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.3 standard deviations. Similarly, each of lumber´s thirteen completed bear markets has started from an overvalued position, with a median value of +1.5 standard deviations above the longterm mean. Over the course of each bear market lumber continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.5 standard deviations. Lumber: Historical Cycle Summary Declines Date Start End Mar20 Aug21
Price Start End
Advances Real Start Rel. Change, % Val, σ
39
16
55
3.5
Apr23 Aug32
24
11
44
1.3
Sep50 Feb61
77
67
29
1.8
Mar69 Jun70
125
74
45
1.0
Mar73 Sep74
180
100
52
1.1
Aug79 Apr82
277
127
64
1.8
May83 Aug84
248
121
54
0.7
Aug87 Nov90
215
153
39
0.0
Dec93 May95
479
241
52
4.0
Feb96 Feb01
425
202
57
2.3
Feb05 Feb09
419
147
68
1.5
Mar13 Sep15
391
229
43
0.8
May18 Mar20
597
279
55
3.4
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Aug21 Apr23
16
24
59
2.6
Aug32 Sep50
11
77
292
1.9
Feb61 Mar69
67
125
55
1.9
Jun70 Mar73
74
180
119
2.6
Sep74 Aug79
100
277
89
2.4
Apr82 May83
127
248
86
0.9
Aug84 Aug87
121
215
63
2.4
Nov90 Dec93
153
479
187
1.6
May95 Feb96
241
425
69
0.3
Feb01 Feb05
202
419
89
1.2
Feb09 Mar13
147
391
142
2.1
Sep15 May18
229
597
148
1.1
Mar20 Jun20
279
432
56
0.6
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Since 1900 the soft has gone through twelve complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen lumber´s price increase by 89% in real terms, before being corrected by a median decline of 52%. The median bull market has lasted for three years, and its subsequent correction has taken twoandahalf years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the twelve completed bull markets in lumber has
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 10.4 68 4.0 6.1
Median 2.5 52 1.5 3.5
Min. 1.3 29 0.0 1.6
Max. 18.1 292 0.3 5.6
Median 3.0 89 1.9 3.3
Min. 0.8 55 2.6 1.6
Mar23 2.7 526 89 3.3
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in May 2018. From the starting price of $597 the commodity´s price fell by 55% in real terms. This decline is on par with the median decline of 52% over all recorded lumber bear markets. The decline´s starting relative valuation of +3.4 standard deviations
308  David J. Howden was far higher than the median bear market starting relative valuation of +1.5 standard deviations. At the recent March 2020 low of $279 lumber was –0.6 standard deviations undervalued. This is quite a mild undervaluation compared with the median starting valuation for a bull market advance (1.9). However, during its bear market of 201820 the commodity lost 4.0 standard deviations of valuation, which is a little more than the median decline (a loss of 3.5 standard deviations). As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in lumber has lasted for three years and gained 89% in real terms. The weakest advance, during 196169, gained 55% in real terms. Since April 2020, lumber has already gained 56%. As such, I expect the current cycle to gain an additional 33% in real terms by March 2023. This implies an expected annual return of 11% by the time the present bull market reaches completion.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, lumber has increased its valuation within a relatively narrow band of +4.0 standard deviations (the weakest advance increased its valuation by +1.6 and the strongest increased by +5.6 standard deviations). In other words, never in the 120year price history under examination has lumber failed to increase its valuation by less than +1.6 standard deviations over its bull market. Since the March 2020 low the commodity´s relative valuation has increased by +2.0 standard deviations, implying some upside potential, although the balance of evidence suggests that the advance in lumber is already well underway.
Commodities, the Decade Ahead  309 The March 2020 undervaluation of 0.6 standard deviations made the commodity more undervalued than 73% of all previous months. By the time the current bull market reaches its end, I expect lumber to be trading at a price which is +2.7 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to lumber trading at $526 by March 2023, a price that is +2.7 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for lumber starts in January 1890. This means that to date there have been 1,506 5year holding periods and 1,446 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of lumber is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of lumber over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of lumber as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 6.4% annual loss in lumber over the coming 5year period. The forecast range is also strictly negative, ranging from 6.2 to 6.6%. The model explains 53% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of lumber will breakeven by June 2025 with a 9% probability, and that the return will exceed 10% with a less than 1% probability.
310  David J. Howden
Commodities, the Decade Ahead  311
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Lumber´s relative valuation of +1.4 standard deviations above its longterm mean is far higher than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly overvalued. As such, lumber is the 40th most undervalued commodity of the group. I forecast that the commodity will yield an annual loss of 6.4% over the coming five years, and 2.6% over the coming decade. Both returns are far lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, lumber ranks 41st out of 43 commodities for both the 5 and 10year return forecasts.
Lumber Forecast return rankings, out of 43 commodities Over the next ten years, I expect the price of lumber to decrease by 2.6% annually. The forecast range is clustered around this level, ranging from 2.5 to 2.7%. The model explains 64% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that lumber will breakeven by June 2030 with a probability of 13%, and that there is virtually no chance that its return will exceed 10% over this period.
Relative Valuation th
40 Lumber 43 Commodity Avg.
+1.4 0.7
Forecast returns: 5Year st
41
6.4 7.6
Probability that return exceeds 10%:
10Year st
41
2.6 5.9
5Year st
10Year th
41
35
0 39
0 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is virtually no chance of lumber achieving this return over either time period, ranking it last out of the 43 markets for both probabilities. Given this evidence, it is highly likely that lumber will significantly underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where lumber is in its current price and valuation cycle. The evidence from lumber´s price and valuation cycles since 1900 points to a probable advance in its price that will end in March 2023. At a high of $526 by that date, lumber will have advanced from its March 2020 low in a manner consistent with the other twelve advances since 1900. Over this time, lumber´s relative valuation should also increase from its current overvalued position of +1.4 standard deviations, to end this bull market rally even more overvalued at +2.7 standard deviations.
312  David J. Howden
Commodities, the Decade Ahead  313 models also forecast price declines over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 7.5% by buying lumber. This expected return decreases to a loss of 2.9% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, lumber ranks 33rd and 41st out of the 43 commodities. This implies that it should yield far inferior returns over both the coming five and ten years than the average commodity. Taking the average of its rankings for these expected returns, lumber ranks 40th out of the 43 commodities.
Lumber Expected return rankings, out of 43 commodities Relative Valuation th
40 Analysis of lumber´s longerterm price behavior points to somewhat muted prices five years from now, at least relative to this forecast cycle high, followed by a continued advance going out to 2030. These longerterm forecasts imply a sharp collapse after the current bull market completes, followed by a period of sideways trending prices near the recent March 2020 lows. By June 2025, I forecast lumber to be trading at $309 per MBFM, and $332 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 53% of the commodity´s 5year returns and 64% of its 10year returns explained since June 1990. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying lumber today and selling it at any date over the coming decade. For example, an expected price of $309 in June 2025 implies an annual rate of return of 6.4% over the next five years if the investor buys lumber today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of lumber, cycle analysis predicts a swift appreciation peaking in March 2023, and the period valuation
Lumber 43 Commodity Median
+1.4 0.8
Expected average returns: 5Year rd
33
7.5 21.2
10Year st
41
2.9 8.1
Overall Rank th
40
314  David J. Howden
Commodities, the Decade Ahead  315
Milk Milk is the main source of nutrition for infants, as well as the primary product produced by the dairy industry. Less commonly, milk is used by the cosmetic industry as a hair and skin treatment. Dairy farming makes use of, in order of importance, cattle, buffalo, goats and sheep. In this report I focus on cow milk as it is the primary type used in the United States and it also comprises the majority of milk production. The European Union is the world´s largest cow milk producer and, along with the United States and China, accounts for over half of global output. India is the world´s largest consumer, though the majority of its milk comes from buffalo.
Milk* European Union United States China Brazil India Rest of World
Production
Consumption
(% World)
(% World)
24 14 13 5 5 39
India European Union United States China Brazil Rest of World
28 25 14 5 5 23
*
Production figures are milk produced from cattle, consumption considers all animal milk
Source: Food and Agriculture Organization of the United Nations
Global cow milk output reached 331 million tons in 2019, a 17% increase over the previous decade. This increase was distributed evenly across most countries, although China has ramped up production at a faster rate than most, albeit from a smaller base. China today produces 40 million additional tons annually compared to one decade ago, an 80% increase. The European Union remains the world´s top producer of cow´s milk, a position it has held since records begin in 1961. Since 1999 world output has increased at an annual rate of 1.8%.
316  David J. Howden
Commodities, the Decade Ahead  317 Globally, there are 265 million head of dairy cattle. This number is 5% more than there was a decade ago and, since 1999, the number of dairy cattle in the world has grown by 1.0% annually. More recently, however, this number peaked (in 2016) and since has steadily declined. Increasing yields have contributed to total supply growth. Globally, dairy cattle yield 2.6 metric tons of milk annually. Yields are 10.5 % higher than they were a decade ago, and since 1999 they have increased by only 0.9% annually. Since the early 1990s the rate of change of annual yields has steadily increased and gives no sign of abating in the near future. Class III milk, employed in the production of cheese, is traded on the Chicago Mercantile Exchange. (Class I refers to fluid milk sold to drink.) The CME class III milk (DA) cash contract returned 37.4% to the investor over the past year. Futures trade in lots of 200,000 pounds (2,000 hundredweight) and are quoted in U.S. dollars per hundredweight.
annually, with a forecast range between 4.5 and 6.4%. The forecast model explains 60% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that milk´s price will breakeven by June 2025 with only a 9% probability, and that there is virtually no chance that the commodity´s return will be over 10% by that date. The coming decade should see improved, though still negative returns. I forecast milk´s price to decrease by 1.6% annually by June 2030. This model explains 48% of the commodity´s 10year returns since June 1990. As such, there is only a 20% probability that milk will breakeven over the coming decade, and virtually no chance that it will yield a return greater than 10%.
Milk: Forecast Summary 22 17 +1.7
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Topping Apr20 Nov23 
5Year Forecast 5Year Annual Forecast Return, % 5.2 5Year Forecast Range, % (4.5, 6.4) 2 0.60 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
The Bottom Line Milk closed June 2020 at a price of $22.35 per hundredweight. Based on historical valuations dating to January 1890 (1,566 months) I estimate the fairvalue price of the commodity to be $17.05, implying an overvaluation of +1.7 standard deviations. This indicates that it is priced more cheaply today than only 5% of all previous months. Analysis of the commodity´s price cycles since 1900 points to the topping of a secular bull market. The April 2020 low of $12.44 looks to be a longterm bottom and the recent June 2020 high of $22.35 meets all the targets for the completion of a bull market with the exception of its short duration. The months ahead should verify this peak and usher in a multiyear decline. Over the coming 5year period, I forecast the price of milk to decrease by 5.2%
9 0
10Year Forecast 10Year Annual Forecast Return, % 1.6 10Year Forecast Range, % (1.6, 1.6) 2 0.48 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
20 0
318  David J. Howden
Historical Analysis Since June 1990, the nominal price of milk has increased from $12.20 per hundredweight to the current close of $22.40 for an annual return of 2.0%. The alltime nominal high for the commodity came in September 2014 at a price of $24.06. In real, inflationadjusted terms the commodity´s price was mostly flat until the mid1970s, at which point it began to fall. Milk´s real high was in October 1946, with its subsequent low forming in January 2009. As of June 2020, the commodity´s price was lower than 83% of all prior monthly closing prices in real terms. Over longer periods, milk´s price has failed to keep pace with general price inflation, resulting in a real yield of around zero to negative 1% for most of the 20 th century. Nominal returns have hovered around 3% for most of the commodity´s history, with real returns averaging 0.3% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 7.8% and resulted by buying milk in January 2009 and holding it until today. Since inflation over that period averaged 1.5%, the investor would have earned a real return of 6.3% per year. More recently the commodity´s price has been in a bull market since April 2020. From that month´s low of $12.44 an advance of 78% has ensued. The June 2020 top of $22.35 looks to be the nearing the top of a longterm secular advance which should usher in a multiyear correction.
Commodities, the Decade Ahead  319 two years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the ten completed bull markets in milk that the commodity´s relative valuation can be calculated for has started from an undervalued position, with a median value of 1.7 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.3 standard deviations. Similarly, each of the commodity´s eleven completed bear markets with available relative valuation data has started from an overvalued position, with a median value of +1.3 standard deviations above the longterm mean. Over the course of each bear market milk continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.3 standard deviations. Milk (Class III): Historical Cycle Summary Declines
Advances
Date Start End Jan18 Aug22
Price Start End 2.61
1.58
49
n.a.
Nov30 Mar33
2.50
1.28
34
0.7
Nov36 Apr39
2.18
1.29
40
1.1
Oct46 May65
3.89
3.44
42
1.0
Feb74
Jul95
7.80
10.57
58
4.2
Aug96 Oct00
18.80
8.90
57
1.4
Aug01 Feb03
15.60
9.00
45
1.0
Apr04 Apr06
19.79
10.86
49
4.0
Jun08
Jan09
20.29
9.45
52
3.1
Sep14 May16
24.06
12.79
47
1.7
Nov19 Apr20
20.36
12.44
38
1.0
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Aug22 Nov30
1.58
2.50
61
1.9
Mar33 Nov36
1.28
2.18
53
1.7
Apr39 Oct46
1.29
3.89
100
2.4
May65 Feb74
3.44
7.80
52
1.1
Aug96
10.57
18.80
72
1.8
Oct00 Aug01
8.90
15.60
72
2.2
Feb03 Apr04
9.00
19.79
116
0.8
Apr06 Jun08
10.86
20.29
73
1.2
Jan09
Sep14
9.45
24.06
126
1.9
May16 Nov19
12.79
20.36
46
1.3
Apr20 Jun20
12.44
22.35
78
1.6
Jul95
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Since 1900 the commodity has gone through ten complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the commodity´s price increase by 72% in real terms, before being corrected by a median decline of 47%. The median bull market has lasted for just under four years, and its subsequent correction has taken about
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 21.4 58 4.2 6.0
Median 2.3 47 1.3 3.3
Min. 0.4 34 0.7 1.8
Max. 8.8 126 0.8 5.3
Median 3.6 72 1.7 3.3
Min. 0.8 46 2.4 2.3
Nov23 1.7 21.37 72 3.3
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in November 2019. From the starting price of $20.36 the commodity´s price fell by 38% in real terms. This decline is close to the median decline of 47% over all
320  David J. Howden recorded milk bear markets. The decline´s starting relative valuation of +.0 standard deviations was also consistent with the median bear market starting relative valuation of +1.3 standard deviations. At the recent April 2020 low of $12.44 the commodity was 1.6 standard deviations undervalued, on par with the median starting valuation to a bull market advance. The loss of 2.6 standard deviations of valuation between 2019 and 2020 was significant, though somewhat weak by historical standards compared with the median change in the measure during correction phases (3.3 standard deviations). The bull market that started in April 2020 looks to be in the late stages of its advance. The median bull market in milk has lasted for nearly four years and gained 72% in real terms. The weakest advance, during 201619, gained 46% in real terms. Since April 2020, the commodity has already gained 78%. Even though the current rally has been quite short at two months, it has already surpassed the median return for a bull market. The greatest bull market return over its 120year history is 116% between 20032004. As such, I expect the current cycle to be in the late stages of its current advance.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, milk has increased its valuation within a relatively narrow band of +3.0 standard deviations (the weakest advance increased its valuation by +2.3 and the strongest increased by +5.3 standard deviations). In other words, never in the 120year price history under examination has milk failed to increase its valuation by less than +2.3 standard deviations over its bull market. Since the April 2020 low the commodity´s relative valuation has increased by +3.3 standard deviations. This is the same as the median bull market change in valuation and reinforces the claim that the current advance is nearing its end. The April 2020 undervaluation of 1.6 standard deviations made the commodity
Commodities, the Decade Ahead  321 more undervalued than 94% of all previous months. By the time the current bull market reaches its end, I expect milk to be trading at a price which is +1.7 standard deviations overvalued relative to its longterm average. This is, incidentally, the current relative valuation at the June 2020 close. In sum, cycle analysis points to milk completing its current bull market trading at $21.37 by November 2023, a price that is +1.7 standard deviations overvalued. Since it has already reached this price and relative valuation, the current rally has satisfied all criteria except duration. As such, milk´s current rally is on its last legs.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like.
We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for milk starts in January 1890. This means that to date there have been
322  David J. Howden 1,506 5year holding periods and 1,446 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of milk is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of milk over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of milk as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 5.2% annual loss in milk over the coming 5year period. The forecast range is also strictly negative, ranging from 4.5 to 6.4%. The model explains 60% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of milk will breakeven by June 2025 with only a 9% probability, and there is virtually no chance that the return will exceed 10%.
Over the next ten years, I expect the price of milk to decrease by 1.6% annually. The model explains 48% of the variance in the commodity´s 240 10year returns since June
Commodities, the Decade Ahead  323 1990. As such, I estimate that milk will breakeven by June 2030 with a probability of 20%, and that there is no chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future.
Milk (Class III) Forecast return rankings, out of 43 commodities Relative Valuation rd
43 Milk 43 Commodity Avg.
+1.7 0.7
Forecast returns: 5Year th
40
5.2 7.6
Probability that return exceeds 10%:
10Year th
39
1.6 5.9
5Year st
41
0 39
10Year
35th 0 22
Milk´s relative valuation of +1.7 standard deviations above its longterm mean is significantly higher than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly overvalued. As such, milk is the most overvalued commodity of the group. I forecast that the commodity will yield an annual return of 5.2% over the coming five years, and 1.6% over the coming decade. Both returns are far lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, milk ranks 40th and 39th out of 43 commodities for the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a no chance that milk can achieve this goal over either period, ranking it last out of the 43 markets for both probabilities. Given this evidence, it is highly likely that milk will significantly underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where milk is in its current price and valuation cycle. The evidence from milk´s price and valuation cycles since 1900 suggests that milk´s price should remain relatively stable until its current bull market ends in November 2023. To be consistent with its ten other bull markets since 1900, milk
324  David J. Howden should top at $21.37. At its current close of $22.35 this price target has already been met. Since April 2020 it has also swung by +3.3 standard deviations of value, which is on target for milk´s bull markets. At two months, the current rally is quite short (relative to a median bull market of 3.6 years). As such, the current advance is likely topping and milk´s price should meander at this high level without pushing into significantly higher territory.
Commodities, the Decade Ahead  325 buying milk today and selling it at any date over the coming decade. For example, an expected price of $14.95 in June 2025 implies an annual rate of return of 7.7% over the next five years if the investor buys milk today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of milk, cycle analysis predicts a topping of its current bull market, and afterwards the period valuation models forecast price decreases over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 1.3% by buying milk. This expected return is roughly the same at 2.4% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, milk ranks 39th and 40th out of the 43 commodities. This implies that milk should yield a return far inferior to the median commodity over both the coming five and ten years. Taking the average of its rankings for these expected returns, milk ranks 41st out of the 43 commodities.
Milk (Class III) Expected return rankings, out of 43 commodities Relative Valuation rd
43 Milk (Class III) 43 Commodity Median
Analysis of milk´s longerterm price behavior points to somewhat muted prices five years from now, at least relative to this forecast cycle high, with a continued advance going out to 2030. These longerterm forecasts imply a collapse after the current bull market completes, followed by a rally taking the commodity back to multiyear highs. By June 2025, I forecast milk to be trading at $14.95 per hundredweight, and $19.00 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 60% of its 5year returns and 48% of its 10year returns explained since June 1990. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by
+1.7 0.8
Expected average returns: 5Year th
39
1.3 21.2
10Year th
40
2.4 8.1
Overall Rank st
41
326  David J. Howden
Commodities, the Decade Ahead  327
Natural Gas Natural gas is a naturally occurring hydrocarbon gas, consisting mostly of methane. The nonrenewable gas is used as a source of energy for heating, cooking, and electricity production. It is also widely used in the manufacture of plastics and, increasingly, as a fuel for vehicles. The United States accounts for roughly onequarter of global production and, along with Russia and Iran, accounts for nearly half of worldwide output. Consumption is concentrated in the United States, Europe, and Russia.
Natural Gas Production
Consumption
(% World)
United States Russia Iran Qatar Canada Rest of World
23 17 6 4 4 45
(% World)
United States European Union Russia China Iran Rest of World
22 12 11 8 6 42
Source: BP Statistical Review of World Energy
Global natural gas output reached 385 billion cubic feet per day in 2019, a 36% increase over the previous decade. This increase came largely as a result of expanded production in the United States, where output increased by 35 billion cubic feet per day since 2009 (a 65% increase). Russia and Iran have also seen strong production increases over the past decade, at 27% and 80% (14 and 10 billion cubic feet per day). The United States is the world´s top natural gas supplier, a position it has held since overtaking Russia in 2011. Since 1999 world output has increased at an annual rate of 2.8%.
328  David J. Howden There are approximately 199 trillion cubic meters of natural gas in reserves globally. Over the last decade world reserves have grown by 1.6% annually. Although there is some disagreement as to which countries have the highest reserves, Russia is widely recognized as being the top country at 38 trillion cubic (16% of global reserves). Natural gas is widely distributed throughout the world, with the top five countries accounting for barely half of global reserves. Natural gas on delivery at the Henry Hub in Erath, Louisiana, trades on the New York Mercantile Exchange. The NYMEX natural gas (NG) cash contract returned 24.3% to the investor over the past year. Futures trade in lots of 10,000 MMBtu (million British thermal units – the amount of heat required to raise the temperature of one million pounds of water by one degree Fahrenheit) and are quoted in U.S. dollars per MMBtu.
The Bottom Line Natural gas closed June 2020 at a price of $1.75 per MMBtu. Based on historical valuations dating to December 1930 (1,075 months) I estimate the fairvalue price of the commodity to be $4.33, implying an undervaluation of 1.1 standard deviations. This indicates that it is priced more cheaply today than 87% of all previous months. Analysis of the gas´ price cycles since 1930 points to the start of a new secular bull market. The March 2020 low of $1.64 looks to be a longterm bottom. Historically, the median bull market in natural gas has lasted for twoandahalf years and increased its price by 208% in real terms. Following this pattern, the current bull market phase should be completed in September 2022 after an additional 200% gain in the gas´ inflationadjusted price. Over the coming 5year period, I forecast the price of natural gas to increase by 7.4% annually, with a forecast range between 4.1 and 9.0%. The forecast model explains 44% of the variation in the gas´ 5year returns since June 1990. Consequently, I forecast that natural gas´ price will breakeven by June 2025 with a 78% probability, and that there is a 39% chance that the gas´ return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast natural gas´ price to increase by 2.3% annually until June 2030 with a forecast range between 0.9 and 3.4%. This model explains 77% of the gas´ 10year returns since June 1990. As such, there is a 69% probability that natural gas will breakeven over the coming decade, and a 4% chance that it will yield a return greater than 10%.
Commodities, the Decade Ahead  329
Natural Gas: Forecast Summary 1.75 4.33 1.1
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Mar20 Sep22 200 64
5Year Forecast 5Year Annual Forecast Return, % 7.4 5Year Forecast Range, % (4.1, 9.0) 2 0.44 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
78 39
10Year Forecast 10Year Annual Forecast Return, % 2.3 10Year Forecast Range, % (0.9, 3.4) 2 0.77 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
69 4
Historical Analysis Since June 2020, the nominal price of natural gas has increased from $1.48 per MMBtu to the current close of $1.75 for an annual return of 0.6%. The alltime nominal high for the gas came in September 2005 at a price of $15.00. In real, inflationadjusted terms the gas´ price has gradually increased throughout its history. Natural gas´ real high was in September 2005, with its low forming in December 1946. As of June 2020, the gas´ price was lower than 67% of all prior monthly closing prices in real terms. Over longer periods, natural gas´ price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the 20th century. Nominal returns have hovered around 2% for most of the gas´ history, with real returns averaging 1.5% annually between 1930 and 2010. The highest longterm nominal return
330  David J. Howden the investor could have earned was 5.3% and resulted by buying natural gas in November 1975 and holding it until today. Since inflation over that period averaged 3.5%, the investor would have earned a real return of 1.8% per year. More recently the gas´ price has been in a bear market since November 2018. From that month´s high of $4.62 a collapse of 65% ensued. The March 2020 bottom of $1.64 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  331 The median price decline caused the relative valuation to fall by 2.9 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in November 2018. From the starting price of $4.62 the gas´ price fell by 65% in real terms. This decline is on par with the median decline of 67% over all recorded natural gas bear markets. The decline´s starting relative valuation of 0.3 standard deviations is unusual since it is not only far lower than the starting relative valuation to the median bear market (+1.4) but is mildly undervalued. The change in relative valuation over the course of the bear market was also weak at 0.9 standard deviations against a median value of 2.9. The timing was almost spot on, however, as the decline was completed in 16 months against the median duration of 18 months. Natural Gas (Henry Hub): Historical Cycle Summary Declines Date Start End
Advances Real Start Rel. Change, % Val, σ
Jun71
0.16
0.18
18
2.2
Dec74 Nov75
0.30
0.17
46
0.5
Jan84 Feb92
2.87
1.26
68
1.1
Dec96 Aug98
4.05
1.60
62
0.3
Dec00 Sep01
10.42
1.82
83
2.8
Feb03 Oct03
11.08
3.97
65
2.8
Sep05 Sep06
15.00
3.66
76
3.8
Jun08 Mar12
13.16
1.96
86
1.6
Jan14
Feb16
5.00
1.62
68
0.3
Nov18 Mar20
4.62
1.64
65
0.3
Oct62
Since 1930 the gas has gone through ten complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the gas´ price increase by 208% in real terms, before being corrected by a median decline of 67%. The median bull market has lasted for twoandahalf years, and its subsequent correction has taken oneandahalf years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the ten completed bull markets in natural gas that the with available relative valuation information has started from an undervalued position, with a median value of 1.3 standard deviations below the longterm mean. (The only exception to this is the 200305 advance that started from a slightly overvalued position.) From these undervalued starting positions, the median bull market increased its relative valuation by +2.2 standard deviations. Similarly, each of the gas´ ten completed bear markets with available relative valuation data has started from an overvalued position, with a median value of +1.4 standard deviations above the longterm mean (with the exception of the 197475, 201416 and 201820 bear markets which all started from marginally undervalued positions). Over the course of each bear market natural gas continued to shed valuation as its price fell.
Price Start End
Date Start End Dec46 Oct62
Price Start End 0.05
0.16
127
n.a.
Jun71 Dec74
0.18
0.30
35
1.0
Nov75 Jan84
0.17
2.87
806
2.8
Feb92 Dec96
1.26
4.05
182
1.9
Aug98 Dec00
1.60
10.42
510
1.3
Sep01 Feb03
1.82
11.08
494
1.2
Oct03 Sep05
3.97
15.00
252
0.1
Sep06
Jun08
3.66
13.16
234
0.4
Mar12
Jan14
1.96
5.00
151
1.4
Feb16 Nov18
1.62
4.62
168
1.5
Jun20
1.64
1.75
8
1.2
Mar20
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 8.7 86 3.8 4.2
Median 1.5 67 1.4 2.9
Min. 0.7 18 0.5 0.9
Max. 15.8 806 0.1 4.1
Median 2.5 208 1.3 2.2
Min. 1.4 35 2.8 0.5
Sep22 1.0 5.05 208 2.2
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
At the recent March 2020 low of $1.64 the gas was 1.2 standard deviations undervalued, on par with the median starting valuation to a bull market advance. As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold?
332  David J. Howden The median bull market in natural gas has lasted for twoandahalf years and gained 208% in real terms. The weakest advance, during 197174, gained 35% in real terms. Since March 2020, the gas has already gained 8%. As such, I expect the current cycle to gain an additional 200% in real terms by September 2022. This implies an expected annual return of 64% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, natural gas has increased its valuation within a relatively narrow band of +3.6 standard deviations (the weakest advance increased its valuation by +0.5 and the strongest increased by +4.1 standard deviations). In other words, never in the 90year price history under examination has natural gas failed to increase its valuation by less than +0.5 standard deviations over its bull market. Since the March 2020 low the gas´ relative valuation has increased by +0.1 standard deviations, implying further upside potential.
Commodities, the Decade Ahead  333 The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for natural gas starts in December 1930. This means that to date there have been 955 5year holding periods and 835 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of natural gas is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of natural gas over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run.
The March 2020 undervaluation of 1.1 standard deviations made the commodity more undervalued than 88% of all previous months. By the time the current bull market reaches its end, I expect natural gas to be trading at a price which is +1.0 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to natural gas trading at $5.05 by September 2022, a price that is +1.0 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms.
Both models use the relative valuation of natural gas as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic
334  David J. Howden conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 7.4% annual gain in natural gas over the coming 5year period. The forecast range is also strictly positive, ranging from 4.1 to 9.0%. The model explains 44% of the variation of the 300 5year returns of the fuel since June 1990. Given this explanatory power of the model, I estimate that the price of natural gas will breakeven by June 2025 with a 78% probability, and that the return will exceed 10% with a 39% probability.
Commodities, the Decade Ahead  335 Natural gas´ relative valuation of 1.1 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, natural gas is the 13th most undervalued commodity of the group. I forecast that natural gas will yield an annual return of 7.4% over the coming five years, and 2.3% over the coming decade. Both returns are somewhat lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, natural gas ranks 26th and 37th out of 43 commodities for the 5 and 10year return forecasts.
Natural Gas Forecast return rankings, out of 43 commodities Relative Valuation th
13 Natural Gas 43 Commodity Avg.
Over the next ten years, I expect the price of natural gas to increase by 2.3% annually. The forecast range is clustered around this level, ranging from 0.9 to 3.4%. The model explains 77% of the variance in the fuel´s 240 10year returns since June 1990. As such, I estimate that natural gas will breakeven by June 2030 with a probability of 69%, and that there is a 4% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future.
1.1 0.7
Forecast returns: 5Year th
26
7.4 7.6
Probability that return exceeds 10%:
10Year th
37
2.3 5.9
5Year rd
23
38 39
10Year
28th 4 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 38% probability that natural gas can achieve this return by June 2025 and 4% by June 2030, ranking the gas 23rd and 28th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that natural gas will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the gas is in its current price and valuation cycle. The evidence from natural gas´ price and valuation cycles since 1930 points to a probable surge in the gas´ price that will end in September 2022. At a high of $5.05 by that date, natural gas will have advanced from its March 2020 low in a manner consistent with the other ten advances since 1930. Over this time, natural gas´ relative valuation should also increase from its current undervalued position of 1.1 standard deviations, to end this bull market rally overvalued by +1.0 standard deviations. Analysis of natural gas´ longerterm price behavior points to somewhat muted prices five years from now, at least relative to this forecast cycle high, followed by a slight decline going out to 2030. By June 2025, I forecast natural gas to be trading at $2.50 per MMBtu, and $2.15 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 44% of the grain´s 5year returns and 77% of its 10year returns explained since June 1990. In all cases, the price of natural gas is not expected to fall below its March 2020 low at any time over the coming decade.
336  David J. Howden
Commodities, the Decade Ahead  337 natural gas ranks 12th out of the 43 commodities.
