Practical Trend Analysis: Applying Signals and Indicators to Improve Trade Timing [2 ed.] 9781547401086, 9781547417216

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Michael C. Thomsett Practical Trend Analysis

Michael C. Thomsett

Practical Trend Analysis Applying Signals and Indicators to Improve Trade Timing Second Edition

ISBN 978-1-5474-1721-6 e-ISBN (PDF) 978-1-5474-0108-6 e-ISBN (EPUB) 978-1-5474-0110-9 Library of Congress Control Number: 2018962686 Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at http:// dnb.dnb.de. © 2019 Michael C. Thomsett Published by Walter de Gruyter Inc., Boston/Berlin Printing and binding: CPI books GmbH, Leck Typesetting: MacPS, LLC, Carmel Cover Image: Sergey_P/iStock/Getty Images Plus www.degruyter.com

Contents Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context  1 Five Assumptions about Short-Term Trends  1 The Beginnings of Trend Analysis: The Dow Theory  4 The Dow Theory Applied  9 Other Price Theories: EMH  12 Types of EMH in Theory  14 The Bubble Effect  15 Other Price Theories: RWH  17 Trend Analysis as a Risk Management Process  19 Chapter 2: Statistically Speaking: Trends by the Numbers  25 Fat Tails and Trends  26 Bollinger Bands  29 Statistical Tendencies  34 Trends and Averages  35 Trends versus Price  36 Strength and Weakness of Trends  37 Pattern Cycles  38 Market Sentiment Expressed in the Trend  40 Momentum Trading  41 Statistical Measurements and Trend Behavior Distinguished  43 Spikes and How to Manage Them  44 After the Spike: Breakouts and Reversals  46 Statistical Analysis of Fundamentals  46 Game Theory Applied to Trend Analysis  47 Magical Thinking and Trends  50 Chapter 3: Resistance and Support: A Trend’s Moment of Truth  53 Tests of Breadth  53 The Nature of Resistance and Support  55 The Channeling Trading Range  57 Reaction High and Low Prices  59 The Bouncing Price within a Trend  60 The Flip  62 Wedge-Shaped Trends  63 Triangle-Shaped Trends  65 Support and Resistance Zones  68 Breakouts as Signals of Supply and Demand Adjustment  71

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Chapter 4: Trendlines and Channel Lines: The Shape of Things to Come  73 Signal Patterns versus Trends  73 Trendlines and What They Reveal  76 Price Increments on Charts  78 Trend Angles  81 Internal Trendlines  82 Validation of the Trend  83 Retracement versus Reversal  85 Fibonacci Retracement  87 Channel Line Types  89 Expanding with the t-line  93 Chapter 5: Reversal Patterns: End of the Trend  95 The Dilemma: Minor or Major Reversal  96 Reversal versus Consolidation  97 The Time Element: Momentum of Reversal  99 Reversal in Western Patterns  100 Head and Shoulders  100 Gaps  102 Rounding Top and Bottom  104 Rectangle Top and Bottom  106 Double Top and Bottom  108 Diamond Formations  110 Reversal in Eastern Patterns  112 Long Candles  112 Doji Formations  114 Hammer and Hanging Man  115 Engulfing Pattern  117 Harami and Harami Cross  118 Doji Star  119 Piercing and Meeting Lines  120 Three White Soldiers and Three Black Crows  122 Morning and Evening Star  125 Abandoned Baby  126 Squeeze Alert  128 Divergence and its Role in Reversal Trends  130 Breakouts and Proximity to Resistance or Support  132 Conclusion  134 Chapter 6: Continuation Patterns: A Bend in the Trend  135 Continuation and its Relationship to Reversal  137 Western Continuation Signals  138

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Head and Shoulders  139 Inverse Head and Shoulders  140 Gaps  140 Rounding Top and Bottom  141 Rectangle Top and Bottom  143 Double Top and Bottom  145 Diamond Formation  147 Flags and Pennants  148 Cup and Handle  150 Eastern Continuation Signals  151 Long Candlesticks  152 Long-Legged Doji and Spinning Top  153 Thrusting and Separating Lines  155 Side-by-Side Lines  157 Tasuki Gap  159 Gap Filled  160 Chapter 7: Confirmation Signals: Turning the Odds in Your Favor  163 The Causes of Price Movement  163 Behavioral Psychology and the Market  165 The Flaw of Overconfidence  166 Resistance and Support as Keys to Confirmation Proximity  168 Strong and Weak Confirmation  169 Momentum and Timing of Preceding Trends  172 Divergence Analysis and Confirmation  175 Fundamental Analysis and Confirmation  177 Confirmation Bias  178 Chapter 8: Consolidation Patterns; The Sideways Pause  183 Consolidation and its Meaning  184 Resistance and Support as Keys to Consolidation Reading  185 The Triangle Breakout  187 Volume Spikes and Gaps  189 Breakout Signals  191 Consolidation Plateaus  193 The Bollinger Squeeze  196 Chapter 9: Volume Signals: Tracking Price Trends  201 How Volume Confirms Trends  201 Confirmation Trends with Volume  202 Trends with Volume-Marked Breakouts  204 Trend Climax and Gap Patterns  208

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On Balance Volume  212 Accumulation/Distribution  213 Money Flow Index  215 Chaikin Money Flow  218 Chaikin Oscillator  219 Chapter 10: Mind the Gap: When Price Jumps Signal Change  223 The Nature of Gaps  223 Gaps Filled or Unfilled  225 Gap Up and Gap Down  227 Common Gaps  228 Hidden Gaps  230 Breakaway Gaps  232 Runaway Gaps  233 Exhaustion Gaps  234 Island Cluster  235 Ex-Dividend Gaps  236 Gaps as Part of Other Signals  237 Gap Proximity to Resistance or Support  238 Chapter 11: Moving Averages: Order in the Change  241 Two Moving Averages  242 Bollinger Bands  244 Convergence  246 Divergence  246 Price Crossover  247 MA Double Crossover  250 Resistance and Support  252 Chapter 12: Momentum Oscillators: Duration and Speed of a Trend  257 The Nature of Momentum  257 Relative Strength Index  259 Moving Average Convergence Divergence  263 Stochastic Oscillator  266 Chapter 13: Volatility: Marking Risk within the Trend  271 Calculating Volatility  271 Volatility Indicator  273 Evolving Volatility Levels  274 Average True Range  279 Volatility According to the VIX  282

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Chapter 14: Fundamentals: Connecting the Two Sides  285 Value Versus Growth  285 The Concept of Fundamental Volatility  286 Dividend per Share and Increased Dividends   287 P/E Ratio  290 Revenue and Earnings  291 Debt to Total Capitalization Ratio  292 Comparing Fundamental Trends to Technical Trends  294 Chapter 15: Overview: Putting It All Together  305 Moving from Downtrend to Consolidation  306 Secondary Trend Volatility  309 Large Price Move Ending Primary Trend  311 Primary Trend with Secondary Trend  313 Consolidation Primary Trend with Failed Breakouts  315 Conclusion  317 Bibliography  319 Index  323

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Introduction to the Second Edition: The Basic Problem with Numbers In the first edition of this book, the purpose was to fill in the many gaps discovered in the literature about stock market trends. This book is intended as a serious study of trends for experienced investors and traders. These individuals know how trends behave but also need to solidify their analytical tools for trend analysis. There are no simple answers to predicting trend direction, strength, or duration. However, specific tools technicians favor can be used in combination to anticipate trend reversal or continuation, and to confirm those moves. Many books have been written on this topic; however, most are outdated and do not provide readers with a practical view of how trends work and how they can be studied. The best known book on the topic was first published in 1948, and in the new edition, the charts are seventy years out of date and limited to line charts; there are no candlestick charts in the book (although, ironically, the cover art shows a representation of candlestick patterns). One chart compares industrial to “rails,” an old term for what today is called the “transportation” average. The purpose here is not to criticize other published books, but to point out the lack of practical and actionable information about trends. No other book truly addresses the methods of technical analysis needed to properly understand short-term and long-term trends and how to determine whether they will continue or reverse. Most books do not address the third type of trend (beyond bullish and bearish), the sideways-moving trend or consolidation. Many books refer to this as “continuation,” which is an error of definition. These and other issues led to the publication of this book’s first and updated editions, with added emphasis in the many areas useful to traders. The trend, after all, is supposed to be somewhat predictable. Traders employing all the technical tools can improve timing of entry and exit of their trades and overcome the elusive and often mysterious unpredictability of market prices. Price movement is not as unpredictable as many believe; it is only a matter of traders’ uncertainty about how to read the signals and how to move confidence as close as possible to 100 percent so that trades can be timed expertly. Getting to 100 percent is impossible because even the strongest signals will fail or mislead at times. The purpose of trend analysis is not to become perfect in timing the market, but to improve the percentages of being correct versus being wrong, or settle for 50/50. Contrary to the pessimistic conclusions of some market theories (efficient market hypothesis and random walk hypothesis), it is possible to predict price movement. One goal of this book is to convince the reader that it is possible (very

DOI 10.1515/9781547401086-003

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possible) to profit in the market with improved timing. It comes down to how you define the market. Many will say the market is efficient or random, or both. Is this a fair definition of the market? No. Many technical tools offer powerful predictive qualities and enable you to improve well above the 50/50 “guess” many claim defines the market. The claim to efficiency or randomness (usually made by those who do not trade in the real-world of the market) is demonstrably false and unsupportable. Experienced professional traders realize that the market is neither efficient nor random. Even the Dow theory, the basis of traditional technical analysis, does not agree on identification of changes in primary trends. The meaning of trends is debated endlessly among technicians. Is a change in direction a new primary trend, a secondary trend, or merely a retracement? The debate is ceaseless and there appears to be more disagreement than agreement on the basic question of how trends behave. In this uncertain trading environment, how do professional traders manage effectively? This edition offers methods of trend analysis based on a few sound principles. These include the essential observation of the trading range; reversal, continuation, and consolidation; confirmation methods; gaps; and non-price signals confirming or forecasting changes in the current trend. Every experienced trader who relies on a short list of reversal and continuation signals, who understands how chart analysis is performed, and wants to recognize changes in the price pattern, already understands how uncertain a trend can be, and how difficult it is to quantify signals in the moment. Every trader deals with conflicting and contradictory signals, and may easily overlook the larger picture of movement in the trend. These movements may be simplified and classified as reversal, continuation, or consolidation. However, this identification is never 100 percent clear or precise. Experienced traders may not be certain about the current status of individual stock trends even with an advanced level of knowledge. And those who do know also understand that the current status of a trend is likely to change at any moment. A trend in an individual stock is likely to be easier to track and predict than a trend in an index. The index contains many different stocks, so the trend is itself the sum of net increases and decreases in price levels for all the components. Furthermore, the index itself, such as the Dow Jones Industrial Average—the favorite gauge of the market—may be weighted so that a few stocks account for a large portion of a total trend movement. This makes trends of indexes less certain. Even though many stocks track the market closely, this book focuses on individual stock trends. In these cases, it is more reliable to associate trend activity with both fundamental and technical causes and responses. The many charts representing price patterns and trends are based primarily on the period between 2012 and 2016. During this period, the market did not trend strongly so that the stock charts were easy to track. Between 2016 and 2018, however, the overall market moved into a strong bullish trend. The Dow Jones Industrial Average moved 7,000 points in less than two years following the 2016 election. Because so

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many stocks followed this trend, most charts were bullish. This meant that demonstrating trend characteristics was less varied than during more typical, slower-trending markets. As a result, the charts in this book are outdated on purpose, but the visual summaries they provide are relevant to trend analysis. Using historical rather than current charts also adds the clarity of hindsight, enabling an analyst to better understand what went on and how trends and prices behaved during a past period. The first chapter reviews the basic theories about trends and examines whether or not those theories offer reliable intelligence traders can use to time entry or exit. Chapter 2 expands that discussion by introducing statistical observations traders may use to improve accuracy of both trend analysis and price pattern analysis. Chapter 3 provides in-depth analysis of how resistance and support play an essential role in trend analysis and how these trading range borders may be used to test the strength of the trend. Chapter 4 expands on the discussion with a study of trendlines and channel lines. Chapters 5 and 6 are exhaustive studies of reversal and continuation patterns; and Chapter 7 provides the same in-depth analysis of confirmation. In Chapter 8, the nature of consolidation is examined in its effect on trends. Chapter 9 takes a look at volume. In Chapter 10, gaps describe how trend movement can be anticipated in the near future and how these may be either revealing or confusing. Chapter 11 examines the role of moving averages and how these impact and anticipate changes in trends. In Chapter 12, momentum oscillators are examined in how they affect not only price, but the larger trends as well. Chapter 13 addresses the topic of volatility in the trend and Chapter 14 shows how fundamental trends contribute to technical trends. Wrapping up the entire discussion, Chapter 15 puts together multiple indicators to track how trends continue and change over time. A distinction has to be made throughout this book between price patterns and trend attributes. The study of price charts is normally focused on very short-term trends and likely reversal or continuation. This is based primarily on patterns found in candlestick charts or in the application of well-known technical signals. The key here is that price analysis is short term. However, beyond those day-to-day and weekto-week analyses and swing trading decisions, the longer-term trend may be revealing in many more ways than the price trend could possibly provide. For example, in a short-term price trend, assumed levels of resistance and support and, most notably, violations above resistance or below support, often are used as the basis for timing of trades. And in fact, movement through these all-important price levels is invariably the point where reversal or continuation signals have the greatest meaning. However, there is a problem in basing decisions on resistance and support that are short term in nature. These levels may exist momentarily, but the bigger picture is found in how resistance and support provide structure for a longer-term trend. In terms of technical trading, this can mean a matter of months rather than of days or weeks. However, the identification of resistance and support (as well as other trend attributes) only

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becomes reliable when the charter looks at this bigger picture. So a few standards are applied in this book with these concerns in mind. First, analysis of trends is focused on individual stocks and not as much on index or market-wide movement. Second, trends are studied as longer term (three months or more), a departure from the swing trading approach based on price patterns and identification of reversal signals as a primary signal. The degree to which reversal and continuation signals are analyzed is based not on the immediate price pattern but on how the trend behaves over time. The concept here is that traders expect short-term price movement to be chaotic and fast, but longer-term trends often are far more reliable in terms of where prices are heading. This is reflected in the trend and articulated by the technical analyses described in coming chapters. Even though nothing can ever be 100 percent certain or clear, the tools presented in this book will help to improve confidence in timing of trades and also in longer-term decisions to buy, hold, or sell shares of stock. The quantification of “confidence” may be described as existing between 50 percent (random likelihood of a trend moving upward or downward) and 100 percent (certainty of what will occur next). The study of a trend will always fall somewhere in between these levels, never quite falling to completely random 50 percent and never rising all the way to 100 percent. However, in that range, you will be able to define confidence in degrees that help manage a portfolio of equities and to determine levels of risk. For trend analysis, risk may be defined as a level of confidence in the current policy. For example, if you hold stock that has appreciated over several months, where does your confidence reside today? Is the trend continuing or leveling out? What do these patterns mean in terms of confidence? This theory of portfolio management, basing concepts of risk on levels of confidence in the current trend, may help you to improve timing not only of entry, but also of exit from a current position. This may be thought of not as swing trading in the short term, but of risk management for the long-term portfolio. It all relies on the trend.

Chapter 1 The Theory of Trends: Dow, EMH, and RMH in Context This book is meant to give you a detailed practical understanding of trend analysis, that part of technical analysis dedicated to trends and in particular the analysis of individual stocks. A premise of this book is that the market is neither efficient nor random and that trades can be reliably timed based on observation of price behavior within a trend. The debate as to whether the market is efficient and random, or neither, is not settled by any means. Not everyone will agree on the definition of the trend itself. A trend identifies the direction of movement in an observed price over time. In terms of stock charts, this usually refers to price. But the duration is important as well. Every trader must decide whether to adopt a short-term outlook, such as that of the day trader and swing trader, relying on fast price changes; or a long-term outlook based on the study of longer-term trends. A basic statistical reality is that the longer the period studied, the more reliable the observation. In other words, you cannot establish a trend by price action of a few days, but with price action of a few months the trend and its properties (such as resistance and support, momentum and volatility) become clear. Key Point: A trend is the action of price in a specific direction that lasts until a change in that direction occurs.

Five Assumptions about Short-Term Trends You can observe some attributes of short-term trends as the initial hint of the longer-term trend. Duration of a trend matters greatly, because a “short-term trend” may, in fact, not be a trend at all, but a retracement. This occurs when a strong price movement reverts back toward the previous price level. 1. Price acts and reacts within a larger and longer-term trend. When you look only at price and attempt to anticipate which direction it will take next, you must operate on a set of assumptions. The greatest of these is that price acts and reacts within the current trend. If you do not recognize or find a trend, the price is truly random. And some stocks are both volatile and unclear about direction, which makes any kind of trade timing both difficult and risky. But that is often a shortterm problem, whereas longer-term trend analysis is likely to identify clear trends characterized by short-term chaotic and random movement but overall identifiable direction. 2. Supply and demand for shares matters. The second assumption is that price movement reflects supply and demand within the market. While this is true over the long term, short-term price movement is likely to be characterized by DOI 10.1515/9781547401086-001