Natural Gas Expected return rankings, out of 43 commodities Relative Valuation th
13 Natural Gas 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying natural gas today and selling it at any date over the coming decade. For example, an expected price of $2.50 in June 2025 implies an annual rate of return of 7.4% over the next five years if the investor buys natural gas today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of natural gas, cycle analysis predicts a swift appreciation peaking in September 2022, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 28.5% by buying natural gas. This expected return falls to 7.3% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, natural gas ranks 13th and 26th out of the 43 commodities. This implies that natural gas should yield a return greater than the median commodity over the next five years, but somewhat less over the coming decade. Taking the average of the gas´ rankings for these expected returns,
1.1 0.8
Expected average returns: 5Year th
13
28.5 21.2
10Year th
26
7.3 8.1
Overall Rank th
12
338  David J. Howden
Commodities, the Decade Ahead  339
Nickel Nickel is a hard, ductile metal used primarily in alloys. The silverywhite metal is highly resistant to corrosion making it ideal for plating other metals, mostly iron and brass. Originally used as far back as 3500 BC, the element of nickel was not isolated chemically until 1751. Approximately twothirds of mined nickel is used in the production of stainless steel. Another 25% is used in various alloys, with the remainder going to more specialty uses. Increasingly the metal has become an important input in rechargeable batteries. Indonesia accounts for onequarter of the world´s supply and, along with the Philippines and Russia, produces over half of global nickel output. China is the number one demander, consuming over half of the globe´s consumption.
Global nickel output reached 2.7 million metric tons in 2019, a 96% increase over the previous decade. This increase came largely as a result of expanded production from Indonesia which has resumed mining to levels last seen before the country´s government banned nickel exports, a law which has since been rolled back (the country´s 294% increase over the decade adds an additional 0.6 million metric tons annually to the world´s supply). Likewise, the Philippines has nearly trebled output (a 252% increase) for an additional 0.3 million metric tons annually. Indonesia and the Philippines have contended for the top spot as the globe´s largest nickel producer since records begin in 1990. Indonesia currently holds the spot, having overtaken the Philippines in 2018. Given current output and growth rates, it is expected to retain this top position for the foreseeable future.
340  David J. Howden
Commodities, the Decade Ahead  341 Recycled scrap remains an important source of nickel augmenting mined production. Recycled nickel accounts for approximately 47% of consumption. Since 1999 world output has increased at an annual rate of 4.3%. There are approximately 89 million metric tons of nickel in reserves globally. Over the last decade world nickel reserves have grown by 2.3% annually. Indonesia maintains the world´s largest nickel reserves at 21 million tons (24% of global reserves). Although just five countries account for 72% of global reserves, the metal is found widely in smaller amounts throughout the world. The United States has negligible reserves (approximately 0.1% of global levels) although the ability to recycle large amounts of nickel compensate for this limitation. The London Metal Exchange launched nickel contracts in 1979. The LME nickel (NI) cash contract returned 1.0% to the investor over the past year. Futures trade in lots of 6 metric tons and are quoted in U.S. dollars per metric ton.
of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that nickel´s price will breakeven by June 2025 with a 75% probability, and that there is a 42% chance that the metal´s return will be over 10% by that date. The coming decade should see even higher returns. I forecast nickel´s price to increase by 9.1% annually until June 2030 with a forecast range between 7.3 and 11.4%. This model explains 72% of the metal´s 10year returns since June 1990. As such, there is a 98% probability that nickel will breakeven over the coming decade, and a 42% chance that it will yield a return greater than 10%.
Nickel: Forecast Summary 12,790 17,705 0.7
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Mar16 Nov17 131 n.a.
5Year Forecast 5Year Annual Forecast Return, % 7.8 5Year Forecast Range, % (6.3, 8.4) 2 0.36 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
75 42
10Year Forecast
The Bottom Line Nickel closed June 2020 at a price of $12,790 per metric ton. Based on historical valuations dating to June 1840 (2,161 months) I estimate the fairvalue price of the commodity to be $17,706, implying an undervaluation of 0.7 standard deviations. This indicates that it is priced more cheaply today than 75% of all previous months. Analysis of the metal´s price cycles since 1900 points to the continuation of the secular bull market that started in March 2016 at the $8,280 low. Historically, the median bull market in nickel has lasted for 1.7 years and increased its price by 174% in real terms. Following this pattern, the current bull market phase is already running long, but should end after an additional 131% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of nickel to increase by 7.8% annually, with a forecast range between 6.3 and 8.4%. The forecast model explains 36%
10Year Annual Forecast Return, % 9.1 10Year Forecast Range, % (7.3, 11.4) 2 0.72 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
98 42
342  David J. Howden
Historical Analysis Since June 1990, the nominal price of nickel has increased from $8,710 per metric ton to the current close of $12,790 for an annual return of 1.3%. The alltime nominal high for the metal came in May 2007 at a price of $50,900. In real, inflationadjusted terms the metal´s price has increased slowly throughout its history, though it has mostly traded between $100 and $1,000 per metric ton. Nickel´s real high was in May 2007, with its low forming in October 1998. As of June 2020, the metal´s price was lower than 85% of all prior monthly closing prices in real terms. Over longer periods, nickel´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 1% for most of the 20th century. Nominal returns have hovered around 2% for most of the metal´s history, with real returns averaging 1.0% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 5.9% and resulted by buying nickel in October 2001 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 3.9% per year. More recently the metal´s price has been in a bull market since March 2016. From that month´s low of $8,280 a rally of 43% has ensued. The June 2020 close of $12,790 looks to be a stop along the way of the longterm secular advance.
Commodities, the Decade Ahead  343 The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the six completed bull markets in nickel with an available relative valuation has started from an undervalued position, with a median value of 1.5 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.1 standard deviations. Similarly, each of the metal´s six completed bear markets with an available relative valuation has started from an overvalued position, with a median value of +1.1 standard deviations above the longterm mean (with the exception of the 199598 bear market which started from a moderately undervalued position). Over the course of each bear market nickel continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.1 standard deviations. Nickel: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Mar80 Oct87 13,808
9,943
50
1.1
18,750
4,012
82
1.0
Oct98 10,015
3,860
65
0.7
Mar00 Oct01 10,240
4,420
58
0.1
May07 Mar09 50,900
9,405
82
6.7
Feb11 Mar16 28,840
8,280
73
2.0
Feb89 Sep93 Jan95
Date Start End Jul48 Mar80
Price Start End 1,175
13,808
258
0.0
Oct87 Feb89
9,943
18,750
79
2.1
Sep93
Jan95
4,012
10,015
141
2.5
Oct98 Mar00
3,860
10,240
154
1.8
Oct01 May07
4,420
50,900
885
1.5
Mar09 Feb11
9,405
28,840
194
0.3
Mar16 Jun20
8,280
12,790
43
1.0
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the metal has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 174% in real terms, before being corrected by a median decline of 69%. The median bull market has lasted for just under two years, and its subsequent correction has taken more than four years to complete.
Max. 7.6 82 6.7 7.0
Median 4.2 69 1.1 3.1
Min. 1.6 50 0.7 1.1
Max. 31.7 885 0.0 8.2
Median 1.7 174 1.5 2.1
Min. 1.3 79 2.5 1.1
Nov17 1.1 22,695 174 2.1
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in February 2011. From the starting price of $28,840 the metal´s price fell by 73% in real terms. This decline is on par with the median decline of 69% over all recorded nickel bear markets. The decline´s starting relative valuation of +2.0 standard deviations was far more extreme than the median bear market starting relative valuation of +1.1 standard deviations. At the March 2016 low of $8,280 the metal was 1.0 standard deviations undervalued, almost on par with the median starting valuation to a bull market advance. The loss of 3.0 standard deviations of valuation between 2011 and 2016 is also consistent with the median change in the measure during correction phases (3.1 standard deviations). As
344  David J. Howden such, the balance of cycle evidence points to the March 2016 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2016 what can we expect the future to hold? The median bull market in nickel has lasted for nearly two years and gained 174% in real terms. The weakest advance, during 198789, gained 79% in real terms. Since March 2016, the metal has already gained 43%. As such, I expect the current cycle to gain an additional 131% in real terms by the time this cycle ends. The current bear market is already running long, having taken over fourandaquarter years to date. The average advance in nickel has been quite quick, and as such the current rally could be already in its later stages. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, nickel has increased its valuation within a band of +7.1 standard deviations (the weakest advance increased its valuation by +1.1 and the strongest increased by +8.2 standard deviations). In other words, never in the 120year price history under examination has nickel failed to increase its valuation by less than +1.1 standard deviations over its bull market. Since the March 2016 low the metal´s relative valuation has increased by +0.3 standard deviations, implying significant upside potential.
The March 2016 undervaluation of 1.0 standard deviations made the commodity more undervalued than 84% of all previous months. By the time the current bull market reaches its end, I expect nickel to be trading at a price which is +1.1 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to nickel trading at $22,695 by the end of the current rally, a price that is +1.1 standard deviations overvalued.
Commodities, the Decade Ahead  345
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for nickel starts in June 1840. This means that to date there have been 2,101 5year holding periods and 2,041 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of nickel is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of nickel over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of nickel as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 7.8% annual gain in nickel over the coming 5year period. The forecast range is also strictly positive, ranging from 6.3 to 8.4%. The model explains 36% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of nickel will breakeven by June 2025 with a 75% probability, and that the return will exceed 10% with a 42% probability.
346  David J. Howden
Commodities, the Decade Ahead  347
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Nickel´s relative valuation of 0.7 standard deviations below its longterm mean is right on the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by the same amount as the average commodity. As such, nickel is the 26th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 7.8% over the coming five years, and 9.1% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, nickel ranks 24th and 11th out of 43 commodities for the 5 and 10year return forecasts.
Over the next ten years, I expect the price of nickel to increase by 9.1% annually. The forecast range is clustered around this level, ranging from 7.3 to 11.4%. The model explains 72% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that nickel will breakeven by June 2030 with a probability of 98%, and that there is a 42% chance that its return will exceed 10% over this period.
Nickel Forecast return rankings, out of 43 commodities Relative Valuation
Nickel 43 Commodity Avg.
Forecast returns:
Probability that return exceeds 10%:
5Year
10Year
5Year
10Year
26th
24th
11th
19th
11th
0.7 0.7
7.8 7.6
9.1 5.9
42 39
42 22
Finally, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 42% probability that nickel can achieve this return over both periods, ranking the metal 19th and 11th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that nickel will yield comparable performance the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where nickel is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1900 suggests that its current bull market should have ended back in November 2017 at a high of $22,695. Since the metal closed June 2020 at a price of $12,790, there is quite a bit of room for the price to advance to complete its current cycle in a manner consistent with the other six advances since 1900.
348  David J. Howden
Commodities, the Decade Ahead  349 Between today and June 2025 the investor can expect a median annual return of 8.5% by buying nickel. This expected return is a little better at 8.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, nickel rank 24th and 10th. This implies that the metal should yield returns about on par with the average commodity over the next five years, and a little better over the coming decade. Taking the average of the metal´s rankings for these expected returns, nickel ranks 25th out of the 43 commodities.
Nickel Expected return rankings, out of 43 commodities Relative Valuation th
26 Nickel 43 Commodity Median
Analysis of nickel´s longerterm price behavior points to a steady price advance out to five years from now, with a continued bull market going out to 2030. By June 2025, I forecast nickel to be trading at $18,579, and $30,569 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 36% of its 5year returns and 72% of its 10year returns explained since June 1990. In all cases, the price of nickel is not expected to fall below its March 2016 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying nickel today and selling them at any date over the coming decade. For example, an expected price of $18,579 in June 2025 implies an annual rate of return of 7.8% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of nickel, cycle analysis predicts a swift appreciation as the current bull market completes itself, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period.
0.7 0.8
Expected average returns: 5Year nd
10Year th
8.5 21.2
8.8 8.1
32
20
Overall Rank th
25
350  David J. Howden
Commodities, the Decade Ahead  351
Oats Oats are one of the most popular cereal grains consumed in the world, typically either crushed or as flour. Less commonly they are used as a food supplement for ruminant animals, and its straw is widely demanded as animal bedding. A small amount of oat production is used to make beer and skin conditioner. The European Union is the world´s largest producer and consumer of the cereal. Together with Russia, it accounts for over half of both global production and consumption.
Global oat output reached 23 million tons in 2018, a 12% decrease over the previous decade. This decrease came largely as the result of an unusually high harvest in 2008 (2 million tons higher than the average over the past decade) and also due to declining European and Russian harvests as production shifts to other crops. Oat output in the European Union has fallen by 14% since 2008 for a 1.2 million ton reduction in its harvest. Likewise, Russian output has fallen by 19% over the same period, for a loss of 1.1 million tons of oats annually. The European Union is the
352  David J. Howden world´s top oat producer, a position it has held since overtaking Russia in 1996. World output has been slowly but steadily decreasing over time, and since 1999 annual supplies have decreased at an annual rate of 0.3%. Globally, there are 10 million hectares of land devoted to oat production. This area is 15% less than there was a decade ago and, since 1999, the area used for oat production in world has decreased by 1.3% annually. This trend of decreasing land use for oat production has been in force since at least 1961 when records begin. Slightly increasing yields have offset these gradually decreasing harvest areas and slowed the rate of decline in overall oat production. Globally, oats yield 2.3 metric tons to the hectare. Yields are not appreciably higher than they were a decade ago, and since 1999 they have increased by 1.1% annually. This increase in yields has steadily increased over the past 30 years, though has been flat around a 1% annual rate for the past decade. World oat stocks ended 2019 at 2.5 million metric tons. Globally there has been an average annual production deficit of 208,000 metric tons over the past decade, leaving stocks 45% lower than in 2009. Global demand has outstripped supply to pare down stocks, and today they are at their lowest level in over 20 years at 11.4% of annual supply. Oat futures trade on the Chicago Board of Trade. The CBOT oat (O) cash contract returned 19.9% to the investor over the past year. Futures trade in lots of 5,000 bushels and are quoted in U.S. dollars per bushel.
The Bottom Line Oats closed June 2020 at a price of $3.58 per bushel. Based on historical valuations dating to January 1890 (1,567 months) I estimate the fairvalue price of the commodity to be $3.38, implying an overvaluation of +0.1 standard deviations. This indicates that it is
Commodities, the Decade Ahead  353 priced more cheaply today than 45% of all previous months. Analysis of the grain´s price cycles since 1900 points to the continuation of the secular bull market that started in August 2016 at the $2.26 low. Historically, the median bull market in oats has lasted for 4.5 years and increased its price by 146% in real terms. Following this pattern, the current bull market phase should be completed in February 2021 after an additional 97% gain in the grain´s inflationadjusted price.
Oats: Forecast Summary 358 338 +0.1
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Aug16 Feb21 97 49
5Year Forecast 5Year Annual Forecast Return, % 2.4 5Year Forecast Range, % (2.1, 2.8) 2 0.54 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
68 7
10Year Forecast 10Year Annual Forecast Return, % 2.7 10Year Forecast Range, % (2.0, 4.1) 2 0.57 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
86 0, % Probability 5Year Forecast Return > 10, %
75 11
10Year Forecast 10Year Annual Forecast Return, % 3.2 10Year Forecast Range, % (2.0, 5.0) 2 0.61 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
87 1
Over the coming 5year period, I forecast the price of orange juice to increase by 3.5% annually, with a forecast range between 3.0 and 4.8%. The forecast model explains 44% of the variation in the juice´s 5year returns since June 1990. Consequently, I forecast that orange juice´s price will breakeven by June 2025 with a 75% probability, and that there is an 11% chance that the juice´s return will be over 10% by that date. The coming decade should see even more subdued returns. I forecast orange juice´s
366  David J. Howden price to increase by 3.2% annually until June 2030 with a forecast range between 2.0 and 5.0%. This model explains 61% of the juice´s 10year returns since June 1990. As such, there is an 87% probability that orange juice will breakeven over the coming decade, and a 1% chance that it will yield a return greater than 10%.
Historical Analysis Since June 2020, the nominal price of orange juice has decreased from $1.75 per pound to the current close of $1.23 for an annual return of 1.2%. The alltime nominal high for the juice came in November 2016 at a price of $2.17. In real, inflationadjusted terms the juice´s price has mostly fallen throughout its history. Orange juice´s real high was in February 1950, with its subsequent low forming in May 2004. As of June 2020, the juice´s price was lower than 89% of all prior monthly closing prices in real terms. Over longer periods, orange juice´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the seventy years. Nominal returns have hovered around 1% for most of the juice´s history, with real returns averaging 1.8% annually between 1947 and 2010. The highest longterm nominal return the investor could have earned was 5.2% and resulted by buying orange juice in December 2008 and holding it until today. Since inflation over that period averaged 1.7%, the investor would have earned a real return of 3.5% per year. More recently the juice´s price was been in a bear market between November 2016 and October 2019. From the 2016 high of $2.17 a collapse of 60% ensued. The October 2019 bottom of $0.94 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  367 Since 1947 the juice has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the juice´s price increase by 120% in real terms, before being corrected by a median decline of 63%. The median bull market has lasted for nearly twoandahalf years, and its subsequent correction has taken almost five years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in orange juice that the commodity´s relative valuation can be calculated for has started from an undervalued position, with a median value of 1.4 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.1 standard deviations. Similarly, each of the juice´s seven completed bear markets that I have relative valuation data for has started from an overvalued position, with a median value of +2.3 standard deviations above the longterm mean. Over the course of each bear market orange juice continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.7 standard deviations.
The most recently completed phase of its cycles was the bear market decline which started in November 2016. From the starting price of $2.17 the juice´s price fell by 60% in real terms. This decline is on par with the median decline of 63% over all recorded
368  David J. Howden orange juice bear markets. The decline´s starting relative valuation of +2.7 standard deviations was also broadly consistent with the median bear market starting relative valuation of +2.3 standard deviations. At the recent October 2019 low of $0.94 the juice was 1.1 standard deviations undervalued, close to the median starting valuation to a bull market advance (1.4). The loss of 3.8 standard deviations of valuation between 2016 and 2019 is somewhat extreme with the median change in the measure during correction phases (2.7 standard deviations). As such, the balance of cycle evidence points to the October 2019 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in October 2019 what can we expect the future to hold? The median bull market in orange juice has lasted for twoandahalf years and gained 120% in real terms. The weakest advance, during 201516 gained 104% in real terms. Since October 2019, the juice has already gained 32%. As such, I expect the current cycle to gain an additional 88% in real terms by February 2024. This implies an expected annual return of 45% by the time the present bull market reaches completion.
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, orange juice has increased its valuation within a relatively narrow band of +3.4 standard deviations (the weakest advance increased its valuation by +1.7 and the strongest increased by +5.1 standard deviations). In other words, never in the 70year price history under examination has orange juice failed to increase its valuation by less than +1.7 standard deviations over its bull market. Since the October 2019 low the juice´s relative valuation has increased by +0.7 standard deviations, implying further upside potential. The October 2019 undervaluation of 1.2 standard deviations made the commodity more undervalued than 87% of all previous months. By the time the current bull market
Commodities, the Decade Ahead  369 reaches its end, I expect orange juice to be trading at a price which is +2.0 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to orange juice trading at $2.06 by March 2022, a price that is +2.0 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for orange juice starts in January 1947. This means that to date there have been 822 5year holding periods and 762 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of orange juice is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of orange juice over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of orange juice as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 3.5% annual gain in orange juice over the coming 5year period. The forecast range is also strictly positive, ranging from 3.0 to 4.8%. The model explains 44% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of orange juice will breakeven by June 2025 with a 75% probability, and that the return will exceed 10% with an 11% probability.
370  David J. Howden
Commodities, the Decade Ahead  371
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Orange juice´s relative valuation of 0.4 standard deviations below its longterm mean is less undervalued than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity undervalued in absolute terms, but not relative to the median commodity. As such, orange juice is the 34th most undervalued commodity of the group. I forecast that the juice will yield an annual return of 3.5% over the coming five years, and 3.2% over the coming decade. Both returns are far lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, orange juice ranks 35th out of 43 commodities for both the 5 and 10year return forecasts.
Over the next ten years, I expect the price of orange juice to increase by 3.2% annually. The forecast range is clustered around this level, ranging from 2.0 to 5.0%. The model explains 61% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that orange juice will breakeven by June 2030 with a probability of 87%, and that there is a 1% chance that its return will exceed 10% over this period.
Orange Juice Forecast return rankings, out of 43 commodities Relative Valuation
Orange Juice 43 Commodity Avg.
Forecast returns:
Probability that return exceeds 10%:
5Year
10Year
5Year
10Year
34th
35th
35th
36th
32nd
0.4 0.7
3.5 7.6
3.2 5.9
11 39
1 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is only a 11% probability that orange juice can achieve this return by June 2025 and 1% by June 2030, ranking it 36th and 32nd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that orange juice will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where orange juice is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1947 points to a probable advance in its price that will end March 2022. At a high of $2.06 by that date, orange juice will have advanced from its October 2019 low in a manner consistent with the other seven advances since 1947.
372  David J. Howden
Commodities, the Decade Ahead  373 Between today and June 2025 the investor can expect a median annual return of 19.0% by buying orange juice. This expected return is greatly reduced at 3.3% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, orange juice ranks 24th over five years, and 35th over the coming decade. This implies that it should yield comparable returns to the median commodity by June 2025, and far low returns by 2030. Taking the average of the beverage´s rankings for these expected returns, orange juice ranks 34th out of the 43 commodities.
Orange Juice Expected return rankings, out of 43 commodities Relative Valuation th
34 Orange Juice 43 Commodity Median
Analysis of orange juice´s longerterm price behavior points to higher prices five and ten years from now, with a bust being completed before 2025. By June 2025, I forecast orange juice to be trading at $1.46, and $1.67 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 44% of its 5year returns and 61% of its 10year returns explained since June 1990. In all cases, the price of the juice is not expected to fall below its October 2019 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying orange juice today and selling it at any date over the coming decade. For example, an expected price of $1.42 in June 2025 implies an annual rate of return of 3.5% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of orange juice, cycle analysis predicts a steady appreciation topping in March 2022, and the period valuation models also forecast price increases, but over longer time periods and at lower levels than this peak. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period.
0.4 0.8
Expected average returns: 5Year th
10Year th
19.0 21.2
3.3 8.1
24
35
Overall Rank th
34
374  David J. Howden
Commodities, the Decade Ahead  375
Palladium Palladium is a rare silverywhite metal belonging to the platinum group (along with iridium, osmium, platinum, rhodium, and ruthenium). Industrial uses largely center on the automotive industry (primarily catalytic converters), although jewelry, dentistry, watch making, and electrical components are also important sources of demand. Russia accounts for nearly half of global production of the metal and, along with South Africa, produces almost 80% of the world´s supply.
Palladium Production
Consumption
(% World)
Russia South Africa Canada United States Zimbabwe Rest of World
41 38 10 6 6 0
(% World)
N. America Europe China Japan
27 23 22 12
Rest of World
15
Sources: USGS, 2020; Statista, 2020
Global palladium output reached 210,000 kgs in 2019, an 8% increase over the previous decade. This increase came largely as a result of expanded production from China which mined almost no palladium twenty years ago. Of the large producers, Canada has increased output the most at 18% since 2009 (an extra 13 thousand kilograms of annual production). Russia and South Africa have vied for the top spot in the production table since records begin in 1998. Despite being close in annual output, Russia continues to be the world´s largest producer, a position it has held every year but two (2015 and 2017) since 1998. Recycled palladium remains an important source of palladium augmenting mined production. Approximately 30% of the world´s palladium supply comes from recycled sources, with catalytic converters being the primary source. Since 1999 world output has increased at an annual rate of 1.4%.
376  David J. Howden
Commodities, the Decade Ahead  377 There are approximately 6.9 million kilograms of platinum group metals (PGM: mostly platinum and palladium, with smaller amounts of iridium, osmium, rhodium, and ruthenium) in reserves globally. Over the last decade world PGM reserves have shrunk by 0.3% annually as new sources have proven difficult to find. Nearly all of the world´s reserves are located in South Africa (91%). The top five producing countries (Canada, Russia, South Africa, the United States, and Zimbabwe) account for all the world´s reserves. At current reserve and mining levels, platinum group reserves will be halved by 2142. The metal is traded on the New York Mercantile Exchange, and also on the London Metal Exchange. The NYMEX palladium (PA) cash contract returned 25.6% to the investor over the past year. Futures trade in lots of 100 troy ounces and are quoted in U.S. dollars per troy ounce.
annually, with a forecast range between 10.5 and 6.2%. The forecast model explains 57% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that palladium´s price will breakeven by June 2025 with a 20% probability, and that there is only a 3% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat more positive returns. I forecast palladium´s price to increase by 2.3% annually until June 2030 with a forecast range between 1.4 and 2.9%. This model explains 51% of the metal´s 10year returns since June 1990. As such, there is a 68% probability that palladium will breakeven over the coming decade, and 7% chance that it will yield a return greater than 10%.
Palladium: Forecast Summary 1,932 972 +1.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Down Feb20 Mar22 46 30
5Year Forecast 5Year Annual Forecast Return, % 8.0 5Year Forecast Range, % (6.2, 10.5) 2 0.57 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
The Bottom Line Palladium closed June 2020 at a price of $1,932 per troy ounce. Based on historical valuations dating to January 1968 (630 months) I estimate the fairvalue price of the commodity to be $972, implying an overvaluation of +1.6 standard deviations. This indicates that it is priced more cheaply today than only 6% of all previous months. Analysis of the metal´s price cycles since 1968 points to the start of a new secular bear market. The February 2020 high of $2,598 looks to be a longterm top. Historically, the median bear market in palladium has lasted for just over two years and decreased its price by 71% in real terms. Following this pattern, the current bear market phase should be completed in March 2022 after an additional 46% loss in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of palladium to decrease by 8.0%
20 3
10Year Forecast 10Year Annual Forecast Return, % 2.3 10Year Forecast Range, % (1.4, 2.9) 2 0.51 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
68 7
378  David J. Howden
Historical Analysis Since June 1990, the nominal price of palladium has increased from $116 per ounce to the current close of $1,932 for an annual return of 9.8%. The alltime nominal high for the metal came in February 2020 at a price of $2,598. This was also the alltime high in inflationadjusted terms, with its real low forming in July 1982. There have only been six months in its whole history when palladium traded at a higher real price then it does today. Over longer periods, palladium´s price has proven to be a good inflation hedge, resulting in a real yield of around 7% for most of the past 50 years. Nominal returns have hovered around 10% for most of the metal´s history, with real returns averaging 7.3% annually between 1968 and 2010. The highest longterm nominal return the investor could have earned was 22.6% and resulted by buying palladium in December 2008 and holding it until today. Since inflation over that period averaged 1.7%, the investor would have earned a real return of 20.9% per year. More recently the metal´s price has been in a bull market since February 2016. From that month´s low of $491 an advance of 383% ensued, topping out in February 2020. This high of $2,598 looks to be the end of a longterm secular bull market which should usher in a multiyear correction.
Commodities, the Decade Ahead  379 bull market phase of a cycle. Each of the seven completed bull markets in palladium with available relative valuation data has started from an undervalued position, with a median value of 0.7 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +1.9 standard deviations. Similarly, each of the metal´s six completed bear markets with relative valuation data available has started from an overvalued position, with a median value of +2.1 standard deviations above the longterm mean. Over the course of each bear market palladium continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.0 standard deviations. Palladium: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
May74 May76
140
40
76
n.a.
Feb80
297
54
85
n.a.
162
81
63
n.a.
1,065
156
86
6.0
Feb08 Dec08
571
185
67
1.2
Aug14 Feb16
900
491
45
0.9
Feb20 Jun20
2,598
1,932
25
2.9
Date Start End Jul71 May74
140
216
n.a.
40
297
433
n.a.
Mar84
54
162
184
n.a.
Dec91 Jan01
81
1,065
935
n.a.
Apr03 Feb08
156
571
217
0.7
Dec08 Aug14
185
900
330
0.8
Feb16 Feb20
491
2,598
383
0.5
Jul82 Mar84 Dec91 Jan01
Apr03
Real Start Rel. Change, % Val, σ
37
May76 Feb80 Jul82
Price Start End
Current Bear Market Forecast End Date Relative Valuation Price Real Decline, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1968 the metal has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 330% in real terms, before being corrected by a median decline of 71%. The median bull market has lasted for four years, and its subsequent correction has taken just over two years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and
Max. 7.8 86 6.0 6.7
Median 2.1 71 2.1 2.0
Mar22 0.9 742 71 2.0 Min. 0.8 45 0.9 1.4
Max. 9.1 935 0.5 3.4
Median 4.0 330 0.7 1.9
Min. 1.7 184 0.8 1.7
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bull market advance which started in February 2016. From the starting price of $2,491 the metal´s price increased by 383% in real terms. This advance is on par with the median rally of 330% over all recorded palladium bull markets. The advance´s starting relative valuation of 0.5 standard deviations was also consistent with the median bear market starting relative valuation of 0.7 standard deviations. At the recent February 2020 high of $2,598 the metal was +2.9 standard deviations overvalued, significantly more overvalued than the median starting valuation to a bear market decline. The gain of +3.4 standard deviations of valuation between 2016 and 2020 is also more extreme the median change in the measure during bull market phases (+1.9 standard deviations). As such, the balance of cycle evidence points to the February 2020
380  David J. Howden high marking the end of a bull market rally and the start of a fresh secular bear market. If a new bear market did start in February 2020 what can we expect the future to hold? The median bear market in palladium has lasted for just over two years and lost 71% in real terms. The weakest decline, during 201416, still lost 45% in real terms. Since February 2020, the metal´s price has already declined by 25%. As such, I expect the current cycle to lose an additional 46% in real terms by March 2022. This implies an expected annual return of 30% by the time the present bear market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bear markets to date, palladium has decreased its valuation within a band of 5.3 standard deviations (the weakest decline decreased its valuation by 1.4 and the strongest decreased by 6.7 standard deviations). In other words, never in the 50year price history under examination has palladium failed to decrease its valuation by less than 1.4 standard deviations over its bear market. Since the February 2020 low the metal´s relative valuation has decreased by 1.3 standard deviations, implying continual room for a price decline.
The February 2020 overvaluation of +2.9 standard deviations made the commodity more overvalued than at any time in its history. By the time the current bear market reaches its end, I expect palladium to be trading at a price which is +0.9 standard deviations undervalued relative to its longterm average. In sum, cycle analysis points to palladium trading at $742 on March 2022, a price that is +0.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the
Commodities, the Decade Ahead  381 future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for palladium starts in January 1968. This means that to date there have been 570 5year holding periods and 510 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts.
As we have seen, the future return of palladium is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of palladium over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of palladium as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic
382  David J. Howden conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 8.0% annual loss in palladium over the coming 5year period. The forecast range is also strictly negative, ranging from 10.5 to 6.2%. The model explains 57% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of palladium will breakeven by June 2025 with a 20% probability, and that the return will exceed 10% with only a 3% probability.
Commodities, the Decade Ahead  383 is significantly higher than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly overvalued. As such, palladium is the 42nd most overvalued commodity of the group. I forecast that the metal will yield an annual return of 8.0% over the coming five years, and 2.3% over the coming decade. Both returns are significantly lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, palladium ranks 42nd and 37th out of 43 commodities for the 5 and 10year return forecasts.
Palladium Forecast return rankings, out of 43 commodities Relative Valuation nd
42 Palladium 43 Commodity Avg.
Over the next ten years, I expect the price of palladium to increase by 2.3% annually. The forecast range is clustered around this level, ranging from 1.4 to 2.9%. The model explains 51% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that palladium will breakeven by June 2030 with a probability of 68%, and that there is a 7% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Palladium´s relative valuation of +1.6 standard deviations above its longterm mean
+1.6 0.7
Forecast returns: 5Year nd
42
8.0 7.6
Probability that return exceeds 10%:
10Year th
37
2.3 5.9
5Year th
40
3 39
10Year
25th 7 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is only a 3% probability that palladium can achieve this return by June 2025 and 7% by June 2030, ranking the metal 40th and 25th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that palladium will significantly underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where palladium is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1968 points to a probable decline in its price that will end in March 2022. At a low of $742 by that date, palladium will have declined from its February 2020 high in a manner consistent with the other six corrections since 1968. Analysis of palladium´s longerterm price behavior points to higher prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a rally following the completion of the current bear market, followed by a continued advance taking palladium back to levels not seen since early 2020. By June 2025, I forecast palladium to be trading at $1,276, and $2,432 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 57% of its 5year returns and 51% of its 10year returns explained since June 1990. In all cases, the price of the metal is not expected to rise above its February 2020 at any time during the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying palladium today and selling it at any date over the coming decade. For example, an expected price of $1,276 in June 2025 implies an annual rate of return of 8.0% over the next five years. Changes
384  David J. Howden in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
Commodities, the Decade Ahead  385
Palladium Expected return rankings, out of 43 commodities Relative Valuation nd
42 Palladium 43 Commodity Median
In the case of palladium, cycle analysis predicts a swift depreciation bottoming in March 2022, and the period valuation models forecast mild price increases over the next five years, and a mild appreciation over the coming decade. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 26.9% by buying palladium. This expected return is nearly improved but still negative 7.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, palladium ranks last and secondtolast. This implies that it should yield returns far inferior to the average commodity over both the coming five and ten years. Taking the average of the metal´s rankings for these expected returns, palladium ranks last out of the 43 commodities.
+1.6 0.8
Expected average returns: 5Year rd
43
26.9 21.2
10Year nd
42
7.8 8.1
Overall Rank rd
43
386  David J. Howden
Commodities, the Decade Ahead  387
Palm Oil Palm oil is the world´s most widely consumed vegetable oil. Owing to its low cost, it is the primary cooking oil in the developing world and is also widely used by developed nations in food processing. Palm oil is also used as a biofuel, accounting for half of European biodiesel production. Indonesia produces over 58% of the world´s palm oil and, together with Malaysia, produces nearly 90% of global output.
Global palm oil output reached 71.5 million tons in 2019, a 69% increase over the previous decade. This increase came largely as a result of expanded production in Indonesia, where output has increased by 131% since 2009 for an extra 23 million tons of annual production. Indonesia remains the world´s number one producer, a position it has held since overtaking Malaysia in 2008. Since 1999 world output has increased at an annual rate of 7.1%. Globally, there are 19 million hectares of land devoted to cultivation of palm oil tree trees. This area is 23%
388  David J. Howden more than there was a decade ago and, since 1999, the area of palm oil trees the world has harvested has grown by 3.6% annually. Although land use peaked in 2015, cultivation has since picked up and total area is nearing its alltime high. Increasing yields have added to these gradually increasing harvest areas and contributed to total supply growth. Globally, the palm oil trees yield 14.4 metric tons of fruit to the hectare. Yields are not appreciably higher than they were a decade ago, and since 1999 they have increased by only 1.2% annually. While yields are still increasing, the rate of change has steadily declined over the last 30 years, from 34% annually to the current rate near 1%. Palm oil is traded primarily on the Chicago Mercantile Exchange. The CME palm oil (CPO) cash contract returned 1.9% to the investor over the past year. Futures trade in lots of 25 metric tons and are quoted in U.S. dollars per metric ton.
The Bottom Line Palm oil closed June 2020 at a price of $533 per metric ton. Based on historical valuations dating to January 1980 (486 months) I estimate the fairvalue price of the commodity to be $712, implying an undervaluation of 0.9 standard deviations. This indicates that it is priced more cheaply today than 82% of all previous months. Analysis of the oil´s price cycles since 1980 points to the start of a new secular bull market. The April 2020 low of $500 looks to be a longterm bottom. Historically, the median bull market in palm oil has lasted for 2.3 years and increased its price by 154% in real terms. Following this pattern, the current bull market phase should be completed in August 2022 after an additional 147% gain in the oil´s inflationadjusted price. Over the coming 5year period, I forecast the price of palm oil to increase by 10.3% annually, with a forecast range between 9.3 and 11.8%. The forecast model explains 65% of the variation in the oil´s 5year returns since June 1990. Consequently, I forecast that palm oil´s price will breakeven by June 2025 with a 95% probability, and that there is a 52% chance that the oil´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast palm oil´s price to increase by 7.8% annually until June 2030 with a forecast range between 5.8 and 10.8%. This model explains 61% of the oil´s 10year returns since June 1990. As such, there is a 99% probability that palm oil will breakeven over the coming decade, and a 26% chance that it will yield a return greater than 10%.
Commodities, the Decade Ahead  389
Palm Oil: Forecast Summary 533 712 0.9
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Apr20 Aug22 147 53
5Year Forecast 5Year Annual Forecast Return, % 10.3 5Year Forecast Range, % (9.3, 11.8) 2 0.65 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
95 52
10Year Forecast 10Year Annual Forecast Return, % 7.8 10Year Forecast Range, % (5.8, 10.8) 2 0.61 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 26
Historical Analysis Since June 1990, the nominal price of palm oil has increased from $206 per metric ton to the current close of $504 for an annual return of 3.1%. The alltime nominal high for the oil came in February 2011 at a price of $1,145. In real, inflationadjusted terms the oil´s price has mostly traded between $500 and $1,000 over its history. Palm oil´s real high was in May 1984, with its subsequent low forming in February 2001. As of June 2020, the oil´s price was lower than 74% of all prior monthly closing prices in real terms. Over longer periods, palm oil´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 1% for most of the last 40 years. Nominal returns have hovered around 1.5% for most of the oil´s history, with real returns averaging 0.7% annually between 1980 and 2010. The highest longterm nominal
390  David J. Howden return the investor could have earned was 6.1% and resulted by buying palm oil in February 2001 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of around 4.1% per year. More recently the oil´s price has been in a bear market since February 2011. From that month´s high of $1,145 a collapse of 62% ensued. The April 2020 bottom of $500 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  391 Palm Oil: Historical Cycle Summary Declines Date Start End May84 Aug86
Price Start End
Advances Real Start Rel. Change, % Val, σ
721
149
80
n.a.
Jul88
Jun90
392
206
52
n.a.
Dec94
Jul96
541
384
32
n.a.
May98 Feb01
590
170
73
n.a.
Mar04 Feb05
477
319
35
n.a.
Mar08 Nov08
1,052
397
62
n.a.
Feb11 Apr20
1,145
500
62
3.4
Date Start End Oct82 May84
Price Start End 269
721
154
n.a.
Aug86
149
392
142
n.a.
Jun90 Dec94
206
541
128
n.a.
Jul96 May98
384
590
48
n.a.
Feb01 Mar04
170
477
164
n.a.
Feb05 Mar08
319
1,052
197
n.a.
Nov08 Feb11
397
1,145
176
0.1
Apr20 Jun20
500
534
7
1.1
Jul88
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1980 the oil has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the oil´s price increase by 154% in real terms, before being corrected by a median decline of 62%. The median bull market has lasted for just over two years, and its subsequent correction has taken nearly two years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in palm oil with available relative valuation data has started from an undervalued position, with a median value of 0.6 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.5 standard deviations. Similarly, each of the oil´s seven completed bear markets with available relative valuation data has started from an overvalued position, with a median value of +3.4 standard deviations above the longterm mean. Over the course of each bear market palm oil continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.5 standard deviations.
Max. 9.2 80 n.a. n.a.
Median 1.9 62 3.4 4.5
Min. 0.7 32 n.a. n.a.
Max. 4.5 197 0.1 n.a.
Median 2.3 154 0.6 3.5
Min. 1.6 48 1.1 n.a.
Aug22 2.4 1,273 154 3.5
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in February 2011. From the starting price of $1,145 the oil´s price fell by 62% in real terms. This decline is on par with the median decline of 62% over all recorded palm oil bear markets. At the recent April 2020 low of $500 the oil was 1.1 standard deviations undervalued, consistent with the median undervaluations in other markets at the start of bull markets. The loss of 4.5 standard deviations of valuation between 2011 and 2020 is also consistent with other commodities. As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in palm oil has lasted for over two years and gained 154% in real terms. The weakest advance, during 199698, gained 48% in real terms. Since April 2020, the oil has already gained 7%. As such, I expect the current cycle to gain an additional 137% in real terms by August 2022. This implies an expected annual return of 53% by the time the present bull market reaches completion.
392  David J. Howden
Commodities, the Decade Ahead  393 As we have seen, the future return of palm oil is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of palm oil over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of palm oil as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 10.3% annual gain in palm oil over the coming 5year period. The forecast range is also strictly positive, ranging from 9.3 to 11.8%. The model explains 65% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of palm oil will breakeven by June 2025 with a 95% probability, and that the return will exceed 10% with a 52% probability.
The April 2020 undervaluation of 1.1 standard deviations made the commodity more undervalued than 87% of all previous months. By the time the current bull market reaches its end, I expect palm oil to be trading at a price which is +2.4 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to palm oil trading at $1,273 by August 2022, a price that is +2.4 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for palm oil starts in January 1980. This means that to date there have been 426 5year holding periods and 366 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts.
Over the next ten years, I expect the price of palm oil to increase by 7.8% annually. The forecast range is clustered around this level, ranging from 9.3 to 11.8%. The model explains 65% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that palm oil will breakeven by June 2030 with a probability of 99%, and that there is a 26% chance that its return will exceed 10% over this period.
394  David J. Howden
Commodities, the Decade Ahead  395 terms, but not by much relative to other commodities. As such, palm oil is the 17th most undervalued commodity of the group. I forecast that the oil will yield an annual return of 10.3% over the coming five years, and 7.8% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, palm oil ranks 15th out of 43 commodities for both the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 52% probability that palm oil can achieve this return by June 2025 and 26% by June 2030, ranking the oil 14th and 15th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that palm oil will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where palm oil is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1980 points to a probable advance in its price that will end August 2022. At a high of $1,273 by that date, palm oil will have advanced from its April 2020 low in a manner consistent with the other seven advances since 1980.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future.
Palm Oil Forecast return rankings, out of 43 commodities Relative Valuation th
17 Palm Oil 43 Commodity Avg.
0.9 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year th
10.3 7.6
7.8 5.9
52 39
26 22
15
15
14
15
Palm oil´s relative valuation of 0.9 standard deviations below its longterm mean is slightly lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute
Analysis of palm oil´s longerterm price behavior also points to higher prices five and ten years from now. These longerterm forecasts confirm the September 2022 high projected by cycle analysis, though over a longer time horizon and at lower levels. By June 2025, I forecast palm oil to be trading at $871, and $1,129 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 65% of its 5year
396  David J. Howden
Commodities, the Decade Ahead  397
returns and 61% of its 10year returns explained since June 1990. In all cases, the price of the oil is not expected to fall below its April 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying palm oil today and selling it at any date over the coming decade. For example, an expected price of $871 in June 2025 implies an annual rate of return of 10.3% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of palm oil, cycle analysis predicts a steady appreciation topping in August 2022, and the period valuation models also forecast price increases over the longer term. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 38.5% by buying the oil. This expected return is somewhat muted at 10.3% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, palm oil ranks 7th and 15th out of the 43 commodities. This implies that it should yield returns superior to the average commodity over both time periods, but especially over the next five years. Taking the average of the oil´s rankings for these expected returns, palm oil ranks 14th out of the 43 commodities.
Platinum Platinum is one of the least reactive metals and highly resistant to corrosion. It is one of the more rare elements found on Earth, although several localized deposits exist in large quantities. The silverywhite metal is used widely in vehicle emissions control devices (catalytic converters), and jewelry. Smaller amounts are used in chemical production and electronics. Although it has a much shorter history than gold and silver, platinum is also widely demanded for investment purposes. South Africa accounts for nearly threequarters of global production of the metal and, along with Russia and Zimbabwe, produces over 90% of the world´s platinum. Consumption is driven by automobile production, with Western Europe, China, North America, and India accounting for almost 70% of the world´s consumption.
Palm Oil Expected return rankings, out of 43 commodities Relative Valuation th
17 Palm Oil 43 Commodity Median
0.9 0.8
Expected average returns: 5Year th
10Year th
38.5 21.2
10.3 8.1
7
15
Overall Rank th
14
Global platinum output reached 180,000 kilograms in 2019, a 2% decrease over the previous decade. This decrease came largely as a result of consolidated production in the top five mining countries, as smaller producers reduced output. Decreased production also resulted as the top two countries in terms of output, South Africa and Russia, have decreased production since 2009. South Africa produces 8% less platinum today than it did a decade ago (11,000 kilograms annually), while Russia has decreased production by a much larger percentage (10%) though from a much lower base, resulting in an output decline of 3,000 kilograms annually. South Africa remains the world´s top platinum producer, a position it has held since records begin in 1999. Recycled platinum remains an important source augmenting mined production. Approximately 30% of the world´s platinum supply comes from recycled sources, with catalytic converters being the primary source. (In 2018 49,000 kilograms was recovered
398  David J. Howden
Commodities, the Decade Ahead  399 from catalytic converters in the United States alone, and globally 116,000 kilograms was recycled.) Since 1999 world output has increased at an annual rate of 0.5%. There are approximately 6.9 million kilograms of platinum group metals (PGM: mostly platinum and palladium, with smaller amounts of iridium, osmium, rhodium, and ruthenium) in reserves globally. Over the last decade world PGM reserves have shrunk by just 0.3% annually as new sources have proven difficult to find. Nearly all of the world´s reserves are located in South Africa (91%). The top five producing countries (Canada, Russia, South Africa, the United States, and Zimbabwe) account for all the world´s reserves. At current reserve and mining levels, platinum group reserves will be halved by 2142. Platinum trades primarily on the New York Mercantile Exchange, and also on the London Metal Exchange. The NYMEX platinum (PL) cash contract returned 0.8% to the investor over the past year. Futures trade in lots of 50 troy ounces and are quoted in U.S. dollars per troy ounce.
43% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that platinum´s price will breakeven by June 2025 with a 97% probability, and that there is a 71% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast platinum´s price to increase by 11.0% annually until June 2030 with a forecast range between 9.1 and 13.2%. This model explains 80% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that platinum will breakeven over the coming decade, and a 64% chance that it will yield a return greater than 10%.
Platinum: Forecast Summary 826 1,447 1.5
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Mar20 Jan23 101 32
5Year Forecast 5Year Annual Forecast Return, % 13.9 5Year Forecast Range, % (12.6, 16.9) 2 0.43 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
97 71
10Year Forecast
The Bottom Line Platinum closed June 2020 at a price of $826 per troy ounce. Based on historical valuations dating to September 1917 (1,234 months) I estimate the fairvalue price of the commodity to be $1,447, implying an undervaluation of 1.5 standard deviations. This indicates that it is priced more cheaply today than 93% of all previous months. Analysis of the metal´s price cycles since 1917 points to the start of a new secular bull market. The March 2020 low of $724 looks to be a longterm bottom. Historically, the median bull market in platinum has lasted for 2.8 years and increased its price by 116% in real terms. Following this pattern, the current bull market phase should be completed in January 2023 after an additional 101% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of platinum to increase by 13.9% annually, with a forecast range between 12.6 and 16.9%. The forecast model explains
10Year Annual Forecast Return, % 11.0 10Year Forecast Range, % (9.1, 13.2) 0.80 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 64
400  David J. Howden
Historical Analysis Since June 1990, the nominal price of platinum has increased from $486 per ounce to the current close of $826 for an annual return of 1.8%. The alltime nominal high for the metal came in February 2008 at a price of $2,155. In real, inflationadjusted terms the metal´s price has mostly fallen throughout its history. Platinum´s real high was in February 2008, with its low forming in July 1930. As of June 2020, the metal´s price was lower than 65% of all prior monthly closing prices in real terms. Over longer periods, platinum´s price has failed to keep pace with general price inflation, resulting in a real yield of around 0% for most of the 20th century. Nominal returns have hovered around 3% for most of the metal´s history, with real returns averaging 0.3% annually between 1917 and 2010. The highest longterm nominal return the investor could have earned was 4.6% and resulted by buying platinum in December 1958 and holding it until today. Since inflation over that period averaged 3.6%, the investor would have earned a real return of 1.0% per year. More recently the metal´s price has been in a bear market since August 2011. From that month´s high of $1,842 a collapse of 65% ensued. The March 2020 bottom of $724 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  401 The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the five completed bull markets in platinum with a relative valuation available has started from an undervalued position, with a median value of 1.7 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.9 standard deviations. Similarly, each of the metal´s five completed bear markets with an available relative valuation has started from an overvalued position, with a median value of +2.0 standard deviations above the longterm mean (with the exception of the 198698 bear markets which both started from a slightly undervalued position). Over the course of each bear market platinum continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.6 standard deviations. Platinum: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Feb37 Apr46
63.86
35
58
n.a.
Jan59
87.15
54
57
n.a.
May74 Nov77
190
162
33
0.7
Jan80
Jul85
420
284
51
3.8
Aug86 Oct98
624
334
64
0.5
Jun08 Oct08
2,069
823
60
2.9
Aug11 Mar20
1,842
724
65
2.0
Sep46
Date Start End Apr31 Feb37
Price Start End 64 23.43
Real Start Rel. Change, % Val, σ 200
n.a.
Apr46 Sep46
35
87
125
n.a.
Jan59 May74
54
190
112
2.2
Nov77 Jan80
162
420
106
1.1
Aug86
284
624
116
3.0
Oct98 Jun08
334
2,069
364
1.6
Oct08 Aug11
823
1,842
114
0.7
Mar20 Jun20
724
827
15
1.7
Jul85
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1917 the metal has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 116% in real terms, before being corrected by a median decline of 58%. The median bull market has lasted for nearly three years, and its subsequent correction has taken over eightandahalf years to complete.
Max. 12.3 65 3.8 6.8
Median 8.6 58 2.0 3.6
Min. 0.3 33 0.5 1.1
Max. 15.3 364 0.7 4.9
Median 2.8 116 1.7 2.9
Min. 0.4 106 3.0 2.5
Jan23 1.2 1,562 116 2.9
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in August 2011. From the starting price of $1,842 the metal´s price fell by 65% in real terms. This decline is on par with the median decline of 57% over all recorded platinum bear markets. The decline´s starting relative valuation of +2.0 standard deviations was also consistent with the median bear market starting relative valuation of +1.4 standard deviations. At the recent March 2020 low of $724 the metal was 1.7 standard deviations undervalued, on par with the median starting valuation to a bull market advance. The loss of 
402  David J. Howden 3.7 standard deviations of valuation between 2011 and 2020 is high relative to the median change in the measure during correction phases (2.7 standard deviations). As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in platinum has lasted for 2.8 years and gained 116% in real terms. The weakest advance, during 197780, gained 106% in real terms. Since March 2020, the metal has already gained 15%. As such, I expect the current cycle to gain an additional 101% in real terms by September 2022. This implies an expected annual return of 38% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, platinum has increased its valuation within a relatively narrow band of +2.4 standard deviations (the weakest advance increased its valuation by +2.5 and the strongest increased by +4.9 standard deviations). In other words, never in the 100year price history under examination has platinum failed to increase its valuation by less than +2.5 standard deviations over its bull market. Since the March 2020 low the metal´s relative valuation has increased by +0.2 standard deviations, implying significant upside potential.
The March 2020 undervaluation of 1.7 standard deviations made the commodity more undervalued than 96% of all previous months. By the time the current bull market reaches its end, I expect platinum to be trading at a price which is +1.2 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to platinum trading at $1,562 on January 2023, a price that is +1.2 standard deviations overvalued. Forecasted Returns
Commodities, the Decade Ahead  403 The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for platinum starts in September 1917. This means that to date there have been 1,174 5year holding periods and 1,114 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of platinum is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future.
I have developed two models to forecast the return of platinum over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run.
404  David J. Howden Both models use the relative valuation of platinum as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 13.9% annual gain in platinum over the coming 5year period. The forecast range is also strictly positive, ranging from 12.6 to 16.9%. The model explains 43% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of platinum will breakeven by June 2025 with a 97% probability, and that the return will exceed 10% with a 71% probability.
Commodities, the Decade Ahead  405 the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Platinum´s relative valuation of 1.5 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, platinum is the 8th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 13.9% over the coming five years, and 11.0% over the coming decade. Both returns are significantly higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, platinum ranks 8th and 6th out of 43 commodities for the 5 and 10year return forecasts.
Platinum Forecast return rankings, out of 43 commodities Relative Valuation th
8 Platinum 43 Commodity Avg.
Over the next ten years, I expect the price of platinum to increase by 11.0% annually. The forecast range is clustered around this level, ranging from 9.1 to 13.2%. The model explains 80% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that platinum will breakeven by June 2030 with a probability of 99%, and that there is a 64% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform
1.5 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year th
13.9 7.2
11.0 5.9
71 39
64 22
8
6
7
5
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 71% probability that platinum can achieve this return by June 2025 and 64% by June 2030, ranking the metal 7th and 5th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that platinum will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where platinum is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1917 points to a probable advance in its price that will end January 2023. At a high of $1,562 by that date, platinum will have advanced from its March 2020 low in a manner consistent with the other seven advances since 1917. Analysis of platinum´s longerterm price behavior points to higher prices five and ten years from now. These longerterm forecasts confirm the September 2022 high projected by cycle analysis, though over a longer time horizon. By June 2025, I forecast platinum to be trading at $1,586, and $2,348 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 43% of its 5year returns and 80% of its 10year returns explained since June 1990. In all cases, the price of the meal is not expected to fall below its March 2020 low at any time over the coming decade.
406  David J. Howden
Commodities, the Decade Ahead  407
Platinum Expected return rankings, out of 43 commodities Relative Valuation th
8 Platinum 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying platinum today and selling it at any date over the coming decade. For example, an expected price of $1,586 in June 2025 implies an annual rate of return of 13.9% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of platinum, cycle analysis predicts a steady appreciation topping in January 2023, and the period valuation models also forecast price increases over the longer term. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 28.1% by buying platinum. This expected return is somewhat muted at 13.9% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, platinum ranks 14th and 7th. This implies that it should yield far superior returns than the average commodity over both the coming five and ten years. Taking the average of the metal´s rankings for these expected returns, platinum ranks 5th out of the 43 commodities.
1.5 0.8
Expected average returns: 5Year th
14
28.1 21.2
10Year th
7
13.9 8.1
Overall Rank th
5
408  David J. Howden
Commodities, the Decade Ahead  409
RBOB Gasoline Reformulated blendstock for oxygenate blending (RBOB) gasoline is a petroleumderived flammable liquid, used primarily in internal combustion engines. One barrel of crude oil (160 liters) can yield up to 72 liters of RBOB gasoline. Gasoline is the most common product produced during the petroleum refining process and represents nearly half of all petroleumbased products. The United States accounts for 40% of global production of the fuel and, along with China, produces nearly half of the world´s supply.
RBOB Gasoline is traded primarily on the New York Mercantile Exchange and futures are also available on the Intercontinental Exchange. The NYMEX RBOB gasoline (RB) cash contract returned 36.6% to the investor over the past year. Futures trade in lots of 42,000 gallons and are quoted in U.S. dollars per gallon.
The Bottom Line Gasoline closed June 2020 at a price of $1.20 per gallon. Based on historical valuations dating to March 1935 (1,024 months) I estimate the fairvalue price of the commodity to be $2.47, implying an undervaluation of 1.6 standard deviations. This indicates that it is priced more cheaply today than 94% of all previous months. Analysis of the fuel´s price cycles since 1935 points to the start of a new secular bull market. The March 2020 low of $0.57 looks to be a longterm bottom. Historically, the median bull market in gasoline has lasted for 6.9 years and increased its price by 233% in real terms. Following this pattern, the current bull market phase should be completed in
410  David J. Howden
Commodities, the Decade Ahead  411
February 2027 after an additional 119% gain in the fuel´s inflationadjusted price. Over the coming 5year period, I forecast the price of gasoline to increase by 17.5% annually, with a forecast range between 16.1 and 20.2%. The forecast model explains 47% of the variation in the fuel´s 5year returns since June 1990. Consequently, I forecast that gasoline´s price will breakeven by June 2025 with a 99% probability, and that there is an 83% chance that the fuel´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast gasoline´s price to increase by 11.4% annually until June 2030 with a forecast range between 10.3 and 12.7%. This model explains 70% of the fuel´s 10year returns since June 1990. As such, there is a 99% probability that gasoline will breakeven over the coming decade, and a 64% chance that it will yield a return greater than 10%.
RBOB Gasoline: Forecast Summary 1.20 2.47 1.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Historical Analysis Since June 1990, the nominal price of gasoline has increased from $0.56 per gallon to the current close of $1.20 for an annual return of 2.6%. The alltime nominal high for the fuel came in June 2008 at a price of $3.49. In real, inflationadjusted terms the fuel´s price has mostly fallen throughout its history. Gasoline´s real high was in June 2008, with its low forming in September 1987. As of June 2020, the fuel´s price was lower than 63% of all prior monthly closing prices in real terms. Over longer periods, gasoline´s price has failed to keep pace with general price inflation, resulting in a real yield of around 0 to 0.5% for most of the 20th century. Nominal returns have hovered around 3% for most of the fuel´s history, with real returns averaging 0.3% annually between 1935 and 2010. The highest longterm nominal return the investor could have earned was 6.2% and resulted by buying gasoline in November 1998 and holding it until today. Since inflation over that period averaged 2.1%, the investor would have earned a real return of 4.1% per year. More recently the fuel´s price has been in a bear market since September 2012. From that month´s high of $3.39 a collapse of 85% ensued. The March 2020 bottom of $0.57 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Up Mar20 Feb27 119 13
5Year Forecast 5Year Annual Forecast Return, % 17.5 5Year Forecast Range, % (16.1, 20.2) 2 0.47 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
99 83
10Year Forecast 10Year Annual Forecast Return, % 11.4 10Year Forecast Range, % (10.3, 12.7) 2 0.70 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 64
Since 1935 the fuel has gone through four complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the fuel´s price increase by 233% in real terms, before being corrected by a median decline of 73%. The median bull market has lasted for just under seven years, and its subsequent correction takes nearly sixandahalf years to complete.
412  David J. Howden
Commodities, the Decade Ahead  413
The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the four completed bull markets in gasoline has started from an undervalued position, with a median value of 2.1 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +4.3 standard deviations. Similarly, each of the fuel´s seven completed bear markets has started from an overvalued position, with a median value of +2.5 standard deviations above the longterm mean. Over the course of each bear market gasoline continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.4 standard deviations. RBOB Gasoline: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
0.93
0.31
72
2.9
Sep90 Nov98
0.99
0.33
73
0.3
Jun08 Dec08
3.49
0.97
71
4.0
Sep12 Mar20
3.39
0.57
85
2.0
Apr81
Jul86
real terms. The weakest advance, during 198690, gained 160% in real terms. Since March 2020, the fuel has already gained 114%. As such, I expect the current cycle to gain an additional 119% in real terms by February 2027. This implies an expected annual return of 13% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, gasoline has increased its valuation within a relatively narrow band of +4.3 standard deviations (the weakest advance increased its valuation by +2.3 and the strongest increased by +5.6 standard deviations). In other words, never in the 85year price history under examination has gasoline failed to increase its valuation by less than +2.3 standard deviations over its bull market. Since the March 2020 low the fuel´s relative valuation has increased by +0.8 standard deviations, implying significant upside potential.
Date Start End Oct70 Apr81
Price Start End 0.12
0.93
250
2.1
Jul86
Sep90
0.31
0.99
160
3.2
Nov98 Jun08
0.33
3.49
704
1.6
Dec08 Sep12
0.97
3.39
216
0.3
Mar20
0.57
1.20
114
2.4
Jun20
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 8.2 85 4.0 6.1
Median 6.4 73 2.5 4.4
Min. 0.5 71 0.3 1.9
Max. 10.5 704 0.3 5.6
Median 6.9 233 2.1 4.3
Min. 3.8 160 3.2 2.3
Feb27 1.9 1.90 233 4.3
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in September 2012. From the starting price of $3.39 the fuel´s price fell by 85% in real terms. This decline is a little more severe than the median decline of 73% over all recorded gasoline bear markets. The decline´s starting relative valuation of +2.0 standard deviations was also consistent with the median bear market starting relative valuation of +2.5 standard deviations. At the recent March 2020 low of $0.57 the fuel was 2.4 standard deviations undervalued, on par with the median starting valuation to a bull market advance. The loss of 4.4 standard deviations of valuation between 2012 and 2020 is also consistent with the median change in the measure during correction phases (4.4 standard deviations). As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in gasoline has lasted for nearly seven years and gained 233% in
The March 2020 undervaluation of 2.4 standard deviations made the commodity more undervalued than 99% of all previous months. By the time the current bull market reaches its end, I expect gasoline to be trading at a price which is +1.9 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to gasoline trading at $1.90 on February 2027, a price that is +1.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure
414  David J. Howden historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for gasoline starts in March 1935. This means that to date there have been 964 5year holding periods and 904 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of gasoline is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of gasoline over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run.
Commodities, the Decade Ahead  415 I forecast a 17.5% annual gain in gasoline over the coming 5year period. The forecast range is also strictly positive, ranging from 16.1 to 20.2%. The model explains 47% of the variation of the 300 5year returns of the fuel since June 1990. Given this explanatory power of the model, I estimate that the price of gasoline will breakeven by June 2025 with a 99% probability, and that the return will exceed 10% with an 83% probability.
Over the next ten years, I expect the price of gasoline to increase by 11.4% annually. The forecast range is clustered around this level, ranging from 10.3 to 12.7%. The model explains 70% of the variance in the fuel´s 240 10year returns since June 1990. As such, I estimate that gasoline will breakeven by June 2030 with a probability of 99%, and a 64% chance that its return will exceed 10% over this period.
Conclusion
Both models use the relative valuation of gasoline as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Gasoline´s relative valuation of 1.6 standard deviations below its longterm mean is far lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the fuel is highly undervalued. As such, gasoline is the 3rd most undervalued commodity of the group.
416  David J. Howden
Commodities, the Decade Ahead  417
I forecast that the fuel will yield an annual return of 17.5% over the coming five years, and 11.4% over the coming decade. Both returns are far greater than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, gasoline ranks 3rd and 5th out of 43 commodities for the 5 and 10year return forecasts.