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 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

reaction to any number of information pieces, including fact and rumor, fundamental and technical clues, and investor behavior (which in the short term is often irrational and crowd-following in nature). For short-term price analysis, relying on supply and demand may not be reliable; it is more likely to be chaotic and irrational in nature. 3. Duration of a trend cannot be known in advance. A third assumption is that trends tend to continue for some length of time. However, the actual time involved varies and is not predictable, so it is ill-advised to attempt to recognize a trend and settle in on the assumption that time is on the side of the trend. This is not necessarily the case. Therefore, trend analysis must include the likelihood that an emerging signal could foreshadow the end of the trend and a reversal of price movement; and that this reversal can be caused by a variety of emerging factors, including supply and demand but also much more. Whether a change in the trend is caused by a flip in supply and demand or a less rational market belief about a company or its stock price, the change is a reality—no matter what underlying fundamentals are at play. The technical aspects of the trend (price patterns, volume, moving averages, and momentum) are based on a variety of rational and irrational influences. Therefore, you need tools for trend analysis; if prices were truly efficient in how they react to fundamental news, the market would be not only efficient but predictable as well. In fact, “efficiency” as used in observation of stock prices refers to the speed of response to information, both true and false, and not to the efficiency of price as an accurate measure of value. Markets might be quite efficient in response time, while making the distinction between responses to either type of information. 4. Markets do not behave efficiently. A fourth assumption concerns market behavior. The inefficiency of markets is easily demonstrated by a study of earnings surprises and resulting stock price behavior. Stock prices fail to account for earnings surprises and often overlook the effects of optimistic beliefs about stocks (especially growth stocks). These factors distort and may even lower net returns when earnings do not perform as expected.1 5. Most traders overreact to any surprises. A fifth assumption, notably among contrarian investors, is that most market traders and investors overreact to any surprises or uncertainties in the market. Therefore, they tend to add greater meaning to the latest news and to assign lesser meaning to older (and perhaps more reliable) information. Contrarians time decisions not merely to contradict what most market participants are doing but are more likely to act based on a different set of criteria. Most traders time and enter both buy and sell trades as a gut reaction to surprises and in the extreme will trade based on greed (when prices have risen) or panic (when prices have fallen). The contrarian, in comparison, tends to enter trades based on recognition of exaggerated price movement, especially following earnings surprises. This is done in the knowledge of a likely correction of that overreaction within a matter of a few days.

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Key Point: Trend behavior reflects market behavior; short-term price movement often is an overreaction to today’s news.

For example, on January 16, 2015, SunTrust Banks (STI) reported earnings of $394 million, down from $426 million in the prior year’s quarter; and earnings fell from 77 cents to 72 cents per share. This negative surprise caused the stock to drop approximately 5 percent in two days. However, price rebounded in the immediate sessions following the drop. This is typical of price behavior and demonstrates the contrarian advantage. The initial response to a negative earnings surprise was a substantial drop in price, but that was immediately corrected. A contrarian acting on knowledge of the behavior would be likely to take bearish trade action on January 16 and then close the position to take profits on January 19 or 20 when price had corrected the overreaction. This price movement is summarized in Figure 1.1.

price rebounded in later sessions

support

stock price declined on earnings date

Source: Chart courtesy of StockCharts.com Figure 1.1: Reaction to earnings surprises

The apparent price action is typical of short-term movement especially in reaction to earnings surprises. A positive surprise would be expected to behave in the same manner but with prices moving upward in an overreaction and then correcting in following sessions. Testing for this price behavior is difficult for short-term price action, whereas longer-term trend analysis discloses far more reliable patterns including reversal or continuation. A basic error made by many traders is to assign too much value to the shortterm trend, and this begs the question about the value of studying longer-term trends.

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 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

The assumption many traders hold is that of price correlation, the belief that today’s price trends correlate with or mirror previous price changes. This is not the case. The price correlation assumption has served as the basis for criticism of technical analysis in support of a random theory about the markets. However, it is applicable as a criticism only to the degree that traders act on the assumption of price correlation. An enlightened trader or investor, especially a contrarian, rejects this assumption and acknowledges that a current price pattern and activity within an existing trend is separate and apart from prior price behavior. Key Point: Price correlation—a belief in the connection between price moves and previous price changes—is misleading and is not a reliable basis for trend analysis.

The Beginnings of Trend Analysis: The Dow Theory The science of trend analysis began with Charles Dow. A reporter, he gained attention when he published a series of articles in The Providence Journal. He moved to New York and established Dow Jones & Company with his partner, Edward Jones. In 1883, they published their first daily paper, the Customer’s Afternoon Letter. Six years later, this two-page newsletter was expanded and renamed the Wall Street Journal. The extraordinary thing about Dow was his observation that financial information about a company could be tracked and trends developed to quantify financial values. This was the study of fundamental information, a company’s revenues and earnings over time. Dow did not imagine his trend analysis skills applying to stock prices, as his interest was on the fundamentals only. This was decades in advance of the SEC requirement for public companies to publish audited quarterly and annual statements. Dow’s emphasis was on pointing out the truth about financial trends, especially for companies that manipulated reported profits and losses. This was occurring in an era before regulation, when corporate reporting was often highly unreliable and even deceptive. Dow’s publications included quarterly and annual information about many publicly traded companies. Key Point: Charles Dow developed the trend to track financial information. His theory was later applied to stock price behavior and today is the basis for trend analysis; it has been named the Dow theory.

Dow also devised the first stock averages. The first such index consisted of nine railroads, a shipping line, and Western Union, as well as a handful of other traded companies. Railroads were emphasized because they were the most actively traded types of companies at the time. Dow passed away in 1902, well before the concept of tracking averages and the Dow theory itself were formalized. Eventually, the first set of averages evolved and formed the basis for how market wide trends are followed and how reversal is signaled. However, Dow himself saw the study of averages as useful

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in observing business trends but not for tracking stock prices and trends. The Dow theory as it is known today was developed over many years by Dow’s successor as editor of the Wall Street Journal, William P. Hamilton. A problem with any type of collective analysis, including the thirty stocks in the Dow Jones Industrial Average (DJIA) is that movement in the index represents the net of all movements of the components, both up and down. Although the DJIA is the most popular version of what investors consider “the market,” it does not represent the tendencies or trends of any individual stocks. It may, in fact, cloak what truly is occurring in many stocks outside of the selected components of the DJIA or any other average. Another flaw is found in the weighting of the DJIA, resulting in heavy influence of a few companies. For example, as of September 12, 2018, five stocks accounted for one-third of the total weight of the DJIA: Boeing 9.2% UnitedHealth 6.9% Goldman Sachs 6.0% Apple 5.8% Home Depot 5.5 % Total 33.4%2 This may be troubling to many investors and traders. These five companies represent one-third of “the market” based on their weight on the DJIA. A price-weighted index like the DJIA starts out by adding together the price of the components and dividing it by the number of stocks. However, any time a stock splits, the divisor is adjusted. The net result of this is that higher-priced stocks end up having more impact on the overall index weight. Therefore, five stocks account for one-third of the index value. This is a troubling reality. It means that “The Dow” does not represent what is happening in the market but only what is happening among thirty big companies. It’s true that stock values tend to follow the DJIA, but when you consider how these stocks are weighted, it is deceptive at best. In this respect, the wishful thinking behind the tracking of such an average is a type of “cloud cuckoo land” for investors.3 Key Point: The method of weighting indexes like the DJIA means that “the market” is influenced by only a handful of companies. This may easily distort how DJIA movement affects an individual stock’s performance.

In addition to the DJIA, three other indexes are used by the market, and this is an essential element of the Dow theory. They are the Dow Jones Transportation Average (DJTA), consisting of twenty transportation companies (airlines, trucking companies, shipping, and railroads); the Dow Jones Utility Average (DJUA), including fifteen utility companies; and the Dow Jones Composite Average (DJCA), an index of all sixty-five stocks in the other three indexes.

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The Dow theory is designed to track the overall market trend and not individual stocks. However, many of the principles about confirmation in the Dow theory apply equally to trend analysis of individual stocks. This discipline establishes rules of trend analysis and is what gives the Dow theory prominence and value among traders. It is not so much the movement of the average that matters but application of the rules establishing and defining trends in general. The Dow theory forms the core of trend analysis of stocks. The theory includes six basic tenets: 1. The market contains three movements. These are the primary (major) trends that lasts from under one year up to several years, and may be either bullish or bearish; the medium (secondary reaction) trend, lasting from two weeks to as long as three months, and assumed to retrace from 33 percent to 66 percent of primary movement since the beginning of the primary trend; and the minor (swing) trend, lasting from only a few hours up to a month or more. These three trends tend to coexist. For example, a medium trend plays out within the longer-term primary trend; and the swing trend serves as an adjustment to the medium trend. Key Point: Trends make sense when the three specific types are acknowledged. Even so, it is impossible to forecast how long a trend of any duration will continue.