RBOB Gasoline Forecast return rankings, out of 43 commodities Relative Valuation
RBOB Gasoline 43 Commodity Avg.
Forecast returns:
Probability that return exceeds 10%:
5Year
10Year
5Year
10Year
3rd
3rd
5th
2nd
5th
1.6 0.7
17.5 7.6
11.4 5.9
83 39
64 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is an 83% probability that gasoline can achieve this return by June 2025 and 64% by June 2030, ranking the fuel 2nd and 5th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that gasoline will outperform the average commodity over both the coming 5 and 10year periods.
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where gasoline is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1935 points to a probable advance in its price that will end February 2027. At a high of $1.90 by that date, gasoline will have advanced from its March 2020 low in a manner consistent with the other four advances since 1935. Analysis of gasoline´s longerterm price behavior points to higher prices five and ten years from now, with a bust intervening between the two dates. These longerterm forecasts confirm the February 2027 high projected by cycle analysis. By June 2025, I forecast gasoline to be trading at $2.68, and $3.52 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 47% of its 5year returns and 70% of its 10year returns explained since June 1990. In all cases, the price of the meal is not expected to fall below its March 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying gasoline today and selling it at any date over the coming decade. For example, an expected price of $2.68 in June 2025 implies an annual rate of return of 17.5% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
RBOB Gasoline Expected return rankings, out of 43 commodities Relative Valuation rd
3 RBOB Gasoline 43 Commodity Median
1.6 0.8
Expected average returns: 5Year th
10Year rd
21.2 21.2
17.1 8.1
12
3
Overall Rank st
1
In the case of gasoline, cycle analysis predicts a steady appreciation topping in July 2026, and the period valuation models also forecast price increases. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over
418  David J. Howden the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 21.2% by buying gasoline. This expected return is even higher at 17.1% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, gasoline ranks 12th and 3rd. This implies that it should yield far superior returns than the average commodity over the coming decade, and comparable returns over the next five years. Taking the average of the fuel´s rankings for these expected returns, gasoline ranks 1st out of the 43 commodities.
Commodities, the Decade Ahead  419
Rice Rice is the most widely consumed staple food in the world, especially in Asia and Africa. It is also the third most highly produced agriculture commodity, after sugarcane and corn. Rice accounts for onefifth of all calories consumed globally.
China accounts for approximately onethird of global production of the grain and, along with India and Bangladesh, accounts for nearly twothirds of global production. These three countries also account for nearly 60% of the world´s rice consumption. Global rice output reached 782 million tons in 2018, a 14% increase over the previous decade. This increase came largely as a result of expanded production in India, where output has risen by 17% over the past decade for an additional 24.5 million tons annually. Bangladesh has seen the largest percentage gains in recent years, with production up 21% since 2008. (Starting from a much lower base means that this amounts to only an additional 10 million tons of annual production.) China remains the
420  David J. Howden world´s top rice producer, a position it has held since records begin in 1961. Since 1999 world output has increased at an annual rate of 1.3%. Globally, there are 167 million hectares of land devoted to rice production. This area is 4.4% more than there was a decade ago and, since 1999, the area of rice the world has harvested has grown by 0.4% annually. Increasing yields have added to these gradually increasing harvest areas and contributed to total supply growth. Globally, rice yields 4.7 metric tons to the hectare. Yields are 9% higher than they were a decade ago, and since 1999 they have increased by 1.0% annually. Both trends of slow, gradual increases in both land cultivated and yields, have been in place for more than 30 years and show no immediate signs of abating. World rice stocks ended 2019 at 181.8 million metric tons. Globally there has been an average annual supply surplus of 8.1 million metric tons over the past decade. Recent increases in production have increased rice stocks by 6.7% annually since 2010. Global supply has also outstripped demand to create an annual surplus every year since 2006. The earliest futures trading exchange is the Dōjima Rice Exchange, established in 1710 in Japan. Today rice is traded primarily on the Chicago Board of Trade. The CBOT rough rice (14) cash contract returned 5.6% to the investor over the past year. Futures trade in lots of 2,000 hundredweights and are quoted in U.S. cents per hundredweight.
The Bottom Line Rice closed June 2020 at a price of $0.12. per hundredweight Based on historical valuations dating to January 1947 (882 months) I estimate the fairvalue price of the commodity to be $0.13, implying an undervaluation of 0.3 standard deviations. This indicates that it is priced more cheaply today than 64% of all previous months. Analysis of the grain´s price cycles since 1947 points to the end of the secular bull
Commodities, the Decade Ahead  421 market that started in February 2017 at the bottom of $0.9290. Historically, the median bear market in rice has lasted for 5.2 years and decreased its price by 67% in real terms. Following this pattern, the current bear market phase should be completed in August 2025 after an additional 39% loss in rice´s inflationadjusted price.
Rice: Forecast Summary 12.23 12.98 0.3
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Down Jun20 Aug25 39 9
5Year Forecast 5Year Annual Forecast Return, % 4.3 5Year Forecast Range, % (4.1, 4.6) 2 0.68 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
77 17
10Year Forecast 10Year Annual Forecast Return, % 5.4 10Year Forecast Range, % (3.1, 8.7) 2 0.67 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
95 8
Over the coming 5year period, I forecast the price of rice to increase by 4.3% annually, with a forecast range between 4.1 and 4.6%. The forecast model explains 68% of the variation in the grain´s 5year returns since June 1990. Consequently, I forecast that the price of rice will breakeven by June 2025 with a 77% probability, and that there is a 17% chance that the cereal´s return will be over 10% by that date. The coming decade should see somewhat higher returns. I forecast the price of rice to increase by 5.4% annually until June 2030 with a forecast range between 3.1 and 8.7%. This model explains 67% of the grain´s 10year returns since June 1990. As such, there
422  David J. Howden is a 95% probability that rice will breakeven over the coming decade, and an 8% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of rice has increased from $0.08 per hundredweight to the current close of $0.12 for an annual return of 1.4%. The alltime nominal high for the grain came in April 2008 at a price of $0.21. Rice´s real high was in November 1973, with its subsequent low forming March 2002. As of June 2020, the grain´s price was lower than 98% of all prior monthly closing price in real terms. Over longer periods, rice´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 1% for most of the 20th century. Nominal returns have hovered around 2% for most of the grain´s history, with real returns averaging 0.9% annually between 1947 and 2010. The highest longterm nominal return the investor could have earned was 6.7% and resulted by buying rice in January 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor earned a real gain of around 4.6% per year. More recently the grain´s price has been in a bull market since February 2017. From the 2017 low of $0.09 an advance of 76% ensued. The June 2020 top of $0.17 looks to be the end of a longterm secular rally, and a correction will now bring the grain to fresh lows.
Commodities, the Decade Ahead  423 terms, before being corrected by a median decline of 67%. The median bull market has lasted for just under two years, and its subsequent correction has taken over five years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in rice has started from an undervalued position, with a median value of –0.9 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.1 standard deviations. Similarly, each of the grain´s six completed bear markets has started from an overvalued position, with a median value of +1.5 standard deviations above the longterm mean. Over the course of each bear market rice continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.7 standard deviations. Rough Rice: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Jan74 Dec76
10.32
4.26
67
n.a.
Dec77 Mar87
7.46
4.06
70
1.2
Jan88
Apr93
12.25
4.91
68
2.2
Dec93 Nov94
12.20
6.38
49
1.6
Jan97 Mar02
12.33
3.72
73
1.3
Apr08 Feb17
21.48
9.29
62
5.5
May20 Jun20
17.22
12.23
28
1.0
Date Start End Apr72 Jan74
Price Start End 3.05
10.32
201
n.a.
Dec76 Dec77
4.26
7.46
64
0.7
Mar87 Jan88
4.06
12.25
192
1.2
Apr93 Dec93
4.91
12.20
147
0.5
Nov94 Jan97
6.38
12.33
82
0.8
Mar02 Apr08
3.72
21.48
378
1.9
Feb17 May20
9.29
17.22
76
0.9
Real Start Rel. Change, % Val, σ
Current Bear Market Forecast End Date Relative Valuation Price Real Decline, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1947 the grain has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the cereal´s price increase by 147% in real
Max. 9.3 73 5.5 6.4
Median 5.2 67 1.5 2.7
Aug25 1.7 5.60 67 2.7 Min. 0.9 49 1.0 2.4
Max. 6.1 378 0.5 7.4
Median 1.8 147 0.9 2.1
Min. 0.7 64 1.9 1.9
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bull market advance which started in February 2017. From the starting price of $0.09 the cereal´s price gained 76% in real terms. This advance was somewhat weak compared to the median rally of 147% over all recorded rice bull markets. The advance´s starting relative valuation of 0.9 standard deviations was on par with the median bear market starting relative valuation. At the May 2020 high of $0.12 the grain was +1.0 standard deviations overvalued. This made it marginally less overvalued than the median start to a bear market decline (+1.5 standard deviations). The gain of +1.9 standard deviations of valuation between
424  David J. Howden 2017 and 2020 is approximately equal to the median change in the measure during rallying phases (+2.1 standard deviations). At over three years, the bull market was getting long in the legs relative to the median advance (less than two years). As such, the balance of cycle evidence points to the May 2020 low marking the end of a bull market advance and the start of a fresh secular bear market. If a new bear market did start in May 2020 what can we expect the future to hold? The median bear market in rice has lasted for over five years and lost 67% in real terms. The weakest decline, during 199394, lost 49% in real terms. Since May 2020, rice has already lost 28%. As such, I expect the current cycle to lose an additional 39% in real terms by August 2025. This implies an expected annual return of 9% by the time the present bear market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bear markets to date, rice has decreased its valuation within a relatively narrow band of 4.0 standard deviations (the weakest decline decreased its valuation by 2.4 and the strongest decreased by 7.4 standard deviations). In other words, never in the 70year price history under examination has rice failed to decrease its valuation by less than 2.4 standard deviations over its bear market. Since the May 2020 high the grain´s relative valuation has decreased by 1.3 standard deviations, implying further downside potential.
The May 2020 overvaluation of +1.0 standard deviations made the commodity more overvalued than 83% of all previous months. By the time the current bear market reaches its end, I expect rice to be trading at a price which is 1.7 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to rice trading at $0.05 on August 2025, a price that is 1.7 standard deviations undervalued.
Commodities, the Decade Ahead  425
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for rice starts in January 1947. This means that to date there have been 822 5year holding periods and 762 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of rice is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future.
I have developed two models to forecast the return of rice over these two different time periods – five years and ten years. In general, the 10year forecast model is more
426  David J. Howden robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of rice as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 4.3% annual gain in rice over the coming 5year period. The forecast range is also strictly positive, ranging from 4.1 to 4.6%. The model explains 68% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of rice will breakeven by June 2025 with a 77% probability, and that the return will exceed 10% with a 17% probability.
Commodities, the Decade Ahead  427 commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Rice´s relative valuation of 0.3 standard deviations below its longterm mean is higher than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is close to fairly valued in absolute terms, but is overvalued relative to other commodities. As such, rice is the 32nd most undervalued commodity of the group. I forecast that the grain will yield an annual return of 4.3% over the coming five years, and 5.4% over the coming decade. Both returns are somewhat lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, rice ranks 32nd and 24th out of 43 commodities for the 5 and 10year return forecasts.
Rough Rice Forecast return rankings, out of 43 commodities Relative Valuation th
35 Rice 43 Commodity Avg.
Over the next ten years, I expect the price of rice to increase by 5.4% annually. The forecast range is clustered around this level, ranging from 4.1 to 8.7%. The model explains 67% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that rice will breakeven by June 2030 with a probability of 95%, and that there is an 8% chance that its return will exceed 10% over this period. 7
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other
0.3 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year nd
10Year th
5Year st
10Year rd
4.3 7.6
5.4 5.9
17 39
8 22
32
24
31
23
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 17% probability that rice can achieve this return by June 2025 and an 8% by June 2030, ranking it 31st and 23rd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that rice will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where rice is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1947 points to a probable decline in its price that will end in August 2025. At a low of $0.56 by that date, rice will have declined from its May 2020 low in a manner consistent with the other six corrections since 1947. Analysis of rice´s longerterm price behavior points to higher prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a correction until the current bear market completes, followed by a rally taking rice back to levels not seen since 2008. By June 2025, I forecast rice to be trading at $0.15, and $0.21 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 68% of its 5year returns and 67% of its 10year returns explained since June 1990. In all cases, the price of the meal is not expected to rise above its April 2020 until the very end of this decade.
428  David J. Howden
Commodities, the Decade Ahead  429
Rough Rice Expected return rankings, out of 43 commodities Relative Valuation th
35 Rough Rice 43 Commodity Median
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying rice today and selling it at any date over the coming decade. For example, an expected price of $0.15 in June 2025 implies an annual rate of return of 4.3% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of rice, cycle analysis predicts a swift depreciation bottoming in August 2025, and the period valuation models forecast mild price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 4.6% by buying rice. This expected return is nearly the same at 4.4% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, rice ranks 37th and 33rd. This implies that it should yield returns inferior to the average commodity over both the coming five and ten years. Taking the average of the grain´s rankings for these expected returns, rice ranks 35th out of the 43 commodities.
0.3 0.8
Expected average returns: 5Year th
37
4.6 21.2
10Year rd
33
4.4 8.1
Overall Rank th
35
430  David J. Howden
Commodities, the Decade Ahead  431
S&P GS Commodity Index S&P GSCI (formerly the Goldman Sachs Commodity Index) is the benchmark for commodity investments. Originally developed by Goldman Sachs in 1991, since 2007 Standard & Poor´s has calculated and published its values. The S&P GSCI contains as many commodities as possible, subject to liquidity guidelines. Currently there are 24 commodities in the index, with energy taking the largest weight at 62%. This is followed by industrial metals (11%), precious metals (5%), agriculture (16%) and livestock (7%). An individual commodity´s weight is based on the average quantity of production of that commodity, averaged over the past five years. Consequently, the index serves not just as a gauge of average commodity prices but also as a general economic indicator. S&P GSCI futures are traded on the Chicago Mercantile Exchange. The CME GSCI (GI) cash contract returned 23.5% to the investor over the past year. Futures trade in multiples of $250 times the index and are quoted in terms of index points.
The Bottom Line The S&P GSCI closed June 2020 at a price of $325. Based on historical valuations dating to January 1890 (1,566 months) I estimate the fairvalue price of the index to be $566, implying an undervaluation of 1.6 standard deviations. This indicates that it is priced more cheaply today than 94% of all previous months. Analysis of the index´s price cycles since 1900 points to the start of a new secular bull market. The March 2020 low of $255 looks to be a longterm bottom. Historically, the median bull market in the S&P GSCI has lasted for 3.3 years and increased its price by 51% in real terms. Following this pattern, the current bull market phase should be completed in July 2023 after an additional 22% gain in the index´s inflationadjusted price. Over the coming 5year period, I forecast the price of the S&P GSCI to increase by 14.3% annually, with a forecast range between 13.3 and 16.2%. The forecast model explains 47% of the variation in the index´s 5year returns since June 1990. Consequently, I forecast that S&P GSCI´s price will breakeven by June 2025 with a 98% probability, and that there is a 74% chance that the index´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast the S&P GSCI´s price to increase by 10.3% annually until June 2030 with a forecast range between 8.5 and 12.6%. This model explains 78% of the index´s 10year returns since June 1990. As such, there is a 99% probability that the S&P GSCI will breakeven over the coming decade, and a 55% chance that it will yield a return greater than 10%.
432  David J. Howden
Commodities, the Decade Ahead  433 Nominal returns have hovered around 2% for most of the index´s history, with real returns averaging 1.2% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 4.4% and resulted by buying the S&P GSCI in February 1999 and holding it until today. Since inflation over that period averaged 2.3%, the investor´s returns were somewhat more muted at 2.1% per year. More recently the index´s price has been in a bull market since June 2018. From that month´s high of $487 a loss of 49% ensued until the recent March 2020 low. The March 2020 bottom looks to be the end of a longterm secular decline which should usher in a multiyear rally.
S&P GSCI: Forecast Summary 325 566 1.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Annual Real Return Remaining, %
Up Mar20 Jul23 22 7
5Year Forecast 5Year Annual Forecast Return, % 14.3 5Year Forecast Range, % (13.3. 16.2) 2 0.47 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
98 74
10Year Forecast 10Year Annual Forecast Return, % 10.3 10Year Forecast Range, % (8.5, 12.6) 0.78 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 55
Historical Analysis Since June 1990, the nominal price of the S&P GSCI has increased from $184 to the current close of $325 for an annual return of 1.9%. The alltime nominal high for the index came in June 2008 at a price of $862. In real, inflationadjusted terms the index´s price has mostly decreased gradually throughout its history. The S&P GSCI´s real high was in November 1974, with its subsequent alltime low forming in February 1999. As of June 2020, the index´s price was lower than 18% of all prior monthly closing prices in real terms. Over longer periods, the S&P GSCI´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the past 50 years.
Since 1900 the index has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the index´s price increase by 51% in real terms, before being corrected by a median decline of 60%. The median bull market has lasted for just over three years, and its subsequent correction has taken over eight years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the six completed bull markets in the S&P GSCI has started from an undervalued position, with a median value of 1.8 standard deviations below the longterm mean. (With the exception of the 200911 bull market, that started from an approximately fairlyvalued position.) From these undervalued starting positions, the median bull market increased its relative valuation by +2.8 standard deviations. Similarly, each of the index´s six completed bear markets has started from an overvalued position, with a median value of +2.0 standard deviations above the longterm mean. Over the course of each bear market the S&P GSCI continued to shed valuation
434  David J. Howden
Commodities, the Decade Ahead  435
as its price fell. The median price decline caused the relative valuation to fall by 4.2 standard deviations. S&P GS Commodity Index: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Aug17 Jun32
61
31
51
n.a.
Feb51 Sep71
87
103
26
0.9
Nov74
Jul77
289
138
60
5.6
Nov80 Sep88
293
162
61
0.7
Sep90 Feb99
270
131
61
0.3
Jun08
Jan09
863
336
60
5.6
Apr11 Mar20
759
255
71
3.0
Date Start End Nov11 Aug17
Price Start End 28
61
50
n.a.
Jun32
31.28
87
49
1.8
Sep71 Nov74
103
289
122
2.4
Jul77
Nov80
138
293
51
2.2
Sep88 Sep90
162
270
50
1.4
Feb99 Jun08
131
863
392
1.7
Jan09
Apr11
336
759
112
0.4
Mar20 Jun20
255
325
29
2.0
Feb51
Real Start Rel. Change, % Val, σ
More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, the S&P GSCI has increased its valuation within a band of +6.3 standard deviations (the weakest advance increased its valuation by +1.7 and the strongest increased by +8.0 standard deviations). In other words, never in the 120year price history under examination has S&P GSCI failed to increase its valuation by less than +1.7 standard deviations over its bull market. Since the March 2020 low the index´s relative valuation has increased by +0.4 standard deviations, implying its change in valuation has is still weaker than the weakest bull market in over a century. Coupled with the fact that the 29% price gain since March 2020 is far lower than the previous weakest bull market, there is evidence that there is still upside potential.
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 20.6 71 5.6 7.8
Median 8.4 60 2.0 4.2
Min. 0.6 26 0.3 2.0
Max. 18.7 392 0.4 8.0
Median 3.3 51 1.8 2.8
Min. 2.0 49 2.4 1.7
Jul23 0.8 386 51 2.8
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in April 2011. From the starting price of $759 the index´s price fell by 71% in real terms. This decline is greater than the median decline of 60% over all recorded S&P GSCI bear markets, and the most extreme correction since records begin. The decline´s starting relative valuation of +3.0 standard deviations was far more overvalued than the start to the median bear market. The loss of 5.0 standard deviations of value throughout the bear market on par with the median decline since 1900. At the March 2020 low of $255 the index was 2.0 standard deviations undervalued. This made the index marginally more undervalued than the median start to a bull market advance (1.8 standard deviations). It is also the most undervalued the index has been since 1977. As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in the S&P GSCI has lasted for just over three years and gained 51% in real terms. The weakest advance, during 193251, gained 49% in real terms. Since March 2020, the index has already gained 29%. As such, I expect the current cycle to gain an additional 22% in real terms by July 2023. This implies an expected annual return of 7% by the time the present bull market reaches completion.
The March 2020 undervaluation of 2.0 standard deviations made the commodity more undervalued than 94% of all previous months. By the time the current bull market reaches its end, I expect the S&P GSCI to be trading at a price which is +0.8 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to the S&P GSCI trading at $386 on July 2023, a price that is +0.8 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second
436  David J. Howden problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for the S&P GSCI starts in January 1890. This means that to date there have been 1,506 5year holding periods and 1,446 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of the S&P GSCI is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future.
Commodities, the Decade Ahead  437 I forecast a 14.3% annual gain in the S&P GSCI over the coming 5year period. The forecast range is also strictly positive, ranging from 13.3 to 16.2%. The model explains 47% of the variation of the 300 5year returns of the index since June 1990. Given this explanatory power of the model, I estimate that the price of the S&P GSCI will breakeven by June 2025 with a 98% probability, and that the return will exceed 10% with a 74% probability.
Over the next ten years, I expect the price of the S&P GSCI to increase by 10.3% annually. The forecast range is clustered around this level, ranging from 8.5 to 12.6%. The model explains 78% of the variance in the index´s 240 10year returns since June 1990. As such, I estimate that the S&P GSCI will breakeven by June 2030 with a probability of 99%, and that there is a 55% chance that its return will exceed 10% over this period.
Conclusion I have developed two models to forecast the return of the S&P GSCI over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of the S&P GSCI as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. The S&P GSCI´s relative valuation of 1.6 standard deviations below its longterm mean is far below the average of the 43 markets analyzed herein (a slight undervaluation
438  David J. Howden
Commodities, the Decade Ahead  439
of 0.7 standard deviations) and implies that the index is undervalued in absolute terms, and also relative to the average commodity. As such, the S&P GSCI is the 4th most undervalued index of the group. I forecast that the index will yield an annual return of 14.3% over the coming five years, and 10.3% over the coming decade. Both returns are far greater than the averages for the 42 other commodities (7.2% and 5.9%). Consequently, the S&P GSCI ranks 6th and 7th out of 43 commodities for the 5 and 10year return forecasts.
S&P GS Commodity Index Forecast return rankings, out of 43 commodities Relative Valuation th
S&P GSCI 43 Commodity Avg.
Forecast returns: 5Year th
Probability that return exceeds 10%:
10Year th
4
6
7
1.6 0.7
14.3 7.6
10.3 5.9
5Year th
5
74 39
10Year th
7
55 22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 74% probability that the S&P GSCI can achieve this return by June 2025 and 55% by June 2030, ranking the index 5th and 7th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that the S&P GSCI will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the index is in its current price and valuation cycle. The evidence from the S&P GSCI´s price and valuation cycles since 1900 points to a probable increase in the index´s price that will end in July 2023. At a high of $386 by that date, the index will have advanced from its March 2020 low in a manner consistent with the other eight advances since 1900. Over this time, the S&P GSCI´s relative valuation should also increase from its current undervalued position of 1.6 standard deviations, to end this bull market rally overvalued by +0.7 standard deviations. Analysis of the S&P GSCI´s longerterm price behavior points to higher prices five years from now, with a continued advance going out to 2030. These longerterm forecasts complement and serve to confirm the forecast for higher prices provided by cycle analysis. By June 2025, I forecast the S&P GSCI to be trading at $633, and $870 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 47% of the index´s 5year returns and 77% of its 10year returns explained since June 1990. In all cases, the price of the S&P GSCI is not expected to fall below its March 2020 low at any time over the coming decade.
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying the S&P GSCI today and selling it at any date over the coming decade. For example, an expected price of $633 in June 2025 implies an annual rate of return of 14.3% over the next five years if the investor buys the index today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of the S&P GSCI, cycle analysis predicts a continued appreciation through July 2023, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5and 10year period. Between today and June 2025 the investor can expect a median annual return of 6.2% by buying the S&P GSCI. This expected return increases to 10.9% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, the S&P GSCI ranks 36th and 13th out of the 43 commodities. This implies that the S&P GSCI should lag the median commodity over the coming five
440  David J. Howden
Commodities, the Decade Ahead  441
years before offering somewhat higher returns over the next decade. Taking the average of its rankings for these expected returns, the S&P GS Commodity Index ranks 11th out of the 43 commodities.
S&P GS Commodity Index Expected return rankings, out of 43 commodities Relative Valuation th
4 S&P GSCI 43 Commodity Median
1.6 0.8
Expected average returns: 5Year th
36
6.2 21.2
10Year th
13
10.9 8.1
Steel Overall Rank th
11
Steel, the result of adding a small amount of carbon to iron, is one of the most widely used construction materials. It is also heavily employed in industrial and infrastructure applications. Its high strength and low cost make it an ideal material for basic industrial construction. Although the process to smelt steel has been known for at least 4,000 years, the Industrial Revolution and the use of the blast furnace increased the metal´s prominence.
Steel Production
Consumption
(% World)
China India Japan United States Russia Rest of World
53 6 5 5 4 27
(% World)
China United States India Japan South Korea Rest of World
49 6 6 4 3 33
Source: World Steel Association, 2020
China accounts for over half of world steel production, and nearly half of global demand. Global steel output reached 1.9 billion tons in 2019, a 54% increase over the previous decade. This increase came largely as a result of expanded production from China, where output has risen by 428 million tons per year since 2009 (a 72% increase). India has seen a similar increase at 73%, though from a much lower base. China remains the world´s top producer of steel, a position it has held since records begin in 1998. Recycled scrap remains an important source of steel augmenting
442  David J. Howden
Commodities, the Decade Ahead  443
smelted production. In the United States, approximately 83% of steel consumption comes from recycled sources (globally, more than 60% of steel is recycled). Since 1999 world output has increased at an annual rate of 4.5%. The London Metal Exchange launched scrap steel contracts in 2008. The metal also trades on the Commodity Exchange. The LME scrap steel (SC) cash contract returned 14.3% to the investor over the past year. Futures trade in lots of 10 metric tons and are quoted in U.S. dollars per metric ton.
Scrap Steel: Forecast Summary 264 394 1.1
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Feb16 Jan22 173 88
5Year Forecast 5Year Annual Forecast Return, % 14.9 5Year Forecast Range, % (13.1, 17.8) 2 0.60 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
97 74
10Year Forecast 10Year Annual Forecast Return, % 9.5 10Year Forecast Range, % (8.1, 11.5) 2 0.64 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 45
The Bottom Line Steel closed June 2020 at a price of $264 per metric ton. Based on historical valuations dating to September 1894 (1,500 months) I estimate the fairvalue price of the commodity to be $394, implying an undervaluation of 1.1 standard deviations. This indicates that it is priced more cheaply today than 87% of all previous months. Analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The February 2016 low of $171 looks to be a longterm bottom. Historically, the median bull market in steel has lasted for 5.9 years and increased its price by 218% in real terms. Following this pattern, the current bull market phase should be completed in January 2022 after an additional 173% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of steel to increase by 14.9% annually, with a forecast range between 13.1 and 17.8%. The forecast model explains 60% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that steel´s price will breakeven by June 2025 with a 97% probability, and that there is a 74% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast steel´s price to increase by 9.5% annually until June 2030 with a forecast range between 8.1 and 11.5%. This model explains 64% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that steel will breakeven over the coming decade, and a 45% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of steel has increased from $136 per metric ton to the current close of $264 for an annual return of 2.2%. The alltime nominal high for the metal came in July 2008 at a price of $649. In real, inflationadjusted terms the metal´s price has mostly fallen throughout its history. Steel´s real high was in June 1917, with its subsequent low forming in July 1932. As of June 2020, the metal´s price was lower than 77% of all prior monthly closing prices in real terms. Over longer periods, steel´s price has failed to keep pace with general price inflation, resulting in a real yield of around zero to 1% for most of the 20th century. Nominal returns have hovered around 3% for most of the metal´s history, with real returns averaging 0.4% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 6.0% and resulted by buying steel in November 2001 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of 4.0% per year. More recently the metal´s price has been in a bull market since February 2016. From that month´s low of $171 a rally of 45% has ensued. This trend appears still to be operative, and a multiyear rally in progress.
444  David J. Howden
Commodities, the Decade Ahead  445 deviations). As such, the balance of cycle evidence points to the February 2016 low marking the end of a bear market decline and the start of a fresh secular bull market. Scrap Steel: Historical Cycle Summary Declines Date Start End Mar23 Jul32
Price Start End
Advances Real Start Rel. Change, % Val, σ
32.2
7
74
0.6
Jan51 Mar54
60
32
50
0.9
Dec56 Aug68
72
29
68
1.1
Apr74 Dec82
147
65
79
6.1
Feb89 Nov01
157
89
60
0.6
Jul08
Nov08
649
189
70
5.6
Jan12
Feb16
539
171
70
2.3
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jan51
7
60
379
2.1
Mar54 Dec56
32
72
118
1.6
Aug68 Apr74
29
147
268
1.6
Dec82 Feb89
65
157
96
1.7
Nov01
Jul08
89
649
477
1.6
Nov08 Jan12
189
539
167
0.3
Feb16
171
265
45
1.7
Jul32
Jun20
Current Bull Market Forecast
Since 1900 the metal has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 218% in real terms, before being corrected by a median decline of 70%. The median bull market has lasted for just under six years, and its subsequent correction has taken nearly nine years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the six completed bull markets in steel has started from an undervalued position, with a median value of 1.6 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.9 standard deviations. Similarly, each of the metal´s seven completed bear markets has started from an overvalued position, with a median value of +1.1 standard deviations above the longterm mean. Over the course of each bear market steel continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.7 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in January 2012. From the starting price of $539 the metal´s price fell by 70% in real terms. This decline is on par with the median decline of 70% over all recorded steel bear markets. The decline´s starting relative valuation of +2.3 standard deviations was moderately more extreme than the median bear market starting relative valuation of +1.1 standard deviations. At the recent February 2016 low of $171 the metal was 1.7 standard deviations undervalued, on par with the median starting valuation to a bull market advance (1.6). The loss of 4.0 standard deviations of valuation between 2012 and 2016 is also consistent with the median change in the measure during correction phases (2.7 standard
End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 12.8 79 6.1 7.8
Median 8.7 70 1.1 2.7
Min. 0.3 50 0.6 2.2
Max. 18.5 477 0.3 7.7
Median 5.9 218 1.6 2.9
Min. 2.8 96 2.1 2.3
Jan22 1.2 543 218 2.9
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
If a new bull market did start in February 2016 what can we expect the future to hold? The median bull market in steel has lasted for nearly six years and gained 218% in real terms. The weakest advance, during 198289, gained 96% in real terms. Since February 2016, the metal has already gained 45%. As such, I expect the current cycle to gain an additional 173% in real terms by January 2022. This implies an expected annual return of 88% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, steel has increased its valuation within a band of +5.4 standard deviations (the weakest advance increased its valuation by +2.3 and the strongest increased by +7.7 standard deviations). In other words, never in the 120year price history under examination has steel failed to increase its valuation by less than +2.3 standard deviations over its bull market. Since the February 2016 low the metal´s relative valuation has increased by +0.6 standard deviations, implying significant upside potential. The February 2016 undervaluation of 1.2 standard deviations made the commodity more undervalued than 96% of all previous months. By the time the current bull market reaches its end, I expect steel to be trading at a price which is +1.2 standard deviations overvalued relative to its longterm average.
446  David J. Howden
Commodities, the Decade Ahead  447 conditions in the market and expectations of the future. I have developed two models to forecast the return of steel over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of steel as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
In sum, cycle analysis points to steel trading at $543 on January 2022, a price that is +1.2 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for steel starts in September 1894. This means that to date there have been 1,450 5year holding periods and 1,390 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of steel is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand
I forecast a 14.9% annual gain in steel over the coming 5year period. The forecast range is also strictly positive, ranging from 13.1 to 17.8%. The model explains 60% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of steel will breakeven by June 2025 with a 97% probability, and that the return will exceed 10% with a 74% probability. Over the next ten years, I expect the price of steel to increase by 9.5% annually. The forecast range is clustered around this level, ranging from 8.1 to 11.5%. The model explains 64% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that steel will breakeven by June 2030 with a probability of 99%, and that there is a 45% chance that its return will exceed 10% over this period.
448  David J. Howden
Commodities, the Decade Ahead  449
Scrap Steel Forecast return rankings, out of 43 commodities Relative Valuation th
12 Scrap Steel 43 Commodity Avg.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Steel´s relative valuation of 1.1 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, steel is the 12th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 14.9% over the coming five years, and 9.5% over the coming decade. Both returns are considerably higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, steel ranks 5th and 9th out of 43 commodities for the 5 and 10year return forecasts.
1.1 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year th
14.9 7.6
9.5 5.9
74 39
45 22
5
9
5
9
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 74% probability that steel can achieve this return by June 2025 and 45% by June 2030, ranking the metal 5th and 9th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that steel will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where steel is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1900 points to a probable advance in its price that will end in January 2022. At a high of $543 by that date, steel will have advanced from its February 2016 low in a manner consistent with the other six advances since 1900.
450  David J. Howden
Commodities, the Decade Ahead  451
Analysis of steel´s longerterm price behavior also points to higher prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply period of stable prices once the current bull market completes, followed by a rally taking steel back to levels not seen since 2008. By June 2025, I forecast steel to be trading at $529, and $655 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 60% of its 5year returns and 64% of its 10year returns explained since June 1990. In all cases, the price of the meal is not expected to fall below its February 2016 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying steel today and selling it at any date over the coming decade. For example, an expected price of $529 in June 2025 implies an annual rate of return of 14.9% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
Scrap Steel Expected return rankings, out of 43 commodities Relative Valuation th
12 Scrap Steel 43 Commodity Median
1.1 0.8
Expected average returns: 5Year th
10Year th
32.4 21.2
14.8 8.1
12
5
Overall Rank th
10
In the case of steel, cycle analysis predicts a swift appreciation topping in January 2022, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 32.4% by buying steel. This expected return is somewhat muted at 14.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, steel ranks 12th and 5th. This implies that it should yield returns superior to the average commodity over both the coming five and ten years. Taking the
average of the metal´s rankings for these expected returns, steel ranks 10th out of the 43 commodities.
452  David J. Howden
Commodities, the Decade Ahead  453
Silver Silver has been valued as a monetary metal for over 4,000 years, though the end of the gold standard in the 1930s brought this to an end. It is still widely valued for investment purposes as a precious metal, and alongside gold makes up the bulk of precious metal transactions. In addition to its investment uses, it also has various industrial uses including jewelry, medicine, and electronics. The United States Geological Survey estimates that 1.7 million metric tons have been discovered throughout Silver history. Much of this is still in use, and Production if melted it would form a cube measuring 55 meters on each side. (% World) Mexico accounts for Mexico 23 approximately onequarter of global production of the metal and, along Peru 14 with Peru and China, makes up half of China 13 total output. Global silver output reached Russia 8 27,000 tons in 2019, a 21% increase Poland 6 over the previous decade. This Rest of World 35 increase came largely as a result of expanded production from mines in Source: USGS, 2020 Argentina, Australia, Mexico, and Poland. Decreases in some countries, principally Peru as a result of protests and strikes, offset some of these gains. Still, strong output growth in Mexico (a 77% increase over the past decade) and China (a 24% increase) more than offset these regional declines. Mexico remains the world´s largest producer of silver, a position it has maintained since records begin in 1993 (with the exception of the 200309 period when Peru overtook it. Recovered scrap remains an important source of silver augmenting mine production. Approximately 17%
454  David J. Howden of silver consumption comes from recycled sources. Since 1999 world output has increased at an annual rate of 2.2%. World unmined silver reserves amounts to 560,000 tons in 2019. Over the previous decade, these reserves have grown at the robust rate of 3.4% annually. Most of this growth came from Australia (a 290% increase in reserves over the period), Peru (103%), and Poland (82%). Peru maintains the world´s largest silver reserves, at 120,000 tons (22% of global reserves). Although just five countries account for 71% of global reserves, the metal is found widely throughout the world. Silver is mined primarily as a byproduct of copper, gold, and leadzinc production. Increasingly, gold discoveries have driven increases in silver reserves and output levels although other metals continue to play a significant role in its resource availability. Silver trades primarily on the Commodity Exchange. The metal is one of the exchange´s most liquid contracts. It is also traded on the Intercontinental Exchange and London Metal Exchange. The COMEX silver (SI) cash contract returned 18.8% to the investor over the past year. Futures trade in lots of 5,000 troy ounces and are quoted in U.S. dollars per troy ounce.
Commodities, the Decade Ahead  455 such, there is a 94% probability that silver will breakeven over the coming decade, and a 9% chance that it will yield a return greater than 10%.
Silver: Forecast Summary 18.19 22.31 0.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Mar20 Jul26 275 24
5Year Forecast 5Year Annual Forecast Return, % 11.5 5Year Forecast Range, % (11.3, 11.7) 2 0.50 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
92 57
10Year Forecast 10Year Annual Forecast Return, % 5.3 10Year Forecast Range, % (2.0, 9.2) 2 0.77 Adjusted R
The Bottom Line Silver closed June 2020 at a price of $18.19 per troy ounce. Based on historical valuations dating to March 1772 (2,980 months) I estimate the fairvalue price of the commodity to be $22.31, implying an undervaluation of 0.6 standard deviations. This indicates that it is priced more cheaply today than 73% of all previous months. Analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The March 2020 low of $13.97 looks to be a longterm bottom. Historically, the median bull market in silver has lasted for 6.3 years and increased its price by 306% in real terms. Following this pattern, the current bull market phase should be completed in July 2026 after an additional 275% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of silver to increase by 11.5% annually, with a forecast range between 11.3 and 11.7%. The forecast model explains 50% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that silver´s price will breakeven by June 2025 with a 92% probability, and that there is a 57% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast silver´s price to increase by 5.3% annually until June 2030 with a forecast range between 11.3 and 11.7%. This model explains 77% of the metal´s 10year returns since June 1990. As
Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
94 9
Historical Analysis Since June 1990, the nominal price of silver has increased from $4.91 per troy ounce to the current close of $18.19 for an annual return of 4.5%. The alltime nominal high for the metal came in April 2011 at a price of $47.88. In real, inflationadjusted terms the metal´s price has increased slowly throughout its history. Silver´s real high was in February 1980, with its subsequent low forming decades earlier, in March 1932. As of June 2020, the metal´s price was lower than 30% of all prior monthly closing prices in real terms.
456  David J. Howden Over longer periods, silver´s has served as an effective inflation hedge, resulting in a real yield of around 1% for most of the 20th century. Nominal returns have hovered around 4% for most of the metal´s history, with real returns averaging 1.1% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 8.5% and resulted by buying silver in March 2003 and holding it until today. Since inflation over that period averaged 1.9%, the investor earned a somewhat lower real return 6.6% per year. More recently the metal´s price has been in a bear market since April 2011. From that month´s high of $47.88 a collapse of 75% ensued. The March 2020 bottom of $13.97 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  457 mean. Over the course of each bear market silver continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 6.7 standard deviations. Silver: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Mar35 Dec41
0.64
0.35
51
0.1
Jun68
Oct71
2.49
1.31
55
5.0
Feb80 Nov01
35.20
4.16
95
8.0
Feb08 Oct08
19.83
9.80
52
3.5
Apr11 Mar20
47.88
13.97
75
7.1
Date Start End Mar32 Mar35
Price Start End 0.25
0.64
157
2.3
Dec41 Jun68
0.35
2.49
220
1.2
Oct71 Feb80
1.31
35.20
1,284
1.7
Nov01 Feb08
4.16
19.83
306
0.6
Oct08
Apr11
9.80
47.88
371
1.0
Mar20 Jun20
13.97
18.19
31
1.1
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the metal has gone through five complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 306% in real terms, before being corrected by a median decline of 55%. The median bull market has lasted for just over six years, and its subsequent correction has taken nearly seven years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the five completed bull markets in silver has started from an undervalued position (except for 20082011 which started from a moderately overvalued position), with a median value of 1.2 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +6.1 standard deviations. Similarly, each of the metal´s five completed bear markets has started from an overvalued position, with a median value of +5.0 standard deviations above the longterm
Max. 21.8 95 8.0 8.6
Median 6.8 55 5.0 6.7
Min. 0.7 51 0.1 1.3
Max. 26.5 1,284 1.0 9.7
Median 6.3 306 1.2 6.1
Min. 2.5 157 2.3 2.4
Jul26 5.0 57 306 6.1
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in April 2011. From the starting price of $47.88 the metal´s price fell by 75% in real terms. This decline is far more significant than the median decline of 55% over all recorded silver bear markets. The decline´s starting relative valuation of +7.1 standard deviations was also relatively high compared to the median bear market starting relative valuation of +5.0 standard deviations. At the recent March 2020 low of $13.97 the metal was 1.1 standard deviations undervalued, on par with the median starting valuation to a bull market advance. The loss of 8.2 standard deviations of valuation between 2011 and 2020 is also not far off the median change in the measure during correction phases (6.7 standard deviations). As such, the balance of cycle evidence points to the March 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in silver has lasted for 6.3 years and gained 306% in real terms. The weakest advance, during 193235, gained 157% in real terms. Since March 2020, the metal has already gained 31%. As such, I expect the current cycle to gain an additional 275% in real terms by July 2026. This implies an expected annual return of 24% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, silver has increased its valuation within a band of +7.3
458  David J. Howden standard deviations (the weakest advance increased its valuation by +2.4 and the strongest increased by +9.7 standard deviations). In other words, never in the 120year price history under examination has silver failed to increase its valuation by less than +2.4 standard deviations over its bull market. Since the March 2020 low the metal´s relative valuation has increased by +0.5 standard deviations, implying significant upside potential.
The March 2020 undervaluation of 1.2 standard deviations made the commodity more undervalued than 86% of all previous months. By the time the current bull market reaches its end, I expect silver to be trading at a price which is +5.0 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to silver trading at $57 on July 2026, a price that is +5.0 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like.
Commodities, the Decade Ahead  459 We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for silver starts in December 1774. This means that to date there have been 2,887 5year holding periods and 2,827 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of silver is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of silver over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of silver as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 11.5% annual gain in silver over the coming 5year period. The forecast range is also strictly positive, ranging from 11.3 to 11.7%. The model explains 50% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of silver will breakeven by June 2025 with a 92% probability, and that the return will exceed 10% with a 57% probability.
460  David J. Howden
Commodities, the Decade Ahead  461
Silver Forecast return rankings, out of 43 commodities Relative Valuation th
29 Silver 43 Commodity Avg.
0.6 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year nd
11.5 7.6
5.3 5.9
57 39
9 22
10
25
10
22
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 57% probability that silver can achieve this return by June 2025 and 9% by June 2030, ranking the metal 10th and 22nd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that silver will outperform the average commodity over the coming 5year period and deliver average returns (relative to other commodities) over the coming decade. Over the next ten years, I expect the price of silver to increase by 5.3% annually. The forecast range is clustered around this level, ranging from 2.0 to 9.2%. The model explains 77% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that silver will breakeven by June 2030 with a probability of 94%, and that there is a 9% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Silver´s relative valuation of 0.6 standard deviations below its longterm mean is on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms but no more than the average commodity. As such, silver is the 29th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 11.5% over the coming five years, and 5.3% over the coming decade. Relative to other commodities, I expect silver to outperform over the coming five years and deliver comparable performance over the coming decade. Consequently, silver ranks 10th and 25th out of 43 commodities for the 5 and 10year return forecasts.
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where silver is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1900 points to a probable advance in its price that will end June 2026. At a high of $57 by that
462  David J. Howden
Commodities, the Decade Ahead  463
date, silver will have advanced from its March 2020 low in a manner consistent with the other five advances since 1900. Analysis of silver´s longerterm price behavior points to higher prices five and ten years from now, with a boom and bust cycle being completed between the two dates. These longerterm forecasts imply a steady boom going out to the cycle high in 2026, followed by a correction taking silver back to levels comparable to the 2012 highs. By June 2025, I forecast silver to be trading at $31, and $30 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 54% of its 5year returns and 69% of its 10year returns explained since June 1990. In all cases, the price of the meal is not expected to fall below its March 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying silver today and selling it at any date over the coming decade. For example, an expected price of $31 in June 2025 implies an annual rate of return of 11.5% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
Silver Expected return rankings, out of 43 commodities Relative Valuation th
29 Silver 43 Commodity Median
0.6 0.8
Expected average returns: 5Year th
10Year th
13.1 21.2
13.1 8.1
29
8
Overall Rank th
30
In the case of silver, cycle analysis predicts a steady appreciation topping in July 2026, and the period valuation models also forecast price increases, but over different time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 13.1% by buying silver. This expected return is also 13.1% annually over the coming decade. In comparison to the
expected median returns over the coming 5 and 10year periods for other 43 commodities, silver ranks 29th and 8th. This implies that it should yield returns comparable returns relative to the average commodity over both the coming ten years, and superior returns through 2025. Taking the average of the metal´s rankings for these expected returns, silver ranks 30th out of the 43 commodities.
464  David J. Howden
Commodities, the Decade Ahead  465
Soybean Meal Soybean meal is used principally as a protein supplement in animal feeds. Approximately half of soybean meal produced is fed to poultry. A very small amount (less than 2%) is used as a supplement in products for human consumption. China is the world´s largest producer and, along with the United States, accounts for half of global production. Consumption of soybean meal is somewhat more distributed, though China, the United States and the European Union consume well over half of global output.
Soybean Meal China United States Brazil Argentina European Union Rest of World
Production
Consumption
(% World)
(% World)
30 19 14 13 5 19
China United States European Union Brazil Mexico Rest of World
30 14 13 8 3 33
Sources: USDA, 2020
Soybean meal futures trade on the Chicago Board of Trade. The CBOT soybean meal (06) cash contract returned 9.0% to the investor over the past year. Futures trade in lots of 100 tons and are quoted in U.S. dollars per ton.
The Bottom Line Soybean meal closed June 2020 at a price of $289 per ton. Based on historical valuations dating to October 1929 (1,089 months) I estimate the fairvalue price of the commodity to be $365, implying an undervaluation of 0.9 standard deviations. This indicates that it is priced more cheaply today than 82% of all previous months. Analysis of the commodity´s price cycles since 1929 points to the start of a new secular bull market. The May 2020 low of $285 looks to be a longterm bottom. Historically, the median bull market in soybean meal has lasted for three years and increased its price by 130% in real terms. Following this pattern, the current bull market phase should be completed in July 2023 after an additional 128% gain in the commodity´s
466  David J. Howden
Commodities, the Decade Ahead  467
inflationadjusted price. Over the coming 5year period, I forecast the price of soybean meal to increase by 8.1% annually, with a forecast range between 7.7 and 8.8%. The forecast model explains 54% of the variation in the commodity´s 5year returns since June 1990. Consequently, I forecast that soybean meal´s price will breakeven by June 2025 with a 93% probability, and that there is a 36% chance that the commodity´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast soybean meal´s price to increase by 6.0% annually until June 2030 with a forecast range between 5.6 and 6.4%. This model explains 69% of the commodity´s 10year returns since June 1990. As such, there is a 99% probability that soybean meal will breakeven over the coming decade, and a 5% chance that it will yield a return greater than 10%.
Soybean Meal: Forecast Summary 289 365 0.9
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Historical Analysis Since June 1990, the nominal price of soybean meal has increased from $175 per ton to the current close of $289 for an annual return of 1.7%. The alltime nominal high for the commodity came in August 2014 at a price of $594. In real, inflationadjusted terms the commodity´s price has mostly fallen throughout its history. Soybean meal´s real high was in May 1973, with its subsequent low forming in February 1999. As of June 2020, the commodity´s price was lower than 86% of all prior monthly closing prices in real terms. Over longer periods, soybean meal´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the 20th century. Nominal returns have hovered around 2% for most of the commodity´s history, with real returns averaging 1.0% annually between 1929 and 2010. The highest longterm nominal return the investor could have earned was 4.4% and resulted by buying soybean meal in August 2006 and holding it until today. Since inflation over that period averaged 2.7%, the investor earned a somewhat lower real return of 1.7% per year. More recently the commodity´s price has been in a bear market since July 2012. From that month´s high of $578 a collapse of 56% ensued. The May 2020 bottom of $285 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Up May20 Jul23 128 31
5Year Forecast 5Year Annual Forecast Return, % 8.1 5Year Forecast Range, % (7.7, 8.8) 2 0.54 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
93 36
10Year Forecast 10Year Annual Forecast Return, % 6.0 10Year Forecast Range, % (5.6, 6.4) 0.69 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 5
Since 1929 the commodity has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the commodity´s price increase by 130% in real terms, before being corrected by a median decline of 58%. The median bull market has lasted for just over three years, and its subsequent correction has also nearly four years to complete.
468  David J. Howden
Commodities, the Decade Ahead  469
The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the eight completed bull markets in soybean meal has started from an undervalued position, with a median value of 1.1 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.1 standard deviations. Similarly, each of the commodity´s seven completed bear markets that has started from an overvalued position, with a median value of +2.0 standard deviations above the longterm mean. Over the course of each bear market soybean meal continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.0 standard deviations. Soybean Meal: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Dec34 Mar36
41
22
47
n.a.
May37 Jul40
48
22
53
n.a.
Sep50
97
50
58
n.a.
Apr54 Nov60
104
45
61
n.a.
Jun66 Mar70
107
70
45
1.7
May73 Jun74
390
99
77
8.3
Apr77 May85
278
110
78
2.2
Jun88 Feb95
290
149
60
0.7
May97 Feb99
308
125
61
1.4
Jun04 Aug06
310
160
52
2.8
Jul12
578
285
56
2.0
Date Start End Oct31 Dec34
41
146
n.a.
22
48
106
n.a.
Jul46
22
97
208
n.a.
Sep50 Apr54
50
104
89
n.a.
Nov60 Jun66
45
107
118
1.6
Mar70 May73
70
390
388
0.8
Jun74 Apr77
99
278
130
0.3
May85 Jun88
110
290
140
1.6
Feb95 May97
149
308
94
1.0
Feb99 Jun04
125
310
115
1.4
Aug06
Jul12
160
578
221
1.1
May20
Jun20
285
290
2
1.0
Jul40
May20
Real Start Rel. Change, % Val, σ
19
Mar36 May37
Jul46
Price Start End
deviations was also consistent with the median bear market starting relative valuation. At the recent May 2020 low of $285 the commodity was 1.0 standard deviations undervalued, on par with the median starting valuation to a bull market advance. The loss of 3.0 standard deviations of valuation between 2012 and 2020 is also consistent with the median change in the measure during correction phases (3.0 standard deviations). As such, the balance of cycle evidence points to the May 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in May 2020 what can we expect the future to hold? The median bull market in soybean meal has lasted for 3.2 years and gained 130% in real terms. The weakest advance, during 195054 gained 89% in real terms. Since May 2020, the commodity has already gained 2%. As such, I expect the current cycle to gain an additional 128% in real terms by May 2023. This implies an expected annual return of 31% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, soybean meal has increased its valuation within a band of +6.8. standard deviations (the weakest advance increased its valuation by +2.3 and the strongest increased by +9.1 standard deviations). In other words, never in the 90year price history under examination has soybean meal failed to increase its valuation by less than +2.3 standard deviations over its bull market. Since the May 2020 low the commodity´s relative valuation has increased by +0.1 standard deviations, implying significant upside potential.
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 8.1 78 8.3 8.6
Median 3.8 58 2.0 3.0
Min. 1.1 45 0.7 1.7
Max. 6.0 388 0.3 9.1
Median 3.2 130 1.1 3.1
Min. 1.2 89 1.6 2.3
Jul23 2.1 656 130 3.1
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started July 2012. From the starting price of $578 the commodity´s price fell by 56% in real terms. This decline is on par with the median decline of 58% over all recorded soybean meal bear markets. The decline´s starting relative valuation of +2.0 standard
The May 2020 undervaluation of 1.0 standard deviations made the commodity more undervalued than 83% of all previous months. By the time the current bull market reaches its end, I expect soybean meal to be trading at a price which is +2.1 standard deviations overvalued relative to its longterm average.
470  David J. Howden
Commodities, the Decade Ahead  471
In sum, cycle analysis points to soybean meal trading at $656 on July 2023, a price that is +2.1 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for soybean meal starts in October 1929. This means that to date there have been 1,029 5year holding periods and 959 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of soybean meal is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of soybean meal over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of soybean meal as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 8.1% annual gain in soybean meal over the coming 5year period. The forecast range is also strictly positive, ranging from 7.7 to 8.8%. The model explains 54% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of soybean meal will breakeven by June 2025 with a 93% probability, and that the return will exceed 10% with a 36% probability.
Over the next ten years, I expect the price of soybean meal to increase by 6.0% annually. The forecast range is clustered around this level, ranging from 5.6 to 6.4%. The model explains 69% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that soybean meal will breakeven by June 2030 with a probability of 99%, and that there is a 5% chance that its return will exceed 10% over this period.
472  David J. Howden
Commodities, the Decade Ahead  473
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Soybean meal´s relative valuation of 0.9 standard deviations below its longterm mean is not far off the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is moderately undervalued. As such, soybean meal is the 19th most undervalued commodity of the group. I forecast that the commodity will yield an annual return of 8.1% over the coming five years, and 6.0% over the coming decade. Both returns are about on par with the averages for the 42 other commodities (7.6% and 5.9%). Consequently, soybean meal ranks 23rd out of 43 commodities for both the 5 and 10year return forecasts.
Soybean Meal Forecast return rankings, out of 43 commodities Relative Valuation th
18 Soybean Meal 43 Commodity Avg.
0.9 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year rd
10Year rd
5Year th
10Year th
8.1 7.6
6.0 5.9
36 39
5 22
23
23
25
27
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 36% probability that soybean meal can achieve this return by June 2025 and 5% by June 2030, ranking it 36th and 27th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that soybean meal will provide a return comparable to that of the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where soybean meal is in its current price and valuation cycle. The evidence from the price and valuation cycles since 1929 points to a probable advance in its price that will end in July 2023. At a high of $656 by that date, soybean meal will have advanced from its May 2020 low in a manner consistent with the other seven advances since 1929.
Analysis of soybean meal´s longerterm price behavior points to far more muted prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a correction once the current bull market completes, followed by a rally taking soybean meal back to levels not seen since 2014. By June 2025, I forecast soybean meal to be trading at $427, and $517 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 54% of its 5year returns and 69% of its 10year returns explained since June 1990. In all cases, the price of the meal is not expected to fall below its May 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying soybean meal today and selling it at any date over the coming decade. For example, an expected price of $427 in June 2025 implies an annual rate of return of 8.1% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of soybean meal, cycle analysis predicts a swift appreciation topping in May 2023, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is
474  David J. Howden
Commodities, the Decade Ahead  475
to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 32.5% by buying soybean meal. This expected return is somewhat muted at 8.1% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, soybean meal ranks 11th and 22nd. This implies that it should yield returns comparable returns superior to the average commodity over the coming five years, and comparable returns over the next decade. Taking the average of the commodity´s rankings for these expected returns, soybean meal ranks 17th out of the 43 commodities.
Soybean Meal Expected return rankings, out of 43 commodities Relative Valuation th
18 Soybean Meal 43 Commodity Median
0.9 0.8
Expected average returns: 5Year th
10Year nd
32.5 21.2
8.1 8.1
11
22
Overall Rank
Soybean Oil Soybean oil is extracted from the seeds of the soybean and, after palm oil, is the second most consumed oil globally. In addition to the food processing industry, soybean oil is also used in the manufacture of oilbased paints as well as limited medical uses. Brazil is the world´s largest producer, and with the United States produces more than twothirds of the world´s soybean oil supply. China and the United States combine for nearly half of the world´s consumption.
th
17
Global soybean oil output reached 54 million tons in 2019, a 39% increase over the previous decade. This increase came largely as a result of expanded production from China. Output growth in Brazil and Argentina has also been quite strong, combining for an additional four million metric ton of additional annual production over the past decade. Since 2009 world output has increased by an annual rate of 3.4%. Global stocks stood at 2.4 metric tons at the end of 2019 and have remained steady near that level for the past decade. The United States is the world´s largest
476  David J. Howden
Commodities, the Decade Ahead  477
producer, a position it has maintained since records begin in 2009. Soybean oil futures are traded on the Chicago Board of Trade. The CBOT soybean oil (07) cash contract returned 7.0% to the investor over the past year. Futures trade in lots of 60,000 pounds and are quoted in U.S. cents per pound.
The Bottom Line Soybean oil closed June 2020 at a price of $0.26 per pound. Based on historical valuations dating to January 1911 (1,314 months) I estimate the fairvalue price of the commodity to be $0.37, implying an undervaluation of 1.1 standard deviations. This indicates that it is priced more cheaply today than 86% of all previous months.
Soybean Oil: Forecast Summary 26.63 36.95 1.1
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Historical Analysis Since June 1990, the nominal price of soybean oil has increased from $0.25 per pound to the current close of $0.26 for an annual return of 0.1%. The alltime nominal high for the oil came in February 2008 at a price of $0.65. In real, inflationadjusted terms the oil´s price has mostly fallen throughout its history. Soybean oil´s real high was in March 1947, with its subsequent low forming in January 2001. As of June 2020, the oil´s price was lower than 94% of all prior monthly closing prices in real terms.
Up Apr20 Oct21 153 107
5Year Forecast 5Year Annual Forecast Return, % 9.9 5Year Forecast Range, % (9.0, 11.4) 2 0.54 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
94 49
10Year Forecast 10Year Annual Forecast Return, % 7.0 10Year Forecast Range, % (5.1, 9.9) 2 0.64 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
Analysis of the oil´s price cycles since 1911 points to the start of a new secular bull market. The April 2020 low of $0.2545 looks to be a longterm bottom. Historically, the median bull market in soybean oil has lasted for 1.5 years and increased its price by 157% in real terms. Following this pattern, the current bull market phase should be completed in October 2021 after an additional 153% gain in the oil´s inflationadjusted price. Over the coming 5year period, I forecast the price of soybean oil to increase by 9.9% annually, with a forecast range between 9.0 and 11.4%. The forecast model explains 54% of the variation in the oil´s 5year returns since June 1990. Consequently, I forecast that soybean oil´s price will breakeven by June 2025 with a 94% probability, and that there is a 49% chance that the oil´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast soybean oil´s price to increase by 7.0% annually until June 2030 with a forecast range between 5.1 and 9.9%. This model explains 64% of the oil´s 10year returns since June 1990. As such, there is a 98% probability that soybean oil will breakeven over the coming decade, and an 18% chance that it will yield a return greater than 10%.
98 18
478  David J. Howden
Commodities, the Decade Ahead  479
Over longer periods, soybean oil´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 13% for most of the 20th century. Nominal returns have hovered around 1% for most of the oil´s history, with real returns averaging 2.0% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 4.1% and resulted by buying soybean oil in January 2001 and holding it until today. Still, since inflation over that period averaged 2.0%, the investor earned a somewhat muted real return of 2.1% per year. More recently the oil´s price has been in a bear market since February 2008. From that month´s high of $0.6569 a collapse of 68% ensued. The April 2020 bottom of $0.26 looks to be the end of a longterm secular decline which should usher in a multiyear rally. Since 1911 the oil has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the oil´s price increase by 157% in real terms, before being corrected by a median decline of 77%. The median bull market has lasted for a yearandahalf, and its subsequent correction has taken over fiveandahalf years to complete.
deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.5 standard deviations. Similarly, each of the oil´s seven completed bear markets has started from an overvalued position, with a median value of +1.6 standard deviations above the longterm mean. Over the course of each bear market soybean oil continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.9 standard deviations. The most recently completed phase of its cycles was the bear market decline which started in February 2008. From the starting price of $0.65 the oil´s price fell by 68% in real terms. This decline is close to the median decline of 77% over all recorded soybean oil bear markets. The decline´s starting relative valuation of +5.3 standard deviations was significantly more extreme than the median bear market starting relative valuation of +1.6 standard deviations.
Soybean Oil: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Jul46
11.80
11.80
28
1.0
Mar47 Sep68
33.50
7.12
87
2.5
Sep74
Jan76
50.37
15.23
84
6.5
May77 Dec82
32.47
15.88
77
1.6
May84 Aug86
38.83
13.76
82
0.8
Jun88
Jan01
2.46
12.18
74
0.2
Feb08 Apr20
65.69
25.45
68
5.3
Mar41
Date Start End Sep39 Mar41
Price Start End 3.90
11.80
201
1.5
Jul46
Mar47
11.80
33.50
157
0.6
Sep68 Sep74
7.12
50.37
391
1.2
Jan76 May77
15.23
32.47
96
0.1
Dec82 May84
15.88
38.83
131
1.3
Aug86 Jun88
13.76
2.46
112
1.3
Jan01 Feb08
12.18
65.69
347
1.7
Apr20
25.45
26.63
4
1.2
Jun20
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 21.5 87 6.5 7.8
Median 5.6 77 1.6 2.9
Min. 1.3 28 0.2 1.6
Max. 7.1 391 0.1 7.7
Median 1.5 157 1.3 2.5
Min. 0.7 96 1.7 1.5
Oct21 1.3 65.34 157 2.5
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in soybean oil has started from an undervalued position, with a median value of 1.3 standard
At the recent June 2020 low of $0.25 the oil was 1.2 standard deviations undervalued, on par with the median starting valuation of the seven bull markets. The loss of 6.5 standard deviations of valuation between 2008 and 2020 is far greater than the median change in the measure during correction phases (2.9 standard deviations). As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in soybean oil has lasted for 1.5 years and gained 157% in real terms. The weakest advance, during 197677, gained 96% in real terms. Since April 2020, soybean oil has already gained 4%. As such, I expect the current cycle to gain an additional 153% in real terms by October 1921. This implies an expected annual return of 107% by the time the present bull market reaches completion.