2. Market trends go through three distinct phases. For bull markets, these are the accumulation phase, characterized by the purchase of shares among knowledgeable investors; the public participation phase, in which a broader cross-section of the market recognizes the popularity of a company and buys shares of its stock; and a distribution, or selling phase. During the middle phase of public participation, another phenomenon occurs. Speculation levels increase as traders buy shares in the belief that prices are going to continue rising into the future. As this occurs, knowledgeable investors (who began buying when no one else was) now begin selling against the speculative fever. The phases of market trends reveal why the contrarian approach make sense. Most market participants (the “crowd”) invariably miss the changes in trends and tend to buy and to sell at the worst times. For bear markets, three phases also occur but in a different sequence. First is a distribution phase, in which knowledgeable investors begin disposing of shares that have appreciated to the point of being overbought. The middle phase is a bearish version of public participation in which the market at large recognizes that the trend has turned. Selling activity spreads as the bear market expands and this phase may also be characterized as a panic phase. Most investors want to get out of long positions before prices drop further. The third phase continues the selling activity in a widespread segment of the market and a slowing down

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 7

of price declines. During this time, a gradual return to accumulation of shares occurs among knowledgeable investors who recognize that prices have declined to bargain levels. The overall decline is likely to slow and even to move into a sideways consolidation phase. The three phases do not apply in the third type of trend, a sideways movement known as consolidation. This period can last several months or even years, during which prices are in a range bound by a narrow breadth of trading. The lack of identifiable phases does not make consolidation any less of a trend than bull or bear markets; it is, however, more difficult to interpret. Key Point: The three distinct phases of every market define investor behavior and enable investors to track a trend’s development over time.

3. The market discounts news and this is reflected in prices. One efficiency of the market is that all news is absorbed and reflected in stock prices immediately. However, this does not confirm the efficient market hypothesis (EMH)that states that reaction to news is always efficient. The fact that all news is discounted immediately does not make a distinction between true and false news. It also does not mean that price reaction is reasonable. Some forms of news (such as earnings surprises) cause an immediate overreaction in price, which is then adjusted (later during the same session or in one to two sessions that follow). This belief cannot be proven beyond doubt. However, it is a worthwhile part of the theory behind trend behavior. It explains retracement or sudden turns in trends, whether the theoretical and underlying reasons for these movements are caused by news or by other factors. It also does not explain why prices change based on rumors that have not been confirmed. In practice, this discounting of news (broadly speaking) may act in an inefficient manner. This better explains actual price movement in the short term, which tends to be highly chaotic. Key Point: Even though markets are efficient in the immediate discounting of price for known information, it does not make a distinction between fact and rumor.

4. Averages must confirm one another before a change in the trend is acknowledged. This is a simple idea. For a trend to be acknowledged as new and opposite of the previous trend, it must be witnessed in the major average (the DJIA) and confirmed in one of the others (the most popular being the Transportation Average). However, in practice, analysts do not always agree about whether confirmation has occurred when a turn in direction occurs. Some will believe it is confirmation, but others will deny this and call it a retracement or a secondary trend. The reliance on the transportation sector made sense at the end of the nineteenth century. At that time the United States was a leading industrial and manufacturing country and factories depended on railroads to ship their products to

8 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

the market. Dow’s original belief was that activity among railroads reflected the state of the economy. This was true in 1900 and it remains true today. Even with a decline in manufacturing activity in recent years, the United States remains a dominant manufacturing force in the world, second only to China.4 Charles Dow believed that a bull market could occur only if both industrials and railroads rallied together, and that by the same argument a bear market was not valid until a decline in the industrials was confirmed by a decline in the rails. Even with today’s global markets, this logic may still apply and it explains why the same requirement for confirmation is used. Even though transportation now includes not only rails but trucking, shipping, and air freight companies, the connection between industrial profits and transportation activity is direct. Key Point: Confirmation is a key element of all changes to an existing trend. No reversal can be accepted without strong confirmation.

5. Trend status is confirmed by volume of trading. Another form of confirmation is found in volume. The shares traded and, more specifically, changes in that number (either a higher or lower number of shares traded) tends to confirm a change in the mood of the market and thus in the trend as well. A smaller level of volume is not as significant as a larger volume, especially when that volume spikes much higher than a typical level of trading activity. This indicates greater interest in that stock, whether among buyers or sellers. Dow speculated that high volume represented the true sentiment of the market, driven by one side or the other; and that increased volume signaled the direction to follow in the trend as well. As a form of confirmation, under this theory, a sudden increase in volume may signal the end of a current trend and beginning of a new one. When this logic is applied to individual stocks, it clearly confirms other reversal signals. The application of the idea to marketwide averages like the DJIA is not as certain. However, as a tenet of the Dow theory, the role of volume has led to recognition among traders that volume indicators should not be ignored in the analysis of trends and reversals. Key Point: Volume is directly related to price and often anticipates coming changes in the current trend.

6. Trends continue until specific signals show that they have ended. The final tenet of the Dow theory is logical. A trend remains in effect until reversal signals and confirmation reveal that the trend has ended and reversed. This applies to averages as well as to individual stocks. This rule about trends is profound for many analysts. Trends do not suddenly end for no reason or without signals announcing their end. Those who subscribe to the random walk hypothesis (RWH) would disagree, claiming that all price movement is entirely random and movement in either direction is 50/50. However,

The Dow Theory Applied 

 9

if that were true, it would be impossible to spot specific trends and unlikely that price movement would be able to continue in one direction for any duration. A 50/50 random chance occurrence would dictate that prices would rise and fall in either direction about half the time. The existence of very real trends disproves this idea. Dow was correct: trends continue if no signal arises to point to reversal and confirmation of the end of the trend. Key Point: Trends continue until reversal signals are located. Trends never simply end for no observable reasons.

The Dow Theory Applied The tenets of the Dow theory can be observed in the study of price charts, more in hindsight than in foresight. Now of analysis, it is more difficult to interpret the meaning of a reversal in price. It might be a retracement or a secondary trend or it might be the beginning of a new major trend. As applied to individual stocks, all the Dow tenets serve as important features of charts and the discipline of technical analysis. To study the Dow theory in practice, a review of price charts for the industrials and transportations is instructive. Even with the imperfections of price-weighted averages like the DJIA, the tenets of this theory provide a foundation for analysis of trends in individual stocks. The biggest decline in the DJIA in history occurred between October 2007 and March 2009, when the index lost 54 percent of its value. From a high of 14,164.53, the DJIA ended at 6,542.05 on March 9, 2009.5 After that big bear market, the DJIA bounced back to its previous five-digit levels. Tracking this history, the DJIA chart in Figure 1.2 reveals the long-term trend in effect for three years. In the first two years, a long-term primary bullish trend was in effect. A secondary trend moved the index lower, only to then resume the major trend. Later, the market resumed and continued this long-term bullish trend. The year 2016 ended below 20,000. By September 2018 the average had moved up to over 26,000 but at year end was at 23,387.

10 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

Dow Industrials—2009 to 2011

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secondary trend

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resumption of major trend

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ma

Dow Industrials—2012 to 2016

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resumption of major trend

Source: Chart courtesy of StockCharts.com Figure 1.2: Dow Industrials—2009 to 2016 Key Point: A review of historical price behavior reveals the predictability of price within clear trend movements.

Under the most often watched tenet of the Dow, confirmation by a second average, the Dow Transportation Average tracked the industrials with remarkable consistency. Not only did the Transportations follow the DJIA down from 2007 to 2009, it also confirmed the return to a bull market between 2009 and 2011 and from 2012 through 2016. This is shown for the same period in Figure 1.3.

The Dow Theory Applied 

 11

Dow Transportation—2009 to 2011

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on mati

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sista

of re

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gt

min

fir con

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a em

nd

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confirming the secondary trend

confirming resumption of the major trend

Dow Transportation—2012 to 2016

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nd resumption of major trend

su

Source: Chart courtesy of StockCharts.com Figure 1.3: Dow Transportation—2009 to 2016

The long-term established rising line of resistance was similar for both averages and support, also rising, marked the major trend. The most significant feature of this confirming chart occurred in mid-2011, when a secondary trend in the DJIA took the index down 2,000 points over a three-month period. Was this a valid trend? With confirmation by the Transportation Average, it was clear that the direction had changed. Even so, the question remained: Was this a new primary bearish trend or only a secondary trend? The answer was revealed in the last three months of 2011 when the DJIA turned once again and rose sharply and this turn was mirrored by the Transportation Average. Similar patterns and confirmation followed between 2012 and 2016. The comparison makes the point that when direction of a primary trend changes and is confirmed, the trend itself (primary or secondary) is real. During this period,

12 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

an additional number of swing trends were also seen, which is typical of any trend over time. Key Point: The confirmation of DJIA trend reversal is found in similar changes in a second average, often the Transportation Average.

Chart interpretations are subjective. Distinguishing between a secondary trend and a swing trend is a matter of opinion and difficult even in hindsight. The most difficult part of this analysis is in reading the meaning of reversals and confirmation in the moment. Does a strong reversal mean the trend has ended? Or is it one of many swing trends or a new secondary trend? Analysts who study the Dow averages rarely agree universally on what current trends mean. For averages like these, confirmation beyond a second average is the most dependable form of confirmation. For individual stocks, many additional types of confirmation may be applied more effectively because one stock is tracked more accurately than an index consisting of many stocks. Key Point: Is a trend a secondary or a swing trend? Because the duration overlaps, it often is difficult to know. However, the important thing is to recognize when reversal has occurred.