480  David J. Howden More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, soybean oil has increased its valuation within a relatively narrow band of +6.2 standard deviations (the weakest advance increased its valuation by +1.5 and the strongest increased by +7.7 standard deviations). In other words, never in the 120year price history under examination has soybean oil failed to increase its valuation by less than +1.5 standard deviations over its bull market. Since the April 2020 low the oil´s relative valuation has increased by +0.1 standard deviations, implying significant upside potential. The April 2020 undervaluation of 1.2 standard deviations made the commodity more undervalued than 86% of all previous months. By the time the current bull market reaches its end, I expect soybean oil to be trading at a price which is +1.3 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to soybean oil trading at $0.65 on October 2021, a price that is +1.3 standard deviations overvalued.
Commodities, the Decade Ahead  481 Both models use the relative valuation of soybean oil as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for soybean oil starts in January 1911. This means that to date there have been 1,254 5year holding periods and 1,194 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of soybean oil is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of soybean oil over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run.
I forecast a 9.9% annual gain in soybean oil over the coming 5year period. The forecast range is also strictly positive, ranging from 9.0 to 11.4%. The model explains 54% of the variation of the 300 5year returns of the seed oil since June 1990. Given this explanatory power of the model, I estimate that the price of soybean oil will breakeven by June 2025 with a 94% probability, and that the return will exceed 10% with a 49% probability. Over the next ten years, I expect the price of soybean oil to increase by 7.0% annually. The forecast range is clustered around this level, ranging from 5.1 to 9.9%. The model explains 64% of the variance in the seed oil´s 240 10year returns since June 1990. As such, I estimate that soybean oil will breakeven by June 2030 with a probability of 98%, and that there is a 18% chance that its return will exceed 10% over this period.
482  David J. Howden
Commodities, the Decade Ahead  483
Soybean Oil Forecast return rankings, out of 43 commodities Relative Valuation th
14 Soybean Oil 43 Commodity Avg.
1.1 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year th
9.9 7.6
7.0 5.9
49 39
18 22
16
19
16
18
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where soybeans are in their current price and valuation cycle. The evidence from the price and valuation cycles since 1911 points to a probable advance in the oil´s price that will end in October 2021. At a high of $0.65 by that date, soybean oil will have advanced from its April 2020 low in a manner consistent with the other seven advances since 1911.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Soybean oil´s relative valuation of 1.1 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, soybean oil is the 14th most undervalued commodity of the group. I forecast that the oil will yield an annual return of 9.9% over the coming five years, and 7.0% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, soybean oil ranks 16th and 19th out of 43 commodities for the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 49% probability that soybean oil can achieve this return by June 2025 and 18% by June 2030, ranking the seed oil 16th and 18th out of the 43 markets for both probabilities. Given this evidence, it is likely that soybean oil will outperform the average commodity over both the coming 5and 10year periods.
Analysis of soybean oil´s longerterm price behavior points to far more muted prices five years from now, at least relative to its cycle high, with a continued advance going out to 2030. These longerterm forecasts imply a correction once the current bull market completes, followed by a rally taking soybean oil back to its 2011 highs. By June 2025, I forecast soybean oil to be trading at $0.42, and $0.57 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 54% of its 5year returns and 64% of its 10year returns explained since June 1990. In all cases, the price of the oil
484  David J. Howden
Commodities, the Decade Ahead  485
is not expected to fall below its April 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying soybean oil today and selling it at any date over the coming decade. For example, an expected price of $0.42 in June 2025 implies an annual rate of return of 9.9% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of soybean oil, cycle analysis predicts a swift appreciation topping in October 2021, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 32.6% by buying soybean oil. This expected return is somewhat muted at 8.1% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, soybean oil ranks 10th and 23rd. This implies that it should yield returns higher than the average commodity over the coming five years, and comparable returns over the next decade. Taking the average of the oil´s rankings for these expected returns, soybean oil ranks 13th out of the 43 commodities.
Soybean Oil Expected return rankings, out of 43 commodities Relative Valuation th
14 Soybean Oil 43 Commodity Median
1.1 0.8
Expected average returns: 5Year th
10Year rd
32.6 21.2
8.1 8.1
10
23
Soybeans The soybean is the most widely grown legume in the world. The bean is used for food both in its unfermented form (soy milk, tofu, etc.) and, more traditionally, in its fermented form (soy sauce, natto, etc.). China accounts for approximately half of global production of the bean. In the United States the bulk of soybean production goes to animal feed, and allows for industrialscale farming of chickens, hogs, and turkeys. Soybean oil is also used in a large variety of processed foods. The United States and Brazil combine to produce nearly 70% of the world´s supply, though China is the world´s largest consumer by a large margin.
Soybeans Production
Consumption
(% World)
United States Brazil Argentina China India Rest of World
35 34 11 4 4 12
(% World)
China United States Argentina Brazil India Rest of World
26 17 11 9 2 35
Sources: Food and Agriculture Organization of the United Nations, 2018; IndexBox, 2020
Overall Rank th
13
Global soybean output reached 348 million tons in 2018, a 50% increase over the previous decade. This increase came largely as a result of expanded production in Brazil where output has almost doubled since 2009 (by 58 million tons annually). Production growth in the United States is also quite strong, up 53% over the past decade, and more than offsetting the 18% loss in Argentine output. The United States remains the world´s largest producer, a position it has held continually since records begin in 1961. Given current growth rates, this dominance should end in by 2021 as Brazil becomes the world´s number one producer. Since 1999 world output has increased at an annual rate of 4.3%. This rapid growth is mostly the response to the increased global demand for meat products, which use soybeanderived food in industrial production.
486  David J. Howden
Commodities, the Decade Ahead  487 Globally, there are 124 million hectares of land devoted to soybean production. This area is 30% more than there was a decade ago and, since 1999, the area of soybeans the world has harvested has grown by 2.9% annually. These trends have been in place for more than 30 years. Increasing yields have added to these gradually increasing harvest areas and contributed to total supply growth. Globally, soybeans yield 2.8 metric tons to the hectare. These yields are more than 16% higher than they were a decade ago and, since 1999, they have grown by 1.3% annually. World soybean stocks ended 2019 at 102 million metric tons. Globally there has been an average annual supply surplus of 5.6 million metric tons. Recent increases in production have increased soybean stocks by 5.1% annually since 2015. Soybeans trade on the Chicago Board of Trade. The CBOT soybeans (S) cash contract returned 0.0% to the investor over the past year. Futures trade in lots of 5,000 bushels and are quoted in U.S. cents per bushel.
annually, with a forecast range between 7.9 and 10.3%. The forecast model explains 56% of the variation in the bean´s 5year returns since June 1990. Consequently, I forecast that the price of soybeans will breakeven by June 2025 with a 94% probability, and that there is a 42% chance that the bean´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast the price of soybeans to increase by 6.1% annually until June 2030 with a forecast range between 4.5 and 8.4%. This model explains 70% of the bean´s 10year returns since June 1990. As such, there is a 99% probability that soybeans will breakeven over the coming decade, and an 8% chance that it will yield a return greater than 10%.
Soybeans: Forecast Summary 866 1,082 0.9
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Sep18 May22 85 39
5Year Forecast 5Year Annual Forecast Return, % 8.8 5Year Forecast Range, % (7.9, 10.3) 0.56 Adjusted R2 Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
The Bottom Line Soybeans closed June 2020 at a price of $8.66 per bushel. Based on historical valuations dating to October 1917 (1,232 months) I estimate the fairvalue price of the commodity to be $10.82, implying an undervaluation of 0.9 standard deviations. This indicates that it is priced more cheaply today than 81% of all previous months. Analysis of the bean´s price cycles since 1917 points to the continuation of the secular bull market that started in September 2018 at the bottom of $7.74. Historically, the median bull market in soybeans has lasted for 3.7 years and increased its price by 104% in real terms. Following this pattern, the current bull market phase should be completed in May 2022 after an additional 85% gain in the bean´s inflationadjusted price. Over the coming 5year period, I forecast the price of soybeans to increase by 8.8%
94 42
10Year Forecast 10Year Annual Forecast Return, % 6.1 10Year Forecast Range, % (4.5, 8.4) 0.70 Adjusted R2 Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 8
488  David J. Howden
Historical Analysis Since June 1990, the nominal price of soybeans has increased from $6.15 per bushel to the current close of $8.66 for an annual return of 1.1%. The alltime nominal high for the bean came in August 2012 at a price of $17.78. In real, inflationadjusted terms the bean´s price has mostly trended in the $1 to $3 range throughout its history with some intermittent price spikes. Soybean´s real high was in February 1918, with its subsequent low forming October 2001. As of June 2020, the bean´s price was lower than 98% of all prior monthly closing prices in real terms. More recently the bean´s price has been in a bear market between August 2012 and September 2018. From the 2012 high of $17.78 a collapse of 60% ensued. The August 2018 bottom of $7.74 looks to be the end of a longterm secular decline, and the rally since then should continue to new highs.
Commodities, the Decade Ahead  489 to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in soybeans has started from an undervalued position, with a median value of –1.3 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +3.6 standard deviations. Similarly, each of the bean´s eight completed bear markets has started from an overvalued position, with a median value of +2.0 standard deviations above the longterm mean. Over the course of each bear market soybeans continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.2 standard deviations. Soybeans: Historical Cycle Summary Declines
Advances
Date Start End May48 Oct49
Price Start End 422
215
53
0.3
Apr54 Nov60
411
212
54
0.0
Jun66 Sep69
377
235
46
0.5
May73 Dec75
1,157
446
68
10.7
Apr77 Feb87
983
465
75
3.3
Jun88
939
409
71
0.6
Apr04 Aug06
1,015
512
53
3.4
Aug12 Sep18
1,778
774
60
3.8
Oct01
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Oct49 Apr54
215
411
84
2.1
Nov60 Jun66
212
377
64
1.4
Sep69 May73
235
1,157
293
1.4
Dec75 Apr77
446
983
104
0.3
Feb87 Jun88
465
939
91
1.0
Oct01 Apr04
409
1,015
134
1.6
Aug06 Aug12
512
1,778
207
0.8
Sep18
774
867
19
1.1
Jun20
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Over longer periods, soybean´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 12% for most of the 20th century. Nominal returns have hovered around 1% for most of the bean´s history, with real returns averaging 1.4% annually between 1917 and 2010. The highest longterm nominal return the investor could have earned was 4.1% and resulted by buying soybeans in October 2001 and holding it until today. Since inflation over that period averaged 2.0%, the investor earned a real gain of around 2.1% per year. Since 1917 the bean has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the bean´s price increase by 104% in real terms, before being corrected by a median decline of 57%. The median bull market has lasted for just under four years, and its subsequent correction has taken nearly five years
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 13.3 75 10.7 11.0
Median 4.7 57 2.0 3.2
Min. 1.4 46 0.3 1.4
Max. 6.0 293 0.3 12.1
Median 3.7 104 1.3 3.6
Min. 1.3 64 2.1 1.6
May22 2.5 1,577.96 104 3.6
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in August 2012. From the starting price of $17.78 the bean´s price fell by 60% in real terms. This decline is on par with the median decline of 57% over all recorded soybean bear markets. The decline´s starting relative valuation of +3.8 standard deviations was significantly more overvalued than the median bear market starting relative valuation of +2.0 standard deviations. At the September 2018 low of $7.74 the bean was 1.1 standard deviations undervalued. This made the bean marginally less undervalued than the median start to a bull
490  David J. Howden market advance (1.3 standard deviations). The loss of 4.9 standard deviations of valuation between 2012 and 2018 is also more extreme than the median change in the measure during correction phases (3.2 standard deviations). As such, the balance of cycle evidence points to the September 2018 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in September 2018 what can we expect the future to hold? The median bull market in soybeans has lasted for nearly four years and gained 104% in real terms. The weakest advance, during 196066, gained 64% in real terms. Since April 2018, the bean has already gained 19%. As such, I expect the current cycle to gain an additional 85% in real terms by May 2022. This implies an expected annual return of 39% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, soybeans have increased their valuation within a band of +10.5 standard deviations (the weakest advance increased its valuation by +1.6 and the strongest increased by +12.1 standard deviations). In other words, never in the 103year price history under examination have soybeans failed to increase their valuation by less than +1.6 standard deviations over a bull market. Since the August 2018 low the bean´s relative valuation has increased by +0.4 standard deviations, implying significant upside potential.
The August 2018 undervaluation of 1.1 standard deviations made the commodity more undervalued than 86% of all previous months. By the time the current bull market reaches its end, I expect soybeans to be trading at a price which is +2.5 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to soybeans trading at $15.78 on May 2022, a price that is +2.5 standard deviations overvalued.
Commodities, the Decade Ahead  491
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for soybeans starts in October 1917. This means that to date there have been 1,173 5year holding periods and 1,113 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of soybeans is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of soybeans over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of soybeans as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 8.8% annual gain in soybeans over the coming 5year period. The forecast range is also strictly positive, ranging from 7.9 to 10.3%. The model explains 56% of the variation of the 300 5year returns of the bean since June 1990. Given this explanatory power of the model, I estimate that the price of soybeans will breakeven by June 2025 with a 94% probability, and that the return will exceed 10% with a 42% probability.
492  David J. Howden
Commodities, the Decade Ahead  493
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Soybean´s relative valuation of 0.9 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued not only in absolute terms, but also relative to other commodities. As such, soybeans are the 19th most undervalued commodity of the group. I forecast that the bean will yield an annual return of 8.8% over the coming five years, and 6.1% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, soybeans rank 20th and 21st out of 43 commodities for the 5 and 10year return forecasts.
Over the next ten years, I expect the price of soybeans to increase by 6.1% annually. The forecast range is clustered around this level, ranging from 4.5 to 8.4%. The model explains 70% of the variance in the bean´s 240 10year returns since June 1990. As such, I estimate that soybeans will breakeven by June 2030 with a probability of 99%, and that there is an 8% chance that its return will exceed 10% over this period.
Soybeans Forecast return rankings, out of 43 commodities Relative Valuation th
19 Soybeans 43 Commodity Avg.
0.9 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year st
5Year th
10Year rd
8.8 7.6
6.1 5.9
42 39
8 22
20
21
19
23
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 42% probability that soybeans can achieve this return by June 2025 and an 8% by June 2030, ranking the bean 19th and 23rd out of the 43 markets for both probabilities. Given this evidence, it is highly likely that soybeans will offer comparable performance to the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where soybeans are in their current price and valuation cycle. The evidence from the price and valuation cycles since 1917 points to a probable advance in soybean´s price that will end in May 2022. At a high of $15.77 by that date, soybeans will have advanced from their September 2018 low in a manner consistent with the other seven advances since 1917.
494  David J. Howden
Commodities, the Decade Ahead  495 valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 24.9% by buying soybeans. This expected return is somewhat muted at 8.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, soybeans rank 17th and 19th. This implies that they should yield returns comparable to the average commodity over both the coming five and ten years. Taking the average of the bean´s rankings for these expected returns, soybeans rank 18th out of the 43 commodities.
Soybeans Expected return rankings, out of 43 commodities Relative Valuation th
19 Analysis of soybean´s longerterm price behavior points to far more muted prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a correction once the current bull market completes, followed by a rally taking soybeans near their 2012 highs. By June 2025, I forecast soybeans to be trading at $13.20, and $15.69 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 56% of its 5year returns and 69% of its 10year returns explained since June 1990. In all cases, the price of soybeans is not expected to fall below its September 2018 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying soybeans today and selling them at any date over the coming decade. For example, an expected price of $13.20 in June 2025 implies an annual rate of return of 8.8% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of soybeans, cycle analysis predicts a swift appreciation topping in May 2022, and the period
Soybeans 43 Commodity Median
0.9 0.8
Expected average returns: 5Year th
10Year th
24.9 21.2
8.8 8.1
17
19
Overall Rank th
18
496  David J. Howden
Commodities, the Decade Ahead  497
Sugar Sugar is the generic name for the sweettasting carbohydrate commonly added to food. Sugar is produced primarily from sugar cane, with a smaller amount coming from sugar beets. (Globally about seven times more sugar is processed from cane than beets.)
Sugar Production
Consumption
(% World)
India Brazil European Union Thailand China Rest of World
19 16 10 9 6 40
(% World)
India European Union China Brazil United States Rest of World
15 10 9 6 6 54
Source: International Sugar Organization, 2018
India accounts for about onefifth of global production of sugar and, along with Brazil and the European Union, accounts for nearly half of global sugar production. Consumption is less concentrated, though India consumes nearly oneseventh of global production. Global sugar output reached 2.1 billion tons in 2018, a 12% increase over the previous decade. This increase came largely as a result of expanded production from Brazil, through the increased use of sugar cane. Brazilian output has increased by 16% over the past decade, for an extra 101 million metric tons of sugar annually. The world´s largest producer of cane sugar is India, a position it has held since overtaking Brazil in 1982. Since 1999 world output has increased at an annual rate
498  David J. Howden of 1.8%. Globally, there are 26 million hectares of land devoted to cane sugar production. This area is 8.8% more than there was a decade ago and, since 1999, the area of sugar cane the world has harvested has grown by 1.6% annually (although land use has levelled off since 2014). Increasing yields have added to these gradually increasing harvest areas and contributed to total supply growth. Globally, cane sugar yields 72.6 metric tons to the hectare. Yields are not appreciably higher than they were a decade ago, and since 1999 they have increased by only 0.5% annually. Over the past 30 years yields have increased between 12% annually. Since 2014 yields have increased noticeably, and the resumption of the longerterm productivity gains appears to be solid. Global sugar stocks are near their alltime highs at 44.4 million metric tons in 2019. Over the past decade, the average annual surplus of sugar production has been roughly 1.5 million metric tons, leaving an average ending inventory of 42.4 million tons, implying a longrun growth rate of global sugar inventories of 4.4% annually. With such growth to stocks, sugar demand should not face any supplyside constraint for the foreseeable future. Sugar became exchange traded when sugar futures were added to the Coffee Exchange in the City of New York in 1914 to form the New York Coffee and Sugar Exchange. After merging with the New York Board of Trade in 1998 it has, since 2007, been a subsidiary of the Intercontinental Exchange. The sugar no. 11 contract is the world´s benchmark for sugar cane pricing. The ICE sugar no. 2 (SB) cash contract returned 9.7% to the investor over the past year. Futures trade in lots of 112,000 pounds and are quoted in U.S. cents per pound.
The Bottom Line Sugar closed June 2020 at a price of $0.11 per pound. Based on historical valuations
Commodities, the Decade Ahead  499 dating to January 1890 (1,566 months) I estimate the fairvalue price of the commodity to be $0.16, implying an undervaluation of 1.0 standard deviations. This indicates that it is priced more cheaply today than 83% of all previous months.
Sugar: Forecast Summary 11.84 16.78 1.0
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Apr20 Aug23 357 63
5Year Forecast 5Year Annual Forecast Return, % 8.3 5Year Forecast Range, % (8.2, 8.5) 2 0.47 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
88 41
10Year Forecast 10Year Annual Forecast Return, % 6.5 10Year Forecast Range, % (5.1, 8.5) 2 0.68 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
98 15
Analysis of the sweetener´s price cycles since 1900 points to the start of a new secular bull market. The April 2020 low of $0.10 looks to be a longterm bottom. Historically, the median bull market in sugar has lasted for 3.3 years and increased its price by 370% in real terms. Following this pattern, the current bull market phase should be completed in August 2023 after an additional 357% gain in its inflationadjusted price. Over the coming 5year period, I forecast the price of sugar to increase by 8.3% annually, with a forecast range between 8.2 and 8.5%. The forecast model explains 47% of the variation in the sweetener´s 5year returns since June 1990. Consequently, I forecast that sugar´s price will breakeven by June 2025 with an 88% probability, and that
500  David J. Howden there is a 41% chance that the sweetener´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast sugar´s price to increase by 6.5% annually until June 2030 with a forecast range between 5.1 and 8.5%. This model explains 68% of the sweetener´s 10year returns since June 1990. As such, there is a 98% probability that sugar will breakeven over the coming decade, and a 15% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of sugar has decreased from $0.12 per pound to the current close of $0.11 for an annual return of 0.2%. The alltime nominal high for the sweetener came in November 1974 at a price of $0.53. In real, inflationadjusted terms the sweetener´s price has mostly fallen throughout its history. Sugar´s real high was in November 1974, with its subsequent low forming in January 1985. As of June 2020, the sweetener´s price was lower than 85% of all prior monthly closing prices in real terms. Over longer periods, sugar´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 2% for most of the 20th century. Nominal returns have hovered around 1% for most of its price history, with real returns averaging –2.0% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 4.2% and resulted by buying sugar in June 1985 and holding it until today. Since inflation over that period averaged 1.7%, the investor would have earned a real return of 2.5% per year.
Commodities, the Decade Ahead  501 $0.10 looks to be the end of a longterm secular decline which should usher in a multiyear rally. Since 1900 the sweetener has gone through seven complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the sweetener´s price increase by 370% in real terms, before being corrected by a median decline of 81%. The median bull market has lasted for just over three years, and its subsequent correction has taken about five years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the seven completed bull markets in sugar has started from an undervalued position, with a median value of 1.2 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +4.3 standard deviations. Similarly, each of the sweetener´s eight completed bear markets with relative valuation data available has started from an overvalued position, with a median value of +3.0 standard deviations above the longterm mean (with the exception of the 19902000 bear market which started from a slightly undervalued position). Over the course of each bear market sugar continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 4.0 standard deviations. Sugar (No.11): Historical Cycle Summary Declines
20.80
3.60
79
8.5
May23 Oct53
7.90
3.08
76
0.8
Feb57 Jan62
6.38
2.21
68
2.1
Oct63 Dec66
12.40
1.34
90
6.5
Nov74 Sep77
53.00
6.75
89
8.7
Oct80 Jun85
42.07
2.76
95
0.6
Apr90 Feb00
15.87
5.18
76
0.2
Jan11
37.54
10.39
84
3.8
Apr20
Price Start End
Advances
Date Start End May20 Jan22
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jan22 May23
3.60
7.90
120
2.3
Oct53 Feb57
3.08
6.38
101
2.2
Jan62
Oct63
2.21
12.40
446
0.7
Dec66 Nov74
1.34
53.00
2,426
1.8
Sep77 Oct80
6.75
42.07
350
0.7
Jun85 Apr90
2.76
15.87
370
1.1
Feb00
Jan11
5.18
37.54
743
0.8
Apr20 Jun20
10.39
11.84
13
1.2
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
More recently the sweetener´s price has been in a bear market since January 2011. From that month´s high of $0.37 a collapse of 84% ensued. The April 2020 bottom of
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 30.4 95 8.7 10.8
Median 4.8 81 3.0 4.0
Min. 1.7 68 8.7 10.8
Max. 10.9 2,426 0.7 10.5
Median 3.3 370 1.2 4.3
Min. 1.3 101 2.3 0.9
Aug23 3.1 48.83 370 4.3
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
502  David J. Howden The most recently completed phase of its cycles was the bear market decline which started in January 2011. From the starting price of $0.37 the sweetener´s price fell by 84% in real terms. This decline is on par with the median decline of 81% over all recorded sugar bear markets. The decline´s starting relative valuation of +3.8 standard deviations was marginally higher than the median bear market starting relative valuation of +3.0 standard deviations. At the recent April 2020 low of $0.10 sugar was 1.2 standard deviations undervalued, right on par with the median start to a bull market advance. The loss of 5.0 standard deviations of valuation between 2011 and 2020 is a little more severe than the median change in the measure during correction phases (4.0 standard deviations). As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in sugar has lasted for just over three years and gained 370% in real terms. The weakest advance, during 195357, gained 101% in real terms. Since April 2020, the sweetener has already gained 13%. As such, I expect the current cycle to gain an additional 357% in real terms by August 2023. This implies an expected annual return of 63% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, sugar has increased its valuation within a band of +9.6 standard deviations (the weakest advance increased its valuation by +0.9 and the strongest increased by +10.5 standard deviations). In other words, never in the 120year price history under examination has sugar failed to increase its valuation by less than +0.9 standard deviations over its bull market. Since the April 2020 low the sweetener´s relative valuation has increased by +0.2 standard deviations, implying significant upside potential.
Commodities, the Decade Ahead  503 The April 2020 undervaluation of 1.2 standard deviations made the commodity more undervalued than 88% of all previous months. By the time the current bull market reaches its end, I expect sugar to be trading at a price which is +3.1 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to sugar trading at $0.48 on August 2023, a price that is +3.1 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for sugar starts in January 1890. This means that to date there have been 1,506 5year holding periods and 1,446 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of sugar is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of sugar over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of sugar as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 8.3% annual gain in sugar over the coming 5year period. The forecast range is also strictly positive, ranging from 8.2 to 8.5%. The model explains 47% of the variation of the 300 5year returns of the commodity since June 1990. Given this explanatory power of the model, I estimate that the price of sugar will breakeven by June 2025 with an 88% probability, and that the return will exceed 10% with a 41% probability. ç
504  David J. Howden
Commodities, the Decade Ahead  505
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Sugar´s relative valuation of 1.0 standard deviations below its longterm mean is lower than the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is highly undervalued. As such, sugar is the 16th most undervalued commodity of the group. I forecast that the sweetener will yield an annual return of 8.3% over the coming five years, and 6.5% over the coming decade. Both returns are about on par with the averages for the 42 other commodities (7.6% and 5.9%). Consequently, sugar ranks 22nd and 20th out of 43 commodities for the 5 and 10year return forecasts.
Sugar Forecast return rankings, out of 43 commodities Over the next ten years, I expect the price of sugar to increase by 6.5% annually. The forecast range is clustered around this level, ranging from 5.1 to 8.5%. The model explains 68% of the variance in the commodity´s 240 10year returns since June 1990. As such, I estimate that sugar will breakeven by June 2030 with a probability of 98%, and that there is a 15% chance that its return will exceed 10% over this period.
Relative Valuation th
16 Sugar 43 Commodity Avg.
1.0 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year nd
10Year th
5Year st
10Year th
8.3 7.6
6.5 5.9
41 39
15 22
22
20
21
19
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 41% probability that sugar can achieve this return by June 2025 and 15% by June 2030, ranking the commodity 21st and 19th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that sugar will provide average performance relative to the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where sugar is in its current price and valuation cycle. The evidence from its price and valuation cycles since 1900 points to a probable surge in sugar´s price that will end in August 2023. At a high of $0.48 by that date, sugar will have advanced from its April 2020 low in a manner consistent with the other seven advances since 1900.
506  David J. Howden
Commodities, the Decade Ahead  507 but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 63.8% by buying sugar. This expected return is somewhat muted at 8.3% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods for other 43 commodities, sugar ranks 2nd and 21st. This implies that it should yield returns far greater than the average commodity over both the coming five years, and comparable returns over the next decade. Taking the average of the sweetener´s rankings for these expected returns, sugar ranks 15th out of the 43 commodities.
Sugar Expected return rankings, out of 43 commodities Relative Valuation th
16 Analysis of sugar´s longerterm price behavior points to far more muted prices five years from now, with a continued advance going out to 2030. These longerterm forecasts imply a sharp collapse once the current bull market completes, followed by a rally taking sugar above its 2012 high. By June 2025, I forecast sugar to be trading at $0.17, and $0.22 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 47% of its 5year returns and 68% of its 10year returns explained since June 1990. In all cases, the price of sugar is not expected to fall below its April 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying sugar today and selling it at any date over the coming decade. For example, an expected price of $0.17 in June 2025 implies an annual rate of return of 8.3% over the next five years. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard. In the case of sugar, cycle analysis predicts a swift appreciation topping in August 2023, and the period valuation models also forecast price increases,
Sugar 43 Commodity Median
1.0 0.8
Expected average returns: 5Year
10Year
nd
21
63.8 21.2
8.3 8.1
2
st
Overall Rank th
15
508  David J. Howden
Commodities, the Decade Ahead  509
Tin Tin was one of metals first extracted from the earth, dating back to at least the early Bronze Age over 3,000 years ago. The silverywhite metal is widely used by the manufacturing industry in the form of solder. It is soft and highly malleable, with a low melting point that makes it easy to work with. China accounts for nearly onethird of global production of the metal, and together with Indonesia accounts for over half of global mined output. Global tin output reached 310,000 tons in 2019, a 23% increase over the Tin previous decade. World production Production remained fairly constant at less than 200,000 tons until the mid2000s. A (% World) large output increase, most significantly seen until 2005, was the China 27 result of increased output in China and Indonesia 26 Indonesia. Since 2009, Chinese output has fallen by 26% (30 thousand tons Burma 17 annually). Indonesia and Burma have Peru 6 more than compensated for this drop Bolivia 5 off in production, increasing their tin production by 34 and 53 thousand Rest of World 18 tons annually compared with 2009 Source: USGS, 2020 levels. China remains the world´s largest producer of mined zinc, a position it has held continually since 1990 (except for 2002). This dominance looks set to end as Indonesia is poised to overtake it as the world´s largest producer before the end of 2020. Recycled scrap remains an important source of tin augmenting smelted production. In the United States, approximately 25% of tin consumption comes from recycled sources. Since 1999 world output has increased at an annual rate of 1.8%. There are approximately 4.7 million tons of unmined tin in reserves globally. Over the past decade, worldwide reserves have decreased by 1.7% annually. Twothirds of
510  David J. Howden
Commodities, the Decade Ahead  511 this decline came from China, where reserves fell by 600 thousand tons over the period. At current rate of resource extraction, global zinc reserves should be halved by 2059. China maintains the world´s largest tin reserves at 1.1 million tons (23% of global reserves). Although just five countries account for 73% of global reserves, the metal is found widely throughout the world. The United States has negligible reserves and has not mined tin since 1993. The London Metal Exchange is the primary hub for tin trading since first launching contracts in 1989, with small amounts of the metal being contracted on the Kuala Lumpur Tin Market and the Indonesia Tin Exchange. The LME tin (SN) cash contract returned 10.4% to the investor over the past year. Futures trade in lots of 5 tons and are quoted in U.S. dollars per metric ton.
annually, with a forecast range between 10.2 and 13.8%. The forecast model explains 55% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that tin´s price will breakeven by June 2025 with a 93% probability, and that there is a 56% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast tin´s price to increase by 8.3% annually until June 2030 with a forecast range between 5.8 and 11.1%. This model explains 81% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that tin will breakeven over the coming decade, and a 28% chance that it will yield a return greater than 10%.
Tin: Forecast Summary 16,847 21,438 0.8
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Mar20 Mar25 150 21
5Year Forecast 5Year Annual Forecast Return, % 11.2 5Year Forecast Range, % (10.2, 13.8) 2 0.55 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
93 56
10Year Forecast
The Bottom Line Tin closed June 2020 at a price of $16,847 per metric ton. Based on historical valuations dating to June 1880 (1,681 months) I estimate the fairvalue price of the commodity to be $21,438, implying an undervaluation of 0.8 standard deviations. This indicates that it is priced more cheaply today than 79% of all previous months. Analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The March 2020 low of $14,401 looks to be a longterm bottom. Historically, the median bull market in tin has lasted for 5.0 years and increased its price by 168% in real terms. Following this pattern, the current bull market phase should be completed in March 2025 after an additional 150% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of tin to increase by 11.2%
10Year Annual Forecast Return, % 8.3 10Year Forecast Range, % (5.8, 11.1) 2 0.81 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 28
512  David J. Howden
Historical Analysis Since June 1990, the nominal price of tin has increased from $5,945 per ton to the current close of $16,847 for an annual return of 3.5%. The alltime nominal high for the metal came in April 2011 at a price of $32,275. In real, inflationadjusted terms the metal´s price has been quite volatile throughout its history. Tin´s real high was in November 1979, with its subsequent low forming in September 2001. As of June 2020, the metal´s price was lower than 64% of all prior monthly closing prices in real terms. Over longer periods, tin´s price has just kept pace with general price inflation, resulting in a real yield of around 0% for most of the 20th century. Nominal returns have hovered around 3% for most of the metal´s history, with real returns averaging 0.1% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 8.7% and resulted by buying tin in August 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor earned a real return of 6.7% per year. More recently the metal´s price has been in a bear market since August 2011. From that month´s high of $32,275 a collapse of 61% ensued. The March 2020 bottom of $14,401 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  513 bull market phase of a cycle. Each of the six completed bull markets in tin has started from an undervalued position (except for the bull market of 194651 which started from a slightly overvalued position), with a median value of 1.2 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.8 standard deviations. Similarly, each of the metal´s seven completed bear markets has started from an overvalued position, with a median value of +0.7 standard deviations above the longterm mean (with the exception of the 1918  1921 bear market which started from a slightly undervalued position). Over the course of each bear market tin continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.1 standard deviations. Tin: Historical Cycle Summary Declines Price Start End
Advances
Date Start End Jun18 Jun21
1,852
623
72
0.5
Aug26 Sep31
1,359
498
58
0.5
Jun34
Jul46
1,088
1,177
27
0.7
Jun51
Jun58
2,650
1,983
33
1.3
Nov79 Sep01
16,521
3,710
90
0.5
Apr08 Dec08 23,600
10,355
55
6.7
Apr11 Mar20 32,275
14,401
61
4.5
Real Start Rel. Change, % Val, σ
Date Start End
Price Start End
Real Start Rel. Change, % Val, σ
Jun21 Aug26
623
1,359
120
2.5
Sep31
Jun34
498
1,088
145
1.9
Jul46
Jun51
1,177
2,650
72
0.4
Jun58 Nov79
1,983
16,521
217
0.8
Sep01 Apr08
3,710
23,600
428
1.2
Dec08 Apr11
10,355
32,275
191
1.2
Mar20 Jun20
14,401
16,847
18
1.2
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the metal has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 168% in real terms, before being corrected by a median decline of 58%. The median bull market has lasted for five years, and its subsequent correction has taken seven years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and
Max. 21.8 90 6.7 5.7
Median 7.0 58 0.7 2.1
Min. 0.7 27 0.5 0.3
Max. 21.4 428 1.2 7.9
Median 5.0 168 1.2 2.8
Min. 2.3 72 2.5 0.9
Mar25 1.6 38,617 168 2.8
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in April 2011. From the starting price of $32,275 the metal´s price fell by 61% in real terms. This decline is on par with the median decline of 58% over all recorded tin bear markets. The decline´s starting relative valuation of +4.5 standard deviations was far greater than the median bear market starting relative valuation of +0.7 standard deviations. At the recent March 2020 low of $14,401 the metal was 1.2 standard deviations undervalued. This made the metal marginally more undervalued than the median start to a bull market advance (1.2 standard deviations). The loss of 5.7 standard deviations of valuation between 2011 and 2020 is also far greater than the median change in the
514  David J. Howden measure during correction phases (2.1 standard deviations). As such, the balance of cycle evidence points to the April 2020 low marking the end of a bear market decline and the start of a fresh secular bull market. If a new bull market did start in April 2020 what can we expect the future to hold? The median bull market in tin has lasted for five years and gained 168% in real terms. The weakest advance, during 194651, gained 72% in real terms. Since April 2020, the metal has already gained 18%. As such, I expect the current cycle to gain an additional 150% in real terms by March 2025. This implies an expected annual return of 21% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, tin has increased its valuation within a band of +7.0 standard deviations (the weakest advance increased its valuation by +0.9 and the strongest increased by +7.9 standard deviations). In other words, never in the 120year price history under examination has tin failed to increase its valuation by less than +0.9 standard deviations over its bull market. Since the March 2020 low the metal´s relative valuation has increased by +0.4 standard deviations, implying significant upside potential.
Commodities, the Decade Ahead  515
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for tin starts in June 1880. This means that to date there have been 1,621 5year holding periods and 1,561 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of tin is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future.
The March 2020 undervaluation of 1.2 standard deviations made the commodity more undervalued than 88% of all previous months. By the time the current bull market reaches its end, I expect tin to be trading at a price which is +1.6 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to tin trading at $38,617 on March 2025, a price that is +1.6 standard deviations overvalued. I have developed two models to forecast the return of tin over these two different time periods – five years and ten years. In general, the 10year forecast model is more
516  David J. Howden robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of tin as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast an 11.2% annual gain in tin over the coming 5year period. The forecast range is also strictly positive, ranging from 10.2 to 13.8%. The model explains 55% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of tin will breakeven by June 2025 with a 93% probability, and that the return will exceed 10% with a 56% probability.
Commodities, the Decade Ahead  517 commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Tin´s relative valuation of 0.8 standard deviations below its longterm mean is on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but by not much more than the average commodity. As such, tin is the 21st most undervalued commodity of the group.
Tin Forecast return rankings, out of 43 commodities Relative Valuation th
24 Tin 43 Commodity Avg.
Over the next ten years, I expect the price of tin to increase by 8.3% annually. The forecast range is clustered around this level, ranging from 5.8 to 11.1%. The model explains 81% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that tin will breakeven by June 2030 with a probability of 99%, and that there is a 28% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other
0.8 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year th
11.2 7.6
8.3 5.9
56 39
28 22
13
14
11
14
I forecast that the metal will yield an annual return of 11.2% over the coming five years, and 8.3% over the coming decade. Both returns are somewhat higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, tin ranks 13th and 14th out of 43 commodities for the 5 and 10year return forecasts. Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 56% probability that tin can achieve this return by June 2025 and 28% by June 2030, ranking the metal 11th and 14th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that tin will outperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the metal is in its current price and valuation cycle. The evidence from tin´s price and valuation cycles since 1900 points to a probable advance in the metal´s price that will end in March 2025. At a high of $38,617 by that date, tin will have advanced from its March 2020 low in a manner consistent with the other six advances since 1900. Analysis of tin´s longerterm price behavior points to somewhat muted prices five years from now, with a subsequent surge going out to 2030. These longerterm forecasts imply a sharp collapse once the current bull market completes, followed by a rally taking the metal above its current alltime high. By June 2025, I forecast tin to be trading at $28,688 per ton, and $37,265 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 55% of the metal´s 5year returns and 81% of its 10year returns explained since June 1990. In all cases, the price of tin is not expected to fall below its March 2020 low at any time over the coming decade.
518  David J. Howden
Commodities, the Decade Ahead  519
To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying tin today and selling it at any date over the coming decade. For example, an expected price of $28,688 in June 2025 implies an annual rate of return of 11.2% over the next five years if the investor buys the metal today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
out of the 43 commodities. This implies that tin should yield somewhat higher returns than the average commodity over the coming decade, and especially over the next five years. Taking the average of the metal´s rankings for these expected returns, tin ranks 19th out of the 43 commodities.
Tin Expected return rankings, out of 43 commodities Relative Valuation th
24 Tin 43 Commodity Median
In the case of tin, cycle analysis predicts a swift appreciation topping in March 2025, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 23.0% by buying tin. This expected return is somewhat muted at 11.2% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, tin ranks 19th and 12th
0.8 0.8
Expected average returns: 5Year th
19
23.0 21.2
10Year th
12
11.2 8.1
Overall Rank th
19
520  David J. Howden
Commodities, the Decade Ahead  521
Uranium Uranium is a silverygrey metal used primarily for its nuclear properties. As of 2007, the New York Mercantile Exchange has offered futures contracts on Uranium U308, more commonly known as “yellowcake.” This unenriched uranium is later prepared for use as fuel in nuclear reactors. In its yellowcake form, uranium is of a very low radioactivity and also has industrial uses, mostly in photography and glass making.
Uranium Kazakhstan Canada Australia Namibia Niger Rest of World
Production
Consumption
(% World)
(% World)
43 13 12 10 6 16
United States France China Russia South Korea Rest of World
36 16 16 10 9 13
Source: World Nuclear Association. 2020; Statista, 2018
Kazakhstan accounts for nearly half of global production of the metal and, along with Canada and Australia, mines more than twothirds of the world´s supply. Since yellowcake is almost all bought for enrichment, its end users are those countries with the greatest nuclear electricity capacity. The United States and France account for more than half of the world´s use of this unenriched uranium. Global uranium output reached 53,656 tons in 2019, a 0.3% increase over the previous decade. In the early 2000s the perception was that output would need to expand to
522  David J. Howden accommodate a renaissance in nuclear growth. This expectation has since cooled notably. Output growth in the world´s second largest producer, Canada, has fallen by 29% since 2010 (2.9 thousand tons annually). Expanded production in Kazakhstan and Australia (28% and 12% growth) has more than made up for this loss. Against this backdrop, years of unfavorable economic conditions in the industry have managed to just keep output constant. Since 2010 world output has actually decreased marginally. Kazakhstan remains the world´s largest producer of uranium, a position it has held since records begin in 2010. There are approximately 6.1 million tons of unmined uranium in reserves globally. Australia maintains the world´s largest uranium reserves, 1.8 million tons (30% of global reserves). Although just five countries account for 67% of global reserves, the metal is found widely in small amounts throughout the world. Uranium is a relatively common metal (approximately as widespread as zinc) and known reserves have increased by more than onequarter over the last decade. Nuclear power generation is the obvious driver of the majority of uranium demand. Between 2006 and 2012 nuclear generation dropped significantly, by 12% globally. Most of that decline came from Germany as the country follows through with its plan to complete its nuclear phaseout by the next decade. (In the wake of the Fukushima emergency in 2011, Japan has also divested itself of nearly all its nuclear electrical generation.) Total nuclear electrical generation has almost returned to its 2006 peak as other countries, primarily China, increase their nuclear output. Global capacity has increased by 3.6% over the past decade and, since 1999, has grown at an annual rate of 0.5%. Taken from the 2012 low, global generation has increased by 1.8% annually. This increase is mostly driven by China, where nuclear generation has increased by 20% annually since 2012. The NYMEX uranium (UX) cash contract returned 26.0% to the investor over the past year. Futures trade in lots of 250 pounds and are quoted in U.S. dollars per pound.
Commodities, the Decade Ahead  523
The Bottom Line Uranium closed June 2020 at a price of $32.20 per pound. Based on historical valuations dating to January 1980 (486 months) I estimate the fairvalue price of the commodity to be $46.15, implying an undervaluation of 0.6 standard deviations. This indicates that it is priced more cheaply today than 74% of all previous months. Analysis of the metal´s price cycles since 1980 points to the continuation of the secular bull market that started in November 2016 at the low of $17.75. Historically, the median bull market in uranium has lasted for 5.6 years and increased its price by 797% in real terms. Following this pattern, the current bull market phase should be completed in June 2022 after an additional 726% gain in the metal´s inflationadjusted price.
Uranium: Forecast Summary 32.20 46.15 0.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Nov16 Jun22 726 188
5Year Forecast 5Year Annual Forecast Return, % 8.9 5Year Forecast Range, % (8.7, 9.5) 2 0.31 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
71 47
10Year Forecast 10Year Annual Forecast Return, % 14.7 10Year Forecast Range, % (10.4, 19.8) 2 0.74 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 81
Over the coming 5year period, I forecast the price of uranium to increase by 8.9% annually, with a forecast range between 8.7 and 9.5%. The forecast model explains 31%
524  David J. Howden of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that uranium´s price will breakeven by June 2025 with a 71% probability, and that there is a 47% chance that the metal´s return will be over 10% by that date. The coming decade should see somewhat stronger returns. I forecast uranium´s price to increase by 14.7% annually until June 2030 with a forecast range between 10.4 and 19.8%. This model explains 74% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that uranium will breakeven over the coming decade, and an 81% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of uranium has increased from $11.60 per pound to the current close of $32.20 for an annual return of 3.5%. The alltime nominal high for the metal came in May 2007 at a price of $36.22. In real, inflationadjusted terms the metal´s price has mostly fallen throughout its history. Uranium´s real high was in May 2007, with its subsequent low forming in December 2000. As of June 2020, the metal´s price was lower than 58% of all prior monthly closing prices in real terms. Over longer periods, uranium´s price has just barely kept pace with general price inflation, resulting in a real yield of around 0% for most of the past 40 years. Nominal returns have hovered around 2.5% for most of the metal´s history, with real returns averaging 0.3% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 8.1% and resulted by buying uranium in December 2000 and holding it until today. Since inflation over that period averaged 2.0%, the investor earned a somewhat more subdued return of 6.1% per year.
Commodities, the Decade Ahead  525 More recently the metal´s price has been in a bull market since November 2016. From that month´s low of $17.75 a rally of 88% has ensued thus far. The May 2020 high of $35.30 looks to be a stop along the way of a multiyear rally. Since 1980 the metal has gone through two complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 797% in real terms, before being corrected by a median decline of 75%. The median bull market has lasted for just over fiveandahalf years, and its subsequent correction has taken over seven years to complete. Owing to the relatively short price history of the metal available, it is not possible to track the changes to its relative valuation over a sufficient number of phases to make claims as to its cyclical norms. Still, with two completed cycles it is possible to speak of these bull and bear markets in terms of their price action. Uranium: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
16.50
7.10
61
n.a.
May07 Nov16 136.22
17.75
89
8.2
May96 Dec00
Date Start End Aug91 May96
Price Start End 7.25
16.50
100
n.a.
Dec00 May07
7.10
136.22
1,494
n.a.
Nov16 Jun20
17.75
32.20
72
1.0
Real Start Rel. Change, % Val, σ
Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Max. 9.5 89 n.a. n.a.
Median 7.1 75 8.2 9.2
Min. 4.6 61 n.a. n.a.
Max. 6.4 1,494 n.a. n.a.
Median 5.6 797 1.0 n.a.
Min. 4.8 100 n.a. n.a.
Jun22 n.a. 159 797 n.a.
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in May 2007. From the starting price of $136.22 the metal´s price fell by 89% in real terms. This decline is on par with the median decline of 75% over all recorded uranium bear markets as well as price declines in other commodities. At the November 2016 low of $17.75 the metal was 1.0 standard deviations undervalued. This made the metal more undervalued than 84% of all previous monthly closes. Again, this is broadly consistent with the undervaluations apparent at the end of bear markets in the other commodity markets. If a new bull market did start in November 2016 is still ongoing, what can we expect the future to hold? The median bull market in uranium has lasted for fiveandahalf years and gained 797% in real terms. The weakest advance, during 199196, gained 100% in real terms. Since November 2016, the metal has already gained 71%. As such, I expect the current cycle to gain an additional 726% in real terms by June 2022. This implies an expected annual return of 188% by the time the present bull market reaches completion.
526  David J. Howden More dependable than forecasts of price movements are changes to relative valuation. While there is very little data of uranium´s relative valuation owing to its short price history, we can look to trends common to all other commodities. All commodities increase their relative valuation throughout their bull markets, usually in the range of +1.5 to +2.5 standard deviations. With very few exceptions, nearly all bull markets end with overvalued relative valuations.
Commodities, the Decade Ahead  527 cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for uranium starts in January 1980. This means that to date there have been 426 5year holding periods and 366 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of uranium is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of uranium over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of uranium as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values.
As of June 2020, uranium is still 0.6 standard deviations undervalued, cheaper than 74% of all previous monthly closing prices. This represents only a +0.4 standard deviation increase in the metal´s relative valuation. Both facts point to some significant remaining upside potential in the current bull market. In sum, cycle analysis points to uranium trading at $159 on June 2022, a price that will most likely be overvalued (i.e., have a positive relative valuation).
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the
I forecast an 8.9% annual gain in uranium over the coming 5year period. The forecast range is also strictly positive, ranging from 8.7 to 9.5%. The model explains 31% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of uranium will breakeven by June 2025
528  David J. Howden with a 71% probability, and that the return will exceed 10% with a 47% probability.
Commodities, the Decade Ahead  529 18th and 1st out of 43 commodities for the 5 and 10year return forecasts.
Uranium Forecast return rankings, out of 43 commodities Relative Valuation th
28 Uranium 43 Commodity Avg.
0.6 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year st
5Year th
10Year st
8.9 7.6
14.7 5.9
47 39
81 22
18
1
17
1
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 47% probability that uranium can achieve this return by June 2025 and 81% by June 2030, ranking the metal 17th and 1st out of the 43 markets for both probabilities. Given this evidence, it is highly likely that uranium will overperform the average commodity over both the coming 5 and 10year periods. Over the next ten years, I expect the price of uranium to increase by 14.7% annually. The forecast range is clustered around this level, ranging from 8.7 to 9.5%. The model explains 74% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that uranium will breakeven by June 2030 with a probability of 99%, and that there is an 81% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Uranium´s relative valuation of 0.6 standard deviations below its longterm mean is on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but no more than the average commodity. As such, uranium is the 28th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 8.9% over the coming five years, and 14.7% over the coming decade. Both returns are significantly higher than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, uranium ranks
To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the metal is in its current price and valuation cycle. The evidence from uranium´s price and valuation cycles
530  David J. Howden
Commodities, the Decade Ahead  531
since 1980 points to a probable advance in uranium´s price that will end in June 2022. At a high of $159 by that date, the metal will have advanced from its November 2016 low in a manner consistent with the other two advances since 1980. Analysis of uranium´s longerterm price behavior points to somewhat muted prices five years from now, with a subsequent surge going out to 2030. These longerterm forecasts imply a sharp collapse once the current bull market completes, followed by a rally taking the metal close to its alltime highs. By June 2025, I forecast uranium to be trading at $49.29 per pound, and $127.35 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 31% of the metal´s 5year returns and 74% of its 10year returns explained since June 1990. In all cases, the price of uranium is not expected to fall below its November 2016 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying uranium today and selling it at any date over the coming decade. For example, an expected price of $49.29 in June 2025 implies an annual rate of return of 8.9% over the next five years if the investor buys the metal today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
Uranium Expected return rankings, out of 43 commodities Relative Valuation th
28 Uranium 43 Commodity Median
0.6 0.8
Expected average returns: 5Year st
10Year th
1
6
77.9 21.2
14.8 8.1
Overall Rank th
4
In the case of uranium, cycle analysis predicts a swift appreciation topping in June 2022, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 77.9% by buying uranium. This
expected return is somewhat muted at 14.8% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, uranium ranks 1st and 6th out of the 43 commodities. This implies that uranium should yield a significantly higher return relative to other commodities over both of these time periods. Taking the average of the metal´s rankings for these expected returns, uranium ranks 4th out of the 43 commodities.
532  David J. Howden
Commodities, the Decade Ahead  533
Wheat Wheat is the second most widely cultivated cereal globally (after corn). More land is dedicated to wheat production than any other food, and global trade in the grain is greater than all other crops combined. The European Union is the world´s largest producer and, combined with China and India, accounts for over half of global output. The three countries also account for nearly half of global consumption.
Wheat European Union China India Russia United States Rest of World
Production
Consumption
(% World)
(% World)
18 18 14 10 7 34
China European Union India Russia United States Rest of World
17 16 13 5 4 44
Source: USDA, 2020
Global wheat output reached 734 million tons in 2018, an 8% increase over the previous decade. This increase came largely as a result of increased production yields, and less so by expanded production area. Higher profit margins on other crops have shifted production to other areas and have muted the growth of total wheat output. Notably, the European Union has seen production fall by 9% (13 million tons annually) since 2009. Growth in China and India have more than taken up this slack as production moved to those countries. Chinese wheat output is now 17% higher than a decade ago (an extra 19 million tons
534  David J. Howden annually) and India produces 27% more (21 million extra tons). The European Union still remains the world´s largest wheat producer, a position it has held at least since records begin in 1961. Since 1999 world output has increased at an annual rate of 1.1%. Globally, there are 214 million hectares of land devoted to wheat production. This area is 3.5% less than there was a decade ago and, since 1999, the area of wheat the world has harvested has been essentially unchanged. Land use for wheat production has been erratic over the past 30 years, though the longterm trend is for lower production areas harvested. Increasing yields have more than compensated for the decrease in areas harvested. Globally, wheat yields 3.4 metric tons to the hectare. This represents a 12% increase over the past decade, and 1.2% annually since 1999. Over the past 30 years yields have increased between 12% annually. Global wheat stocks were near their alltime highs at 28.4 million tons in 2019. Over the past decade, the average annual surplus of wheat production has been roughly one million tons, leaving an average ending inventory of 28.4 million tons, implying a longrun growth rate of global wheat inventories of 3.9% annually. At 37% of wheat output, stocks are also at alltime high relative to production. With such growth to stocks, wheat demand should not face any supplyside constraint for the foreseeable future. Hard red (or Kansas City) wheat futures are traded on the Chicago Board of Trade. The CBOT hard red wheat (KW) cash contract returned 2.6% to the investor over the past year. Futures trade in lots of 5,000 bushels and are quoted in U.S. cents per bushel.
The Bottom Line Wheat closed June 2020 at a price of $4.53 per bushel. Based on historical valuations dating to January 1841 (2,154 months) I estimate the fairvalue price of the commodity to be $5.71, implying an undervaluation of 0.8 standard deviations. This indicates that
Commodities, the Decade Ahead  535 it is priced more cheaply today than 79% of all previous months. Analysis of the cereal´s price cycles since 1900 points to the start of a new secular bull market. The August 2016 low of $3.13 looks to be a longterm bottom. Historically, the median bull market in wheat has lasted for 4.6 years and increased its price by 207% in real terms. Following this pattern, the current bull market phase should be completed in March 2021 after an additional 172% gain in the cereal´s inflationadjusted price.
Wheat: Forecast Summary 453 571 0.8
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Aug16 Mar21 172 328
5Year Forecast 5Year Annual Forecast Return, % 5.3 5Year Forecast Range, % (5.1, 5.4) 2 0.48 Adjusted R Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
81 22
10Year Forecast 10Year Annual Forecast Return, % 4.3 10Year Forecast Range, % (3.8, 5.0) 2 0.58 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
92 3
Over the coming 5year period, I forecast the price of wheat to increase by 5.3% annually, with a forecast range between 5.1 and 5.4%. The forecast model explains 48% of the variation in the cereal´s 5year returns since June 1990. Consequently, I forecast that wheat´s price will breakeven by June 2025 with an 81% probability, and that there is a 22% chance that the cereal´s return will be over 10% by that date. The coming decade should see somewhat more subdued returns. I forecast wheat´s
536  David J. Howden price to increase by 4.3% annually until June 2030 with a forecast range between 3.8 and 5.0%. This model explains 58% of the cereal´s 10year returns since June 1990. As such, there is a 92% probability that wheat will breakeven over the coming decade, and a 3% chance that it will yield a return greater than 10%.
Historical Analysis Since June 1990, the nominal price of wheat has increased from $3.25 per bushel to the current close of $4.53 for an annual rate of return of 1.1%. The alltime nominal high for the cereal came in February 2008 at a price of $12.39. In real, inflationadjusted terms the cereal´s price has mostly fallen throughout its history. Wheat´s real high was in September 1917, with its subsequent alltime low forming in August 2016. As of June 2020, the cereal´s price was lower than 91% of all prior monthly closing prices in real terms. Over longer periods, wheat´s price has failed to keep pace with general price inflation, resulting in a real yield of around negative 13% for most of the 20th century. Nominal returns have hovered around 1% for most of the cereal´s history, with real returns averaging 1.8% annually between 1900 and 2010. The highest longterm nominal return the investor could have earned was 2.8% and resulted by buying wheat in April 2000 and holding it until today. Since inflation over that period averaged 0.8%, the investor´s returns were somewhat more muted at 2.0% per year.
Commodities, the Decade Ahead  537 that should continue for some time. Since 1900 the cereal has gone through six complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the cereal´s price increase by 207% in real terms, before being corrected by a median decline of 74%. The median bull market has lasted for just over fourandahalf years, and its subsequent correction has taken over eight years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the six completed bull markets in wheat has started from an undervalued position, with a median value of 1.4 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +4.2 standard deviations. Similarly, each of the cereal´s seven completed bear markets has started from an overvalued position, with a median value of +2.5 standard deviations above the longterm mean. Over the course of each bear market wheat continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 3.7 standard deviations. Wheat (Hard Red): Historical Cycle Summary Declines Date Start End Sep09 Jun14
Price Start End 48 99.76
Advances Real Start Rel. Change, % Val, σ 53
2.5
Date Start End
212
42
80
4.3
Apr37 Nov38
140
63
54
0.8
Dec47
311
126
74
0.1
Feb74 Dec90
559
271
83
6.5
Apr96 Apr00
681
259
65
1.5
Feb08 Aug16
1,239
313
78
7.4
Jul69
Real Start Rel. Change, % Val, σ
Sep17
48
212
225
1.2
Dec32 Apr37
42
140
207
1.8
Nov38 Dec47
63
311
194
1.3
Feb74
126
559
245
2.0
Dec90 Apr96
271
681
116
1.3
Apr00 Feb08
259
1,239
287
1.4
Aug16 Jun20
313
453
35
1.8
Jun14 Sep17 Dec32
Price Start End
Jul69
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
More recently the cereal´s price has been in a bull market since August 2016. From that month´s low of $3.13 a gain of 35% has ensued up to the recent July 2018 high. The advance since the August 2016 bottom looks to be part of a longterm secular bull market
Max. 21.6 83 7.4 9.2
Median 8.5 74 2.5 3.7
Min. 95.3 53 0.1 2.1
Max. 9.1 287 1.2 8.8
Median 4.6 207 1.4 4.2
Min. 3.3 35 2.0 1.4
Mar21 2.4 961 207 4.2
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in February 2008. From the starting price of $12.39 the cereal´s price fell by 78% in real terms. This decline is on par with the median decline of 74% over all recorded wheat bear markets. The decline´s starting relative valuation of +7.4 standard deviations
538  David J. Howden was the most overvalued price in wheat´s history, and far above the median bear market starting relative valuation of +3.7 standard deviations. At the August 2016 low of $3.13 the cereal was 1.8 standard deviations undervalued. This made the cereal marginally more undervalued than the median start to a bull market advance (1.4 standard deviations). The loss of 9.2 standard deviations of valuation between 2008 and 2016 is also far more than the median change in the measure during correction phases (3.7 standard deviations). As such, the balance of cycle evidence points to the August 2016 low marking the end of a bear market decline and the start of a fresh secular bull market which continues to this day. If a new bull market did start in August 2016 what can we expect the future to hold? The median bull market in wheat has lasted for over fourandahalf years and gained 207% in real terms. The weakest advance, during 199096, gained 116% in real terms. Since August 2016, the cereal has already gained 35%. As such, I expect the current cycle to gain an additional 172% in real terms by February 2024. This implies an expected annual return of 328% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, wheat has increased its valuation within a band of +7.4 standard deviations (the weakest advance increased its valuation by +1.4 and the strongest increased by +8.8 standard deviations). In other words, never in the 120year price history under examination has wheat failed to increase its valuation by less than +1.4 standard deviations over its bull market. Since the August 2016 low the cereal´s relative valuation has increased by +1.0 standard deviations, implying its change in valuation is still weaker than the weakest bull market in over a century. Coupled with the fact that the 35% price gain since 2016 is far lower than the previous weakest bull market, there is evidence that there is still upside potential.
The August 2016 undervaluation of 1.8 standard deviations made the commodity
Commodities, the Decade Ahead  539 more undervalued than 96% of all previous months. By the time the current bull market reaches its end, I expect wheat to be trading at a price which is +2.4 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to wheat trading at $9.61 on March 2021, a price that is +2.4 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for wheat starts in January 1841. This means that to date there have been 2,095 5year holding periods and 2,035 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of wheat is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of wheat over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run. Both models use the relative valuation of wheat as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 5.3% annual gain in wheat over the coming 5year period. The forecast range is also strictly positive, ranging from 5.1 to 5.4%. The model explains 48% of the variation of the 300 5year returns of the grain since June 1990. Given this explanatory power of the model, I estimate that the price of wheat will breakeven by June 2025 with an 81% probability, and that the return will exceed 10% with a 22% probability.
540  David J. Howden
Commodities, the Decade Ahead  541
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Wheat´s relative valuation of 0.8 standard deviations below its longterm mean is on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations) and implies that the commodity is undervalued in absolute terms, but no more than the average commodity. As such, wheat is the 22nd most undervalued commodity of the group. I forecast that the cereal will yield an annual return of 5.3% over the coming five years, and 4.3% over the coming decade. Both returns are somewhat lower than the averages for the 42 other commodities (7.6% and 5.9%). Consequently, wheat ranks 31st and 29th out of 43 commodities for the 5 and 10year return forecasts.
Over the next ten years, I expect the price of wheat to increase by 4.3% annually. The forecast range is clustered around this level, ranging from 3.8 to 5.0%. The model explains 58% of the variance in the grain´s 240 10year returns since June 1990. As such, I estimate that wheat will breakeven by June 2030 with a probability of 92%, and that there is a 3% chance that its return will exceed 10% over this period.
Wheat (Hard Red) Forecast return rankings, out of 43 commodities Relative Valuation nd
22 Wheat 43 Commodity Avg.
0.8 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year st
10Year th
5Year th
10Year th
5.3 7.6
4.3 5.9
22 39
3 22
31
29
30
30
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 22% probability that wheat can achieve this return by June 2025 and 3% by June 2030, ranking the grain 30th out of the 43 markets for both probabilities. Given this evidence, it is highly likely that wheat will underperform the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over longer periods (five and ten years) within the background of where the grain is in its current price and valuation cycle. The evidence from wheat´s price and valuation cycles since 1900 points to a probable surge in the cereal´s price that will end in March 2021. At a high of $9.61 by that date, the grain will have advanced from its August 2016 low in a manner consistent with the other six advances since 1900. Over this time, wheat´s relative valuation should also increase from its current undervalued position of 0.8 standard deviations, to end this bull market rally overvalued by +2.4 standard deviations.
542  David J. Howden
Commodities, the Decade Ahead  543 are much less standard. In the case of wheat, cycle analysis predicts a swift appreciation peaking in March 2021, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 25.3% by buying wheat. This expected return falls to 5.3% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, wheat ranks 16th and 30th out of the 43 commodities. This implies that wheat should yield a return comparable to the median commodity over the coming five years, though over the next decade its return should be lower than the average. Taking the average of the grain´s rankings for these expected returns, wheat ranks 21st out of the 43 commodities.