The comparison between the Industrial and Transportation Averages establishes the validity of the concept itself. Confirmation reliably and consistently reveals the nature of trend movement. Beyond the Dow theory, additional ideas about the market should be discussed as well. Two of these pertain more to price patterns than to trends, but they define concepts about how the markets work. These two are the efficient market hypothesis (EMH) and the random walk hypothesis (RWH).

Other Price Theories: EMH The markets are sometimes described as informationally efficient. This means not that price movement is purely efficient, but that price movement is efficient in the way that it responds to publicly known information (whether true or not). The theory goes on to explain that because of this efficiency, it is not possible to consistently beat the average returns of the market. The origin of EMH is traced to 1970 when Professor Eugene Fama of the University of Chicago Graduate School of Business (the Booth School) wrote that better than average returns are not possible based on the analysis of historical price information.6 The distinction between absolute efficiency and informationally efficient markets is worth evaluating. If you assume that “information” includes both true and untrue forms, earnings surprises, and other announcements that are not truly influential in valuation of a company’s stock, then it is likely that market prices react

Other Price Theories: EMH 

 13

efficiently (immediately). However, markets cannot be considered efficient in a real sense because of the obvious overreaction of price to immediate news (earnings surprises being primary in this observation). Fama did not agree with this distinction. He wrote that, In an efficient market, competition among the many intelligent participants lead to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which as of now the market expects to take place in the future.7

This belief is not universally accepted; in fact, many have challenged it. One study concluded that, Significant return from technical analysis, even in conjunction with valuation methods, tends to argue against the efficient market hypothesis. Consequently, there is a close link between the validity of technical analysis and the inefficiency of the market.8

There can be no absolute or conclusive belief concerning EMH because it is a theory. Studies are based on what is observed in price behavior. However, for anyone following secondary or primary trends, the concept of efficiency in the market may be questioned and ample evidence exists that momentum of trends changes over time and often reversals can be accurately predicted with the use of strong indicators and confirmation. If prices relied solely on efficiency in the markets, prices would reflect information rather than the momentum of trends. These two attributes—information and momentum—are not likely to match up consistently. Key Point: The “efficiency” of markets refers to the speed of discounting based on known information. It does not mean that information is reliable or even true.

Unlike information such as earnings surprises or merger announcements, trends are statistically likely to become established with a duration, level of momentum, and slope of change within the chart and to continue until that momentum changes and the trend slows down, pauses, or reverses. Thus, information tends to occur without any reliable or predictable schedule, whereas the shape and duration of trends tends to act within the boundaries of what can be observed statistically. Among the statistical tendencies of trends are frequently observed characteristics. These include price patterns of a specific nature that anticipate reversal or continuation of swing trends and secondary trends; the proximity between discovered signals and the price points of resistance or support; and the strength of signals and confirmation. These characteristics relate to price patterns within swing trends but may also be observed in secondary and primary trends.

14 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

Types of EMH in Theory Studies of the efficient market theory have led to a breakdown into three distinct types: weak, semi-strong, and strong. The weak form observes that prices reflect all publicly known information from the past. In the semi-strong version, the belief is expanded to include both past and current information and, further, that traded security prices change instantly so that the current price always reflects all known information. The strong form of EMH expands to the belief that prices also reflect insider information not known to the investing public. These distinctions all raise a key question about the efficiency of the market. Does it include any distinction between reliable or true information, versus rumors that may end up being unfounded? Does “efficiency” mean that reaction to earnings surprises is also rational or normal? This must be questioned because it often occurs that an earnings surprise causes considerable price movement beyond what would appear rational and that price tends to retrace and self-correct within a short period of time. This often occurs within the same trading day as the day when earnings were announced, or within two to five days after. These price gyrations are far from efficient. In fact, they are both inefficient and irrational, which are the true characteristics of the market. A trader must expect to see this short-term chaotic price behavior, while also knowing that exaggerated price volatility tends to self-correct quickly. A logical conclusion is that while the market reacts efficiently to information, price movement is not always rational and does not always reflect an accurate reaction. The price reaction may be efficient in the sense that it occurs quickly, but it is not efficient in terms of the degree of movement based on the relevant information. The word “efficient” is inaccurate because of this. A more accurate world would be “responsive,” meaning that prices respond immediately, even when the overreaction so often seen will retrace back toward a more normal (or, efficient?) level of price change. One alternative way to address this issue is to speculate about whether the markets act or react efficiently. Anyone who has seen the price reaction to earnings surprises knows that the immediate reaction to the surprise is very likely to be an overreaction, to be followed quickly by a correction to that overreaction. So even if markets are efficient in the reaction to information, they are not able to distinguish between true and false information, and the reaction itself is by no means efficient. Key Point: It is possible, even predictable, that price will react efficiently, even when the level of reaction is inefficient. This leads to immediate correction of overreactions, especially to earnings surprises.

For trend analysis, this distinction is a key one. Anyone relying on the behavior of the trend will notice the statistical tendency of trends over the long term to behave in

The Bubble Effect 

 15

a mathematically predictable manner, moving with a specific momentum and stopping or reversing only when that momentum changes. This is predictable and rational behavior. However, the efficiency of reaction to information may not always lead to an efficient or rational price movement in the short term. For this reason, reliance on technical signals and confirmation popularly applied to price patterns and swing trends also can be applied to longer-term trends with equal reliability. The problem with EMH is that it does not indicate “efficiency” at all in the price of a stock, but rather describes efficiency in the speed of discounting information into the price. Another way to describe the problem with EMH is to analyze its message in relation to market behavior. EMH requires that investors and traders act with rational expectations, an economics hypothesis stating that predictions and expectations are equal to the expected value derived statistically.9 This efficiency standard assumes that investors tend, as a group, to behave rationally and to apply logical standards based on relevant information and to update their predictions based on newly-revised information. This obviously inaccurate assumption recognizes the tendency among individuals to overreact or underreact to specific information while believing that the market will behave efficiently. The assumption about overall markets acting efficiently does not match with the observed technical science of trend patterns and observations. Even on the basis on averages like the DJIA, the confirmation from a second average like the Transportation Average is remarkably consistent and demonstrates the strength of confirmation even among dissimilar organizations. Even with the flaws of weighted averages, the primary trend confirmation challenges EMH. Even the extreme primary trends like the bear market from 2007 to early 2009 that took the DJIA down 53 percent cannot be deemed as efficient. The fundamental attributes of the thirty DJIA stocks did not rationally justify a 53 percent drop in overall index value; even so, the index dropped despite the known fundamentals of the companies that made up that index.

The Bubble Effect The EMH concept is comforting in a sense. It explains how markets are supposed to work and adds an element of consistency and predictability to the markets, even though markets do not act in accordance with those ideas. Markets are more likely to go through price bubbles, and over time numerous bubbles have appeared and even more readily disappeared. Bubbles are followed by sudden and violent adjustments like Black Monday in 1987 and the demise of the dot.com sector following its bubble. During bubbles, “the market” may experience times of irrational exuberance, a term first used by Chairman of the Federal Reserve Alan Greenspan.10

16 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

Key Point: A “bubble effect” demonstrates that long-term trends are subject to short-term distortions. These tend to self-correct quickly.

The extreme market movements between 2007 and 2009 have drawn EMH into criticism. Following the 2009 decline, several published criticisms of EMH made the point that efficiency is not necessarily at play, especially during a period when primary trends are strong and long-lasting. It may also be the case that a reduced level of accuracy in financial disclosures reduces the efficiency of markets, rather than conforming to it.11 This criticism of EMH points to the flaw based on wording. Investors and traders who subscribe to EMH often do not understand the distinction between informational efficiency and accuracy. They take “efficiency” to mean that markets are accurate, and as prices move in response to information they tend to behave inaccurately and to correct (and at times, to overcorrect). None of this short-term price behavior is efficient. The problem within the market is the mistaken belief that efficiency is the same as rationality or accuracy. The many market periods of either irrational exuberance (bull markets) or irrational dread and panic (bear markets) highlight a point about EMH. It might be true that markets are “informally efficient” in the sense that reaction to news is immediate. However, efficiency cannot be isolated to reaction time when, in fact, the level and scope of reaction is itself inefficient. A huge market rise or fall invariably exceeds any fundamental reasons underlying a price move in any form of trend, but especially in a primary trend. The largest bear trend in history, from 2007 to 2009 with its 53 percent drop in Dow index valuation is not supported by the fundamentals of the thirty stocks in that average. Neither is the bounce from 2009 through 2012 supported in any specific fundamental improvements among the thirty Dow stocks. Implications of calling the markets “efficient” include the assumption that reaction to news also leads to efficient and rational price movement. History has shown repeatedly that markets overreact to both good and bad news, to true and false news, and to events and news that have nothing whatsoever to do with fundamental value. If the market is informally efficient, it does not reflect good judgment among investors in the ways they respond to information. In the short term, markets are chaotic and inefficient, and even EMH proponents concede this point. However, the more disturbing reality is that longer-term trends also are inefficient in the way changes in price levels occur, both for index tracking and for individual stocks. At least for individual stocks an intermediate self-correcting effect grows from supply and demand. When stocks are overpriced, selling dominates and when they are underpriced, buyers take over. This has the effect of maintaining an economic balance within individual stock prices, a form of true efficiency based on supply and demand and not on information.