Wheat (Hard Red) Expected return rankings, out of 43 commodities Relative Valuation nd
22 Analysis of wheat´s longerterm price behavior points to somewhat muted prices five years from now, at least relative to this forecast cycle high, with a continued advance going out to 2030. These longerterm forecasts imply a sharp collapse after the current bull market completes, followed by a rally taking the grain back to multiyear highs. By June 2025, I forecast wheat to be trading at $5.86 per bushel, and $6.87 by June 2030. The forecast models for these longerterm projections are reasonably robust, with 48% of the grain´s 5year returns and 58% of its 10year returns explained since June 1990. In all cases, the price of wheat is not expected to fall below its March 2020 low at any time over the coming decade. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying wheat today and selling it at any date over the coming decade. For example, an expected price of $5.86 in June 2025 implies an annual rate of return of 5.3% over the next five years if the investor buys wheat today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place
Wheat 43 Commodity Median
0.8 0.8
Expected average returns: 5Year th
16
25.3 21.2
10Year th
30
5.3 8.1
Overall Rank st
21
544  David J. Howden
Commodities, the Decade Ahead  545
Zinc Zinc is the 23rd most abundant element in the world. Of the metals, only iron, aluminum and copper are produced in larger quantities. The bluishwhite metal is used widely by the construction and manufacturing industries due to its durability when alloyed and resistance to corrosion. It is also widely used in the chemical and health supplement industries. China accounts for onethird of global production of the metal, and Zinc along with Peru and Australia Production produces more than half of global output. (% World) Global zinc output reached 13 China 33 million tons in 2019, a 12% increase over the previous decade. This Peru 11 increase came largely as a result of Australia 10 expanded production from China India 6 where output increased by 29% (1 million metric tons) since 2009. China United States 6 is the world´s largest producer of zinc, Rest of World 34 a position it has held since surpassing Australia in 1998. Source: USGS, 2020 Recycled scrap remains an important source of aluminum augmenting smelted production. In the United States, approximately 25% of zinc consumption comes from recycled sources. Since 1999 world output has increased at an annual rate of 2.5%. There are approximately 250 million tons of unmined zinc ore in reserves globally. Reserves grew at the robust pace of 2.3% over the past decade. Most of this increase came from Australia, which tripled its reserves over this period, and China. Australia maintains the world´s largest
546  David J. Howden
Commodities, the Decade Ahead  547 zinc reserves at 68 million tons (27% of global reserves). Although just five countries account for 70% of global reserves, the metal is found widely throughout the world. The London Metal Exchange launched zinc contracts in 1920, though the contract´s current specifications have existed only since 1986. The metal is also traded on the Commodity Exchange. The LME Zinc (ZS) cash contract returned 20.3% to the investor over the past year. Futures trade in lots of 25 metric tons and are quoted in U.S. dollars per metric ton.
Zinc: Forecast Summary 2,056 2,445 0.6
Current Price FairValue Price Relative Valuation, σ Cycle Forecast Forecast Trend Trend Start Date Expected Trend End Date Expected Real Return Remaining, % Expected Real Return Remaining, annualized %
Up Mar20 Mar24 111 22
5Year Forecast 5Year Annual Forecast Return, % 7.2 5Year Forecast Range, % (6.7, 8.0) 2 0.49 Adjusted R
The Bottom Line Zinc closed June 2020 at a price of $2,056 per metric ton. Based on historical valuations dating to June 1875 (1,741 months) I estimate the fairvalue price of the commodity to be $2,445, implying an undervaluation of 0.6 standard deviations. This indicates that it is priced more cheaply today than 72% of all previous months. Analysis of the metal´s price cycles since 1900 points to the start of a new secular bull market. The March 2020 low of $1,868 looks to be a longterm bottom. Historically, the median bull market in zinc has lasted for 4.0 years and increased its price by 122% in real terms. Following this pattern, the current bull market phase should be completed in March 2024 after an additional 111% gain in the metal´s inflationadjusted price. Over the coming 5year period, I forecast the price of zinc to increase by 7.2% annually, with a forecast range between 6.7 and 8.0%. The forecast model explains 49% of the variation in the metal´s 5year returns since June 1990. Consequently, I forecast that zinc´s price will breakeven by June 2025 with an 82% probability, and that there is a 36% chance that the metal´s return will be over 10% by that date. The coming decade should see comparable returns. I forecast zinc´s price to increase by 7.3% annually until June 2030 with a forecast range between 5.9 and 9.5%. This model explains 61% of the metal´s 10year returns since June 1990. As such, there is a 99% probability that zinc will breakeven over the coming decade, and a less than 21% chance that it will yield a return greater than 10%.
Probability 5Year Forecast Return > 0, % Probability 5Year Forecast Return > 10, %
82 36
10Year Forecast 10Year Annual Forecast Return, % 7.3 10Year Forecast Range, % (5.9, 9.5) 2 0.60 Adjusted R Probability 10Year Forecast Price Return > 0, % Probability 10Year Forecast Price Return > 10, %
99 21
Historical Analysis Since June 1990, the nominal price of zinc has increased from $1,767 per metric ton to the current close of $2,057 for an annual rate of return of 0.5%. The alltime nominal high for the metal came in November 2006 at a price of $4,390. In real, inflationadjusted terms the metal´s price has mostly meandered in the $2,000 to $4,000 range throughout its history. Zinc´s real high was in June 1915, with its subsequent low forming in September 2002. As of June 2020, the metal´s price was lower than 88% of all prior monthly closing prices in real terms. Over longer periods, zinc´s price has increased on par with general price inflation, resulting in a real return of around 0% for most of the 20th century. Nominal returns have hovered around 2.8% for most of the metal´s history, with real returns averaging 0.2% annually between 1900 and 2010. The highest longterm nominal return the
548  David J. Howden investor could have earned was 6.0% and resulted by buying zinc in September 2002 and holding it until today. Since inflation over that period averaged 2.0%, the investor would have earned a real return of around 4.0% per year. More recently the metal´s price has been in a bear market since January 2018. From that month´s high of $3,590 a collapse of 50% ensued. The March 2020 bottom of $1,868 looks to be the end of a longterm secular decline which should usher in a multiyear rally.
Commodities, the Decade Ahead  549 Zinc: Historical Cycle Summary Declines Date Start End
Price Start End
Advances Real Start Rel. Change, % Val, σ
Jun15
Jun21
319
106
81
7.3
Jun25
Jun32
171
65
51
0.1
Jun51
Jun58
405
231
49
1.0
May75 Nov85
871
648
64
2.9
Feb89 Aug93
2,050
876
64
3.0
Aug97 Sep02
1,652
736
60
0.9
Nov06 Oct08
4,390
1,091
77
6.5
Feb11 Nov15
2,478
1,545
42
1.1
Jan18 Mar20
3,590
1,868
50
1.3
Date Start End Jun14 Jun15
Price Start End 115
319
173
1.3
Jun21
Jun25
106
171
63
1.5
Jun32
Jun51
65
405
226
1.7
Jun58 May75
231
871
104
1.7
Nov85 Feb89
648
2,050
183
2.1
Aug93 Aug97
876
1,652
70
1.6
Sep02 Nov06
736
4,390
437
1.7
Oct08 Feb11
1,091
2,478
122
0.8
Nov15
Jan18
1,545
3,590
122
0.6
Mar20 Jun20
1,868
2,057
11
0.8
Real Start Rel. Change, % Val, σ
Current Bull Market Forecast End Date Relative Valuation Price Real Advance, % Change in Rel. Val., σ
Duration, years Real Decline, % Starting Rel. Val., σ Change in Rel. Val., σ
Since 1900 the metal has gone through nine complete price cycles. Each cycle starts with a bull market advance and is corrected by a bear market decline. The median bull market advance over these cycles has seen the metal´s price increase by 122% in real terms, before being corrected by a median decline of 60%. The median bull market has lasted for four years, and its subsequent correction has taken a little over five years to complete. The relative valuation of the commodity ebbs and flows throughout every bear and bull market phase of a cycle. Each of the nine completed bull markets in zinc has started from an undervalued position, with a median value of 1.6 standard deviations below the longterm average. From these undervalued starting positions, the median bull market increased its relative valuation by +2.7 standard deviations. Similarly, each of the metal´s nine completed bear markets started from an overvalued position, with a median value of +1.3 standard deviations above the longterm mean (with the exception of the 192532 bear market which started from a slightly undervalued position). Over the course of each bear market zinc continued to shed valuation as its price fell. The median price decline caused the relative valuation to fall by 2.7 standard deviations.
Max. 10.5 81 7.3 8.8
Median 5.1 60 1.3 2.7
Min. 1.9 42 0.1 1.6
Max. 19.0 437 2.1 8.6
Median 4.0 122 1.6 2.7
Min. 1.0 63 0.6 1.4
Mar24 1.9 4,153 122 2.7
Duration, years Real Advance, % Starting Rel. Val., σ Change in Rel. Val., σ
The most recently completed phase of its cycles was the bear market decline which started in January 2018. From the starting price of $3,590 the metal´s price fell by 50% in real terms. This decline is close to the median decline of 62% over all recorded zinc bear markets. The decline´s starting relative valuation of +1.3 standard deviations was also consistent with the median bear market starting relative valuation of +1.3. At the recent March 2020 low of $1,868 the metal was 0.8 standard deviations undervalued, which is somewhat less undervalued than the median start to a bull market advance (1.6 standard deviations). The loss of 2.1 standard deviations of valuation between 2018 and 2020 is also weak by historical standards, with the median change in the measure during correction phases coming in at 2.7 standard deviations). Although weak by historical standards, the 201820 decline is well within historical parameters for a decline. Combined with the positive forecast returns for the metal, there is a high probability that the March 2020 low marks the end of a bear market and that a multiyear secular bull market has just started. If a new bull market did start in March 2020 what can we expect the future to hold? The median bull market in zinc has lasted for four years and gained 122% in real terms. The weakest advance, during 192125, gained 63% in real terms. Since March 2020, the metal has already gained 11%. As such, I expect the current cycle to gain an additional
550  David J. Howden 76% in real terms by March 2024. This implies an expected annual return of 111% by the time the present bull market reaches completion. More dependable than forecasts of price movements are changes to relative valuation. Over its bull markets to date, zinc has increased its valuation within a band of +7.2 standard deviations (the weakest advance increased its valuation by +1.4 and the strongest increased by +8.6 standard deviations). In other words, never in the 120year price history under examination has zinc failed to increase its valuation by less than +1.4 standard deviations during its bull market. Since the March 2020 low the metal´s relative valuation has increased by +0.2 standard deviations, implying significant upside potential.
Commodities, the Decade Ahead  551 and change in relative valuation over these cycles. The analysis provides a method to ground our expectations of the future and helps to establish whether the commodity is in a bull or bear market phase but leaves many doubts as to what the eventual end of the cycle will look like. We can minimize these doubts by choosing a specific duration to provide estimates of the returns by taking recourse in the large number of similar periods in the past. The price history for zinc starts in June 1875. This means that to date there have been 1,681 5year holding periods and 1,621 10year periods to use as inputs to make forecasts over the coming five and ten years. This large number of periods allows for a more robust statistical analysis, one which yields more dependable forecasts. As we have seen, the future return of zinc is highly dependent on its starting valuation relative to its longerterm mean. Investments made in periods of undervaluation deliver far superior returns to those made during periods of overvaluation. Inflation and interest rates also play a role in forecasting future returns, as do present supplydemand conditions in the market and expectations of the future. I have developed two models to forecast the return of zinc over these two different time periods – five years and ten years. In general, the 10year forecast model is more robust and accurate than the 5year model. This accords with common sense as the longterm volatility of a commodity´s price is much lower than it is in the short run.
The March 2020 undervaluation of 0.8 standard deviations made the commodity more undervalued than 79% of all previous months. By the time the current bull market reaches its end, I expect zinc to be trading at a price which is +1.9 standard deviations overvalued relative to its longterm average. In sum, cycle analysis points to zinc trading at $4,153 on March 2024, a price that is +1.9 standard deviations overvalued.
Forecasted Returns The previous cycle analysis is helpful as it helps to shape our expectations about the future trend´s direction. It also provides time and price targets based on historical norms. The analysis has two deficiencies, however. The first is that there have been only a limited number of cycles since the commodity has begun trading that can be used to measure historical price and duration trends. The small number of cycles creates the second problem, which is that there is a relatively large variance in the values of duration, return
Both models use the relative valuation of zinc as their basis for forecasting its future returns. They also look at interest rates, the yield curve, current macroeconomic conditions (e.g., unemployment, inflation, etc.) and financial indicators. All models are tested statistically at the 95% confidence level, and I also list their explanatory power over past data, as well as their expected ability to estimate future values. I forecast a 7.2% annual gain in zinc over the coming 5year period. The forecast
552  David J. Howden range is also strictly positive, ranging from 6.7 to 8.0%. The model explains 49% of the variation of the 300 5year returns of the metal since June 1990. Given this explanatory power of the model, I estimate that the price of zinc will breakeven by June 2025 with an 82% probability, and that the return will exceed 10% with a 36% probability.
Commodities, the Decade Ahead  553 and 7.3% over the coming decade. This 5year return is on par with the average for the other commodities, and somewhat higher than over the 10year period. Consequently, zinc ranks 27th and 18th out of 43 commodities for the 5 and 10year return forecasts.
Zinc Forecast return rankings, out of 43 commodities Relative Valuation th
30 Zinc 43 Commodity Avg.
0.6 0.7
Forecast returns:
Probability that return exceeds 10%:
5Year th
10Year th
5Year th
10Year th
7.2 7.6
7.3 5.9
36 39
21 22
27
18
25
17
Furthermore, I consider the probability that the forecasted return for the commodity will exceed 10%. The averages for all 43 commodities give less than even odds (39% and 22%) of accomplishing this feat over both 5 and 10year time horizons. Given the explanatory power of the forecast models I estimate that there is a 36% probability that zinc can achieve this return by June 2025 and 22% by June 2030, ranking the metal 25th and 17th out of the 43 markets for both probabilities.
Over the next ten years, I expect the price of zinc to increase by 7.3% annually. The forecast range is clustered around this level, ranging from 5.9 to 9.5%. The model explains 60% of the variance in the metal´s 240 10year returns since June 1990. As such, I estimate that zinc will breakeven by June 2030 with a probability of 99%, and that there is a 21% chance that its return will exceed 10% over this period.
Conclusion This investment report assesses the forecasted returns of the 43 most highly traded commodities in the world. Each commodity is assessed on its own merits, resulting in quantitative forecasts for the next five and ten years. This concluding analysis, however, takes a qualitative look at these forecasts by ranking them against the 42 other commodities. In general, the closer to 1st the ranking is, the more likely it is to outperform the other commodities. A ranking of 43rd signifies that the commodity is the most overvalued, or that it is expected to yield the lowest return in the future. Zinc´s relative valuation of 0.6 standard deviations below its longterm mean is on par with the average of the 43 markets analyzed herein (a slight undervaluation of 0.7 standard deviations). As such, zinc is the 27th most undervalued commodity of the group. I forecast that the metal will yield an annual return of 7.2% over the coming five years,
Given this evidence, it is highly likely that zinc will provide comparable performance relative to the average commodity over both the coming 5 and 10year periods. To put the full analysis in context we need to consider the forecasted returns over
554  David J. Howden
Commodities, the Decade Ahead  555
longer periods (five and ten years) within the background of where the metal is in its current price and valuation cycle. The evidence from zinc´s price and valuation cycles since 1900 points to a probable surge in the metal´s price that will end in March 2024. At a high of $4,153 by that date, the metal will have advanced from its March 2020 low in a manner consistent with the other nine advances since 1900. Over this time, zinc´s relative valuation should also increase from its current undervalued position of 0.6 standard deviations, to end this bull market rally overvalued by +1.9 standard deviations. To make these expected prices comparable with other commodities, we can compare the annualized return the investor can expect to earn by buying zinc today and selling it at any date over the coming decade. For example, an expected price of $2,906 in June 2025 implies an annual rate of return of 7.2% over the next five years if the investor buys zinc today. Changes in valuation and price repeat in somewhat predictable ways, as outlined above, but the time horizons during which these changes take place are much less standard.
Zinc Expected return rankings, out of 43 commodities Relative Valuation th
27 Zinc 43 Commodity Median
0.6 0.8
Expected average returns: 5Year th
10Year th
22.9 21.2
7.5 8.1
20
25
Overall Rank th
24
In the case of zinc, cycle analysis predicts a swift appreciation peaking in March 2024, and the period valuation models also forecast price increases, but over longer time periods. One way to remove the noise and mitigate the timing uncertainty is to take the median return expected over the coming 5 and 10year period. Between today and June 2025 the investor can expect a median annual return of 22.9% by buying zinc. This expected return falls to 7.5% annually over the coming decade. In comparison to the expected median returns over the coming 5 and 10year periods, zinc ranks 20th and 25th out of the 43 commodities. This implies that zinc should yield return superior to the median commodity over the next five years, though just average returns by the end of
the decade. Taking the average of the metal´s rankings for these expected returns, zinc ranks 24th out of the 43 commodities.
556  David J. Howden
Commodities, the Decade Ahead  557
Ranking and Conclusion With the individual analyses complete it is now time to turn our attention to separating the wheat from the chaff. While the individual analyses are useful in isolation of each other for gathering our bearings about where the commodity has been and where it is heading, it is useful to compare them all headtohead to determine where superior returns are to be found. We´ll start by comparing the relative valuations, forecast period returns and associated probabilities. There are some very general conclusions to be gathered. The first is that of the seven commodity groups (the indexes, energy, grains, industrial metals, livestock, precious metals, and softs) only energy and the industrial metals can be expected to offer superior returns moving forward. The boxes shaded black denote those commodities that are ranked 1st through 5th in their respective category (the topranked commodities). Those shaded dark grey illustrate those commodities ranked 38th through 43rd (the bottom of the list). Visually we can immediately see that nearly all energy commodities are forecast to offer superior returns and have an easier time bettering the hurdle rate of 10% than the other commodity groups. We can also add to this list uranium (technically an industrial metal, though traded for its use in energy applications), steel and platinum. The bottom five of the rankings are a mixed bag, though in general grains and livestock are forecast to offer inferior returns over the next five years and decade. Market volatility (the VIX) is also expected to perform poorly (which is generally quite a good thing for other markets). The preceding comparison looked at the forecast period returns in isolation of the cycle analysis. This approach has its merits, specifically the statistical robustness of the approach during “normal” economic times, but the cycle analysis allows us to integrate market swings that stem from deeply over and undervalued markets into the analysis. This step is important because the basis of my methodology is that markets swing through periods of over and undervaluation, oscillating around their fairvalue level. This idea is captured by focusing on price and valuation cycles. At the same time, current economic and financial data can be used to estimate future performance, often with high degrees of confidence given the long data sets available. This idea is encapsulated in the period forecasts. Putting the two together yields an expected price path for a given commodity to take over the coming decade. From this price path, expected returns can be calculated and compared across the 43 markets.
558  David J. Howden
Commodities, the Decade Ahead  559 Commodities, ranking summary
Commodities, forecast summary Relative Forecast Return Valuation 5Year 10Year
Probability that return exceeds 10%: 5year 10year
0.1 1.6 1.6
2.6 12 14.3
3.5 5.7 10.3
31 0 74
4 0 55
1 1.5 1.5 1.5 1.5 1.1 1.6
12.7 18.4 17.1 6.2 18.3 7.4 17.5
8.9 11.9 12.2 4.2 12.2 2.3 11.4
63 82 79 24 84 38 83
39 67 71 3 72 4 64
0.4 0.8 0.1 0.9 0.3 0.9 1.1 0.9 0.8
4.1 7.7 2.4 10.3 4.3 8.1 9.9 8.8 5.3
3.8 6 2.7 7.8 5.4 6 7 6.1 4.3
7 37 7 52 17 36 49 42 22
0 10 0 26 8 5 18 8 3
1.2 0.9 0.6 0.3 0.8 0.7 1.1 0.8 0.6 0.6
5.6 11.3 10.5 14.1 11.4 7.8 14.9 11.2 8.9 7.2
3.9 9.1 7.5 8.8 10.2 9.1 9.5 8.3 14.7 7.3
15 55 52 65 56 42 74 56 47 36
0 43 22 42 52 42 45 28 81 21
0.8 2.1 1.6 1.7
6.4 9.5 8.3 5.2
3.5 4.8 5 1.6
12 45 26 0
0 1 0 0
0.7 1.6 1.5 0.6
1.2 8 13.9 11.5
2 2.3 11 5.3
8 3 71 57
0 7 64 9
1.3 0.4 0.5 1.4 0.4 1
8.9 2.9 4.2 6.4 3.5 8.3
7.8 4.6 3.4 2.6 3.2 6.5
41 14 17 0 11 41
14 7 1 0 1 15
Livestock and Dairy Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
27 41 5
28 35 7
Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
15 5 5 5 5 12 2
9 1 4 29 2 26 3
12 4 2 30 2 37 5
9 3 4 29 1 23 2
13 4 3 30 2 28 5
Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybeans Wheat (Hard Red)
32 21 38 17 35 17 12 17 21
34 25 38 15 32 23 16 20 31
32 22 36 16 24 22 19 21 29
38 24 38 14 31 25 16 19 30
35 21 35 15 23 27 18 23 30
Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
11 17 27 35 21 26 12 21 27 27
30 12 14 7 11 24 5 13 18 27
31 10 17 13 8 10 9 14 1 18
33 13 14 8 11 19 5 11 17 25
35 10 16 11 8 11 9 14 1 17
Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
21 1 2 43
28 17 21 40
33 27 26 39
35 18 28 41
35 32 35 35
39 42 5 27
39 42 8 10
40 37 6 25
37 40 7 10
35 25 5 22
10 32 31 40 32 15
18 36 33 41 35 21
15 28 34 41 35 20
21 34 31 41 36 21
20 25 32 35 32 19
Precious Metals Gold Palladium Platinum Silver
Softs
Softs Cocoa Coffee Cotton (No. 2) Lumber Orange Juice Sugar (No. 11)
42 43 7
Livestock and Dairy
Precious Metals Gold Palladium Platinum Silver
37 43 6
Industrial Metals
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
37 41 2
Grains and Oilseeds
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybeans Wheat (Hard Red)
Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
Energy
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
Probability that return exceeds 10%: 5year 10year
Indexes
Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
Relative Forecast Return Valuation 5Year 10Year
Cocoa Coffee Cotton (No. 2) Lumber Orange Juice Sugar (No. 11)
560  David J. Howden This approach yields many of the same results as does an exclusive look at the period forecasts. Here the expected returns can be interpreted as the median return that the investor can be expected to earn by making an investment each month over the next five and ten years. For example, the expected annual return of 6.8% in the Baltic Dry Index over the next five years implies that for any investment made between July 2020 and May 2025, half will yield a return greater than that level and half lower if the investments are sold on the common date of June 2025. Likewise the expected annual return of 2.5% over the coming decade means that if an investor bought the Index each month between July 2020 and May 2030 and sold his whole portfolio in June 2030, half of those months would yield an annual return greater than 2.5% and half less. In general, energy and the industrial metals are expected to outperform other commodities over both of these periods. Grains and livestock are expected to underperform by this measure, and the precious metals and softs are a mixed bag. The worst expected returns over the next five years belong to canola, milk, lean hogs, the VIX and palladium. Not surprisingly, all of these markets are either in down trends or are close to peaking in their current bull markets. This, combined with generally low period forecasted returns over the next five years (the result in almost all cases of highly overvalued prices), yields the inferior returns of the group. On the other side of the list are the top five commodities in terms of their expected returns over the coming five years: uranium, sugar, cobalt, cocoa, and coal. These five commodities all share in common a price position in the nascent stage of fresh bull markets. Combined with reasonably high forecast returns over the next five years, the result is stellar expected overall returns. The bottom five commodities in terms of their expected performance over the coming decade are mostly the same ones as over five years. Canola, milk, lumber, palladium and the VIX round out the bottom of the ranking. There we see the reason being the combination of the poor fiveyear expected returns and low forecast period returns over the next decade. In other words, neither cycle analysis nor the period returns give much reason to expect returns to be anything more than abysmal over the next decade. Not coincidentally, these commodities also among the most overvalued by the relative valuation measure. The top five expected returns over the next ten years are almost all dominated by energy commodities: Brent crude oil, heating oil, RBOB gasoline, West Texas Intermediate crude oil, and scrap steel are all expected to yield annual returns of at least 15% over the coming decade. This group shares in common a position at the start of a new bull market advance for each commodity, and also relatively high period forecasts over the next decade. (They also are among the most undervalued commodities of the group.) These rankings are dependent on both the statistical analysis by way of the period forecasts, and also on the cycle analysis. In both cases the exactness of the forecasts is not perfect, and even though I have tried to quantify this aspect by listing the goodnessoffit of the models and the associated return probabilities, a qualitative approach is more useful. After all, since many common factors are used to estimate these forecasted returns, all commodities could be biased too high or too low in the estimates. Relative to one another, however, a ranking should be maintained. In absolute terms the forecasts and expected returns may be too high or low, but relative to each other the qualitative ranking should be preserved.
Commodities, the Decade Ahead  561 To summarize these results, it is helpful to give an overall rank. This rank corresponds to the median value of the rank that each commodity and index has across three categories: relative valuation, and the 5 and 10year expected returns. RBOB gasoline is expected to yield the greatest return for the investor over the next ten years. From its current price of $0.57 per gallon the fuel´s 5year period forecast estimates an advance to $2.68 by June 2025. From there a brief cooling as its cycle high of $1.90 forms in February 2027 should occur, before the fuel rises to $3.52 per gallon by June 2030 as its 10year forecast calls for. Gasoline´s relative valuation 2.4 standard deviations below its fairvalue level is not only more underpriced than 99% of its previous monthly closes but is the lowest valuation since 1986. It also happens to be the third most undervalued commodity of the group. Palladium, on the other hand, is expected to yield the worst results. From its current price of $1,932 per troy ounce, the precious metal is expected to collapse into its cycle low of $742 by March 2022. From there support will come with mildly higher prices over the rest of the decade. By June 2025, its period forecast calls for a price of $1,276 and $2,432 by June 2030. Palladium´s relative valuation of +1.6 standard deviations above its fairvalue level is the highest since 2001 and makes the metal more overvalued than only 6% of all its monthly closes. It also makes the precious metal the second most overvalued commodity of the group. Given the magnitude of the difference between the expected returns of gasoline and palladium, supported by multiple pieces of evidence from several distinct methodological approaches, it is safe to say that gasoline will make the better investment than palladium over the next decade. The 24.9% difference in returns between the two commodities would need a sizable error to leave the investor with a loss if he bought gasoline and sold palladium today. Still, to mitigate the threat that an error could result in the analyses, we can rely on a broader portfolio to diversify these risks away. A portfolio consisting of the top five ranked commodities – RBOB gasoline, heating oil, West Texas Intermediate crude oil, uranium, and platinum – will almost certainly outperform the bottom five ranked commodities – gold, lumber, milk, the VIX, and palladium. Of course, propensity for risk, local tax laws, and availability of investment vehicles (and their costs) all play a role when the investor makes his choice of what markets he will allocate his funds to. Plus, while these rankings are based on an overall position taken over the whole of the coming decade, the individual commodity reports shed light on some specific timing issues that may help the investor to earn even greater superior returns. Caveat creditor.
562  David J. Howden
Commodities, the Decade Ahead  563
Commodities, expected return summary
Commodities, overall ranking summary
Relative Expected returns: Valuation 5Year 10Year Indexes Baltic Dry Index CBOE Volatility Index S&P GS Commodity Index
0.1 1.6 1.6
6.8 17.7 6.2
2.5 11.6 10.9
1.0 1.5 1.5 1.5 1.5 1.1 1.6
40.7 22.5 20.7 8.7 23.9 28.5 21.2
12.7 18.2 16.8 6.1 18.2 7.3 17.1
0.4 0.8 0.1 0.9 0.3 0.9 1.1 0.9 0.8
0.4 36.9 15.7 38.5 4.6 32.5 32.6 24.9 25.3
0.5 7.7 2.7 10.3 4.4 8.1 8.1 8.8 5.3
1.2 0.9 0.6 0.3 0.8 0.7 1.1 0.8 0.6 0.6
16.8 50.5 14.8 13.7 11.2 8.5 32.4 23.0 77.9 22.9
5.5 11.3 10.4 12.8 10.2 8.8 14.8 11.2 14.8 7.5
0.8 2.1 1.6 1.7
6.9 8.5 9.2 1.3
7.0 5.2 8.9 2.4
0.7 1.6 1.5 0.6
26.4 26.9 28.1 13.1
1.2 7.8 13.9 13.1
1.3 0.4 0.5 1.4 0.4 1.0
42.0 37.8 39.1 7.5 19.0 63.8
8.9 4.6 4.2 2.9 3.3 8.3
Energy Coal (Newcastle) Crude Oil (Brent) Crude Oil (West Texas Intermediary) Ethanol Heating Oil Natural Gas (Henry Hub) RBOB Gasoline
Grains and Oilseeds Canola Corn Oats Palm Oil Rough Rice Soybean Meal Soybean Oil Soybeans Wheat (Hard Red)
Industrial Metals Aluminum Cobalt Copper Iron Ore (62% Fe) Lead Nickel Scrap Steel Tin Uranium Zinc
Livestock and Dairy Feeder Cattle Lean Hogs Live Cattle Milk (Class III)
Precious Metals Gold Palladium Platinum Silver
Softs Cocoa Coffee Cotton (No. 2) Lumber Orange Juice Sugar (No. 11)
Relative Expected returns: Valuation 5Year 10Year RBOB Gasoline Heating Oil Crude Oil (West Texas Intermediary) Uranium Platinum Crude Oil (Brent) Coal (Newcastle) Cocoa Cobalt Scrap Steel S&P GS Commodity Index Natural Gas (Henry Hub) Soybean Oil Palm Oil Sugar (No. 11) Live Cattle Soybean Meal Soybeans Tin Lead Wheat (Hard Red) Corn Aluminum Zinc Nickel Copper Feeder Cattle Ethanol Iron Ore (62% Fe) Silver Cotton (No. 2) Lean Hogs Coffee Orange Juice Rough Rice Oats Baltic Dry Index Canola Gold Lumber Milk (Class III) CBOE Volatility Index Palladium
3 5 6 28 8 9 15 10 20 12 4 13 14 17 16 2 18 19 24 21 22 25 11 30 26 27 23 7 36 29 31 1 32 34 35 38 37 33 39 40 43 41 42
22 18 23 1 14 21 5 4 3 12 36 13 10 7 2 30 11 17 19 41 16 9 25 20 32 27 34 31 28 29 6 40 8 24 37 26 35 38 15 33 39 42 43
3 2 4 6 7 1 10 18 11 5 13 26 23 15 21 17 22 19 12 16 30 24 29 25 20 14 27 28 9 8 34 31 32 35 33 36 37 39 38 41 40 43 42
Median Overall Rank 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th 13th 14th 14th 16th 17th 17th 19th 20th 21st 21st 21st 24th 25th 26th 27th 28th 29th 30th 31st 32nd 33rd 34th 35th 36th 37th 38th 39th 40th 41st 42nd 43rd
Proof