Other Price Theories: RWH 

 17

Key Point: A consistent “cause and effect” in price reaction and overreaction is characteristic of the immediate character of supply and demand in any market.

What is the confidence level that a stock’s current price is the “right” price? That is what matters. Cybercurrency is an interesting example. Is the current price representative of a poor risk, or is it priced at bargain levels? For any issue—whether cybercurrency or listed stock—supply and demand does cause price movement, but the right price is all in the eye of the beholder. Adding to the long-term inefficiency of “the market” as measured by the DJIA, is the fact that the Dow Jones Company replaces components periodically. What is the rationale for this? Some companies become obsolete and should be replaced, and that makes sense. However, in some cases the reasons for removing some companies and placing others in the list of thirty is not as clear. Since its inception in 1884, the Average has been changed fifty-four times. For example, in 2013, four new companies were added to the DJIA: J.P. Morgan, Nike, United Technologies, and Visa. Dropped were Alcoa, Bank of America, Hewlett-Packard, and Merck. In March 2015, Apple (AAPL) was added, replacing AT&T (T). In 2018, one of the original Dow components, General Electric (GE), was replaced by Walgreen Boots (WBA). Without doubt, the periodic replacement of stocks on the DJIA influences its climb in index level.12

Other Price Theories: RWH Closely associated with EMH is the random walk hypothesis (RWH). In this concept of the market, all changes in stock prices are entirely random and cannot be forecast with any reliability. If the EMH rationale is accepted, current prices reflect all known information. Thus, any further movement in price is subject to evolving information, but the direction of movement is entirely random. However, if the market is truly random, no trends could possibly develop. Prices would tend to move in a completely 50/50 manner, moving upward half of the time and downward the other half. The examination of any stock chart over time reveals that this does not occur. Trends for indexes as well as for individual stocks develop, move, and continue moving until reversal signals appear. At this point, the price might level out for a period of consolidation and indecision and then either reverse or continue in the previously established direction. A truly random outcome, such as the outcome of the spin of a roulette wheel, would be black nearly half of the time and red nearly half of the time. Zero and double zero move the odds slightly in favor of the house so that red or black occurs in 47.37 percent of spins. With a total of thirty-eight possible numbers included one through thirty-six plus zero and double zero, the random odds are: 18 ÷ 38 = 47.37%

18 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

The RWH premise was analyzed by professors of finance at the MIT Sloan School of Management and the University of Pennsylvania. Their conclusion was that RWH is wrong and that trends do exist, making the markets predictable, at least to some degree.13 Key Point: If markets were truly random, no form of analysis would have value. The theory of a random market has been questioned many times and the conclusion is that markets are by no means random.

Supporters of RWH point to the equilibrium of supply and demand as explanation for this random assumption about stock prices. However, this would require that buyers and sellers come to the table at the same time and that no news affecting price occurs at that moment. RWH always requires efficiency in the price as well as an equal number of buyers and sellers who agree about the fairness of the current stock price. Neither of these are likely to occur consistently enough to support RWH as a reasonable theory about markets. The fact that buyers and sellers are rarely available in equal numbers is one of the factors creating trends, even ignoring fundamental realities of the company. The vacuum assumed by RWH is that markets work with extreme efficiency and balance, but this ignores the reality in another very important manner. The fundamentals of companies reveal that over time, some companies grow in terms of net profits and market share; they increase dividends they pay; they acquire or merge with competitors; and they invent new products and processes. Other companies lose market share and profits as their products become obsolete and as competitors outperform them. Some companies mismanage their costs, such as General Motors, whose debt/equity ratio rose above 200 percent before bankruptcy was inevitable. This meant that debt accounted for more than the total valuation of the company and that equity was nonexistent. Since GM has reformed and continues to take part in the market, the underlying problems were fundamental and far from random. The success or failure of a company (and as a result, the rise or fall of its stock price) is inevitably traced to tangible and precise underlying fundamentals and not to random luck. Companies like General Motors, Eastman Kodak, and others failed because of fundamental causes such as obsolescence, failure to compete, lack of control over costs, and other problems; and successes like Amazon, Walmart, Microsoft, and McDonald’s also are not random but the result of keen competition, product exceptionalism, and smart management. None of these are random influences on the fundamentals, and they also explain why the stocks of successful companies experience long-term bullish trends. Key Point: Stock prices of well-managed companies tend to move in a bullish trend over time.

The equilibrium of supply and demand based on the assumption of an equal number of agreeable buyers and sellers is unrealistic. RWH relies on this assumption, but the truth is that supply and demand is rarely in equilibrium. It changes based on competitive pricing and quality. There is nothing random about strong competition,

Trend Analysis as a Risk Management Process 

 19

excellent management, and quality of products or services. Within a single day or week, a stock’s price moves in a chaotic and possibly random manner and a reason to study trends. The momentary struggle between buyers and sellers reflects ever-changing adjustments to supply and demand, but the larger picture and the longer-term trend clarify what really causes prices to move upward or downward over time. The numerous short-term effects on stock prices (profit-taking, bargain hunting, earnings surprises, rumors, or merger talks, to name a few) create a random effect on stock prices, but these reflect the short-term, or swing trends only and not the secondary or primary trends that define a stock’s price over months or even years. Those longer-term trends grow from the tangible cause and effect (supply and demand) based on fundamental analysis. In this respect, the fundamentals (competition, profit and loss, cash flow) directly affect the long-term technical aspects (price and movement of price trends). None of this is random. The nature of price trends is best described as the technical reaction to the underlying fundamentals of the company. Stock prices are unpredictable in the short term, primarily because next year’s fundamentals are not yet known. It is unrealistic for stock prices to move randomly without any cause because trends are easily observed in prices. RWH claims that it is impossible to consistently beat the market averages; but with sound stock selection based on the fundamental record, the long-term technical side consistently yields results. One aspect of RWH is a belief that technicians, who rely on analysis of price charts, respond to market and investor behavior. Under this belief fundamentals do not matter because investors set the market mood by buying or selling, resulting in bullish or bearish sentiment. This ignores the glaring differences between well-managed and poorly-managed companies in the same sector and the resulting changes in stock prices over the long term. Investors are far from arbitrary in how they develop sentiment. As a group, investors favor profitable companies and do not favor those companies losing market share and reporting net losses.

Trend Analysis as a Risk Management Process The explanation of price movement as either efficient or random ignores the most important attribute of the trend: its role as a means of risk management. By tracking stock trends and defining the differences between swing, secondary, and primary trends, investors develop methods for managing risk. This is accomplished through carefully timed trades based on trend behavior. Even conservative buy-and-hold traders whose portfolio is treated as permanent, can utilize trends to time defensive measures to avoid losses. These include closing long equity positions in anticipation of bearish turns in current trends; the purchase of put options to insure paper profits; variations of dollar cost averaging to exploit price movements

20 

 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

interpreted as secondary trends or retracements; and trades undertaken following exaggerated reactions to events like earnings surprises. Key Point: In a very real sense, trend analysis is a method for risk management. By recognizing trends as they evolve, investors and portfolio managers can better time entry and exit decisions.

By taking steps such as these, all investors provide risk management attributes to trend following. Understanding how trends work and recognizing or forecasting upcoming reversals is interesting by itself but becomes meaningful when the knowledge is applied to reduce and eliminate risk. Among the risk-reducing methods investors employ is articulation of risk itself through formulations like risk-adjusted value. The expected cash flow from an investment (whether dividend yield, option premium, or capital gains) expresses expectations of net return from an investment. The probabilities assigned to expected cash flow define how this calculation ends up. For example, an investor purchases shares of stock based on several fundamental attributes, including an attractive dividend yield. What is the probability of the dividend continuing to be paid and what payout ratio will apply each year? A set of assumptions like this identifies risk once future cash flow is discounted and based on a range of probabilities. When calculations such as risk-adjusted value are examined considering historical price trends and forecast into the future, risk itself can be defined within a range of possible outcomes. This relies on the continuation or end of a known trend. If this calculation is performed based on past trends, the variables of outcome can be assigned varying levels of confidence based on the strength and consistency of fundamentals. For those relying solely on technical indicators, risk depends on recognition of reversal signals. This means not only identifying the likely reversal of price toward the end of a trend, but also accounting for the unexpected reaction of the trendline to surprises in news yet to be announced. A vulnerable set of technical assumptions may lead to a greater than expected price adjustment, for example. This observation emphasizes why the combination of fundamental and technical analysis improves the understanding of price trends. The technical side does not occur in isolation; it is a mistake for chartists to ignore fundamental analysis in the belief that the fundamentals have no direct or immediate effect on the movement of price. The proponents of EMH and RWH base part of their theories on the belief that technicians rely, often too heavily, on past price performance and ignore fundamentals in the absolute trust of price patterns and reversal signals. For investors and traders intent on using technical analysis wisely, the fundamentals should not be ignored, but used together with technical indicators. It makes sense to first select companies as investment candidates based on the strength of historical financial results and to then analyze trends over both short-term and long-term timeframes. This addresses

Trend Analysis as a Risk Management Process 

 21

the criticism offered by proponents of EMH and RWH that technical traders fit only one mode of behavior. Trends further help investors to manage risk through avoidance or transfer. Risk avoidance is the initial result of thorough fundamental analysis. Investing only in high-quality, well-managed, strongly-capitalized corporations with strong competitive position avoids much of the risk (both fundamental and technical) associated with weaker, poorly capitalized corporations that also tend to exhibit greater price volatility. Key Point: Risk transfer combines analysis in both fundamental and technical trends. This aids in identifying companies with strong fundamental attributes and price potential.

Risk transfer (also known as risk hedging) is a method of reducing risk through the purchase of insurance (long puts to insure equity profits, for example) or application of more advanced options strategies designed to cap losses often in exchange for also placing a ceiling on potential profits. Diversification is another method of risk transfer in which a range of dissimilar risks are retained in the belief that through diversification or asset allocation the exposure to market risk is minimized. When these steps are organized within a program of price trend analysis, the effectiveness of risk transfer is heightened and the retained risks are lowered, even with a spreading of risks through a program of diversification or asset allocation. The trend is the monitoring tool that alerts a portfolio manager or investor when positions are moving toward overbought or oversold conditions. If portfolio management is aimed at quantifying profits through trend analysis (which includes anticipation, recognition, and avoidance of risk), it also becomes necessary to understand the potential for portfolio losses. Within the science of trend analysis, the most basic concept for this involves recognition of how trends evolve and change over time. Is the pattern volatile or predictable? Is the trend changing quickly or slowly, flattening out, or retracing frequently? Are specific reversal signals beginning to appear in the form of momentum or volume indicators? All these changes identify the potential for losses to occur if no action is taken. The potential action may involve closing of portfolio holdings, buying insurance or hedge derivatives, or retaining the risk with an awareness of how the risk might be evolving along with the evolution of the trend. To identify potential risk of loss in a portfolio, trends are tracked and analyzed and confidence levels are assigned. If your confidence level is high that the portfolio is safe in its status from market risk and other forms of risk, then the trend is a source for that high confidence. If confidence declines due to changes in long-term indicators accompanying the price movement, then it makes sense to adopt a policy for action when confidence declines to a predetermined level. One method for assigning a confidence level to portfolio risk exposure is Value at Risk (VaR). Based on a series of assumptions concerning likelihood of loss, time, and confidence interval, VaR may be identified and tracked as a form of trend. However,

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 Chapter 1: The Theory of Trends: Dow, EMH, and RMH in Context

rather than resulting from the movement of price and other factors, VaR is an articulation of risk based on assumptions. Key Point: VaR is one of several risk analysis tools. It is the study of risk levels based on a set of reasonable assumptions.

This process may be applied to a portfolio in general, or to a security within the portfolio. It is a means for assigning probability of loss as a percentage. For example, if confidence is at 90 percent then the potential for loss is at 10 percent. That loss will be defined in terms of dollar value and period. With these assumed variables in place VaR can be tracked over time, and as status changes the holder of that portfolio or stock may decide when or if to act to protect against loss. The most reliable means for changing these assumptions are: in the tracking of intermediate and long-term trends; in recognition of changes in breadth of trading or volatility; recognizing the frequency and severity of retracement; and spotting movements breaking out above resistance or below support. These analytical tools are part of trend analysis, and by quantifying risk with the addition of VaR the decision to act defensively may also be expressed in tangible terms. A portfolio manager may devise VaR based on several methods. The historical method includes observation of past trends such as duration, speed, and degree of reversal when those trends ended, with one of two approaches: The parametric approach tracks volatility of a portfolio against an imposed set of assumptions about net returns. The nonparametric approach is based on historical trend movement without imposing assumptions. Besides historical methods for developing VaR, the analysis may be performed solely based on historical volatility or, for derivatives, implied volatility analysis. For stock trends, this should include analysis of the breadth of trading and especially changes in that breadth, attempts at breakouts above resistance or below support, or changes in volatility within the established trading range. All forms of trend analysis may include studies of statistical moves and probabilities to quantify risk. Or they may be limited to a combination of technical observations based on initial fundamental criteria. For example, a first step in constructing a portfolio and making changes to it may be based on identifying a set of fundamental attributes and trends over time (ten years of revenue and net profit growth, for example). In fundamental analysis, the trend is strictly financial and adds great value to the identification of strong portfolio candidates. The next step is to track the intermediate and long-term trends of a stock, with special attention paid to visual and mathematical trend monitoring methods. The visual methods include trendline and channel line tracking, which while limited in value provide clear views of how trends behave. This is true in terms of duration and breadth of the trend as well as clear identification of changes. Mathematical trend monitoring includes volume and moving

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 23

average and momentum tests that are calculated and then expressed in terms of index values (most notably, flagging areas when a security is overbought or oversold). Key Point: Trend analysis combines visual observation of price patterns with calculated momentum, volume, and price movement over time. Combining sources strengthens the overall process of trend analysis.

For most investors, the combined fundamental and technical approach makes the most sense. Both forms of analysis are based on trends, one involving financial results and the other limited to price and volume. Fundamental trends identify the strength or weakness of the financial results as well as levels of fundamental volatility. Technical trends identify price behavior over both short-term and long-term spans and aid in anticipating even subtle changes in the future, such as a slowing down in the rate of a trend. Several statistical tendencies of trends help to further understand how trends behave and how to recognize changes in their behavior. This is the topic for the next chapter.

Endnotes

1 Lakonishok, Josef, Andrei Shleifer, and Robert Vishny. “Contrarian Investment, Extrapolation, and Risk.” Journal of Finance 49 (1994): 1541–78. 2 Dow Jones & Company. September 12, 2019, at http://indexarb.com/indexComponentWtsDJ.html 3 Aristophanes. The Clouds, 423 B.C. The reference is to the perfect city erected in the clouds and named Cloud Cuckoo Land, the ideal and perfect city devised by characters Mr. Trusting and Mr. Hopeful. 4 United Nations, Industrial Development Organization. World Manufacturing Production, 2nd quarter 2018. https://www.unido.org/sites/default/files/files/2018-09/World_manufacturing_ production_2018_q2.pdf 5 Planes, Alex. “Why the Dow Hit Rock Bottom 4 Years Ago.” The Motley Fool at www.fool.com (March 8, 2013). 6 Fama, Eugene. “Efficient Capital Markets: A Review of Theory and Empirical Work.” Journal of Finance 25 (1970): 383–417. 7 Fama, Eugene. “Random Walks in Stock Market Prices.” Financial Analysts Journal, January–February (1995): 75–80. 8 Caginalp, G., and D. Balenovich. “A Theoretical Foundation for Technical Analysis.” Journal of Technical Analysis 59, no. 5–22, Winter-Spring (2003), http://papers.ssrn.com/sol3/papers. cfm?abstract_id=658165. 9 Muth, John F. “Rational Expectations and the Theory of Price Movements.” Econometrica 29, no. 3 (1961): 315–35. 10 Greenspan, Alan. “The Challenge of Central Banking in a Democratic Society” (speech presented on December 5, 1996 at the Annual Dinner and Francis Boyer Lecture of The American Enterprise Institute for Public Policy Research, Washington, D.C.). 11 Nocera, Joe. “Poking Holes in a Theory of Markets,” New York Times, June 5, 2009. 12 Indexology, at https://us.spindices.com/indexology/djia-and-sp-500/the-changing-djia 13 Lo, Andrew W., and Archie C. Mackinlay. A Non-Random Walk Down Wall Street, Fifth Edition. Princeton, NJ: Princeton University Press, 2002.

Chapter 2 Statistically Speaking: Trends by the Numbers Trend analysis is based on technical attributes of price movement but it can be much more, adding to the value of signals and price attributes. This chapter examines and explains the attributes of trend analysis based on probabilities and statistics. Some primary points in this analysis are: 1. Statistically, no trend continues forever, but some technical traders forget to look for signs of plateau or slowdown in the trend. 2. While a price moves higher, traders need to also track other indicators to determine when stocks are getting too expensive based on price earnings ratio (P/E) among other signals. In this regard, the trend works as an aspect of valuation, which is easily overlooked if a trader’s focus is only on the price of stock. 3. While a price lowers, there is a finite level to the trend; informed investors recognize the point where a stock becomes a bargain and will move in to buy. At this point, the less aware investor is still trend-following and is not looking for the level where the trend is becoming excessive. 4. The trend operates in one of two ways: either it resides within the trading range and may be expected to “bounce” off resistance and support, recognized by strong reversal and confirmation signals or it breaks out and sets up a new higher or lower trading range, meaning the trend moves beyond the previously established range. Key Point: Every trend shares specific attributes relating to duration, over- and underpricing of shares, and action of price relative to resistance and support.

Some traders, even those highly skilled at technical analysis, may easily overlook the attributes of a trend relative to underlying statistical tendencies, valuation, and price movement.  The shortcomings of trend-following lead to risk that might be invisible, especially if the trader is overly focused on the technical price movement alone without understanding the trend itself. Trends operate within the valuation of a stock, and focusing on pattern recognition without understanding how trends are evolving is an error. This ability to understand the relationship between price behavior and the trend has a profound implication: price movement is not the same as trend movement. A price moves without specific patterns of reversal, continuation, retracement, and sideways uncertainty. This all may occur within a larger primary trend for the stock. Although these shorter-term price patterns are referred to by chartists as “trends,” they generally are swing trends but rarely secondary or primary trends. This is profound because managing the risks of the swing trend is a short-term process. Many DOI 10.1515/9781547401086-002

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 Chapter 2: Statistically Speaking: Trends by the Numbers

of the well-known reversal and continuation signals used by swing traders are applicable to longer-term trends as well, but a technical reaction to these signals may not look as significant as it is not a small trading window.

Fat Tails and Trends Statisticians take comfort in a normal distribution, the well-known bell curve that illustrates how outcomes are likely to fall (see Figure 2.1). As the curve moves upward, a greater number of occurrences are found; as the curve moves to the extremes, the number of occurrences decline.

68% fall within one standard deviation 95% fall within two standard deviations Source: Prepared by the author Figure 2.1: Normal distribution on the bell curve

However, the ideal statistical outcome is a model only. Stock trends are not normally distributed and, in fact, may appear random at first glance. There is order and predictability to the trend, but the trend itself can not be measured in the same way as other things, such as mortality, physical characteristics, or auto accidents. In all of these events, a known and likely range of possibilities exists. These are known as discrete random variables because they contain a finite number of possible results. In stock trends, uncertainty about the range itself means that no plotting of standard deviation is possible. Outcomes may appear at many points in the bell curve and not in the

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 27

classic clustering nearer to the top of that curve. Stock trends are examples of continuous random variables in which an unknown range of possible outcomes are in play. Key Point: Stock trends are not normally distributed because the variables are changing constantly. Every change in price creates a new, continuous random variable.

Statisticians identify a given range of possible outcomes, recognizing that a continuous random variable (like the closing price of stock in any one session) must fall within that range. For a stock price, the range is anywhere between zero and an unknown high, which in theory is infinity. However, on a practical level, it is reasonable to set an estimate of a likely high end to the range. Thus, a $20 stock might be assumed to experience an upward move to $200 per share, but the same assumption might reject the possibility of price exceeding $200. Of course, the price could move in the same direction indefinitely, in theory at least; but as a method for making risk management as realistic as possible, this limitation makes sense. It ignores the theory of potential infinite movement and attempts to add a finite property to the likely range of movement. It makes no sense to try and estimate the likely exact value at any given date, but it is possible to estimate a range of possible outcomes. In trend analysis, for example, you may estimate that the current trend and breadth of trading has some assumed value of (a) continuing to move in the same direction and (b) maintain the same breadth as it exhibits currently. This is where the use of specific statistical calculations aid in articulating levels of risk. Statistical calculation works to define not only the orderly progress of a trend but also to identify when it is beginning to change its characteristics. The probability density functions, or finite possible outcomes given a set of reasonable assumptions, limit the estimated range of outcomes. This means that from a statistical point of view, estimating the direction, duration, and slope of a trend can be reduced to a reasonable and likely range of outcomes. Even so, the range will remain broad even when expressed within a series of continuous random variables. It is far more instructive in trend analysis to develop methods to track price and trend development with a system allowing you to spot potential changes to the trend. You can limit the “universe” of likely outcomes without being able to identify a finite range. For example, a stock trading currently at $80 per share might range in the following year between $40 and $160. Moving outside of that range is less likely, and the farther out, the less likely it becomes. This is where another statistical tool, standard deviation, enters the science of trend analysis. Key Point: The possible outcomes of a trend can be limited to a likely range even with continuous random variables. This range changes, though, with every new price change.

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 Chapter 2: Statistically Speaking: Trends by the Numbers

Calculating a likely outcome based on standard deviation produces a model that also serves as a starting point for tracking stock prices. To bring order to the tracking of trends, the application of standard deviation reveals that trends tend to display fat tails. Rather than a large number of outcomes (such as a day’s ending price) falling within a standard deviation of the mean, a high number of a trend’s outcome fall outside of normal distribution. Some are higher than the expected normal distribution and others are lower. Although fat tails “should” be statistically rare, they have been observed to occur frequently in the market: Even ignoring Black Monday, if returns were “normal,” statisticians would expect the S&P 500 to move up or down by 3.5% or more only once every 10,000 years. . . . In contrast, we’ve experienced 118 such occurrences since 1950—nearly half of them in the past two years. Over the past two years, the average daily move up or down has been 1.3%. With that as a baseline, a normal distribution would see a fat-tailed move of 6.4% once every 100 years. In fact, it has already happened 11 times in the past two years.1

A purist who relies on statistical discipline might argue that this proves the randomness of a stock trend. However, that is not the case. It only points to the need for development of statistical tools to track trends that prove continuation or point to reversal (or retracement). Using standard deviation helps to set a standard for trend analysis over the long term. However, even statistical certainties may not apply to trend analysis in an absolute sense. To calculate standard deviation, the following steps are required:2 1. Calculate a moving average for a set period of time (twenty days, for example, the period normally used to map Bollinger Bands, which are based on standard deviation). 2. Find the deviation for each session in the period analyzed. This is the difference between each session’s closing price and the average price for the entire period. 3. Square each session’s deviation, the sum of the values calculated in step 2, or X2. 4. Add together the squared values for all the periods. 5. Divide the sum of the squared valued by the number of periods in the analysis. For example, if twenty sessions are studied, divide by 20. 6. Calculate the square root of the result, which is the standard deviation. Analysts relying on free charting services (in this book, StockCharts.com is used) can calculate specific indicators based on the use of standard deviation. So, this set of calculations does not have to be performed repeatedly. However, it is instructive to understand how those indicators are developed. Many indicators rely on manipulation of moving averages to estimate changes in volume or momentum, and these

Bollinger Bands 

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are examined in later chapters. Bollinger Bands are one example of an indicator that overcomes the lack of standard deviation in trends. Key Point: Standard deviation sets up likely ranges of outcomes in the current trend. This adds a form of reliability to how reversals can be spotted and forecast before they occur.

Bollinger Bands Named for their developer John Bollinger, Bollinger Bands are a statistically-based system for tracking trends. Specifically, they track moving averages and the degree to which price deviates from those averages.3 Bollinger Bands have three moving averages. The middle band is a simple moving average of price. The upper band is two standard deviations higher than the price average and the lower band is two standard deviations below the price average. All three bands are calculated on the same period, usually twenty days. Since the popular bell curve is applicable for normal distributions, the use of standard deviation in a series of bands is applicable for stock prices, which do not exhibit a normal distribution but contain variables and fat tails that can not be calculated using the pure statistical methods based on finite outcomes. (How many registered voters will vote? What distribution of weight ranges applies to fifteen-year-old boys or girls? Which products do consumers prefer out of three possible purchases?) Bollinger Bands are popularly used by chartists as one of dozens of price indicators. For short-term application, these traders look for changes in the bands themselves to generate trades or to find confirmation of a likely reversal and then enter a trade. This short-term application is effective assuming that confirmation is also found. However, this may be viewed as an indicator-specific identification of changing price patterns. Bollinger Bands can also be applied to secondary and primary trends as a means for setting up possible changes, including reversal or continuation. Much of this relies on confirmation in the form of other indicators as well as analysis of Bollinger Bands behavior if and when the upper band moves price through resistance or when the lower band moves price through support. For analysis of the long-term trend, the reliability and strength of Bollinger Bands provides an excellent analytical tool of breadth of trading, resistance or support strength or weakness, and continuing strength or gradually evolving weakness in the trend’s slope and duration. Key Point: Bollinger Bands provide a visual summary of likely trend behavior. In this sense, the indicator is a form of “probability matrix” for a dynamic field of prices.

In the short term, Bollinger Bands measure and identify volatility or market risk associated with the specific stock. This is of great interest to swing traders, but for those focused on longer-term trend analysis, the short-term volatility of price is part of a

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price pattern expected to exist within the context of a longer-term primary trend or an offsetting secondary trend. For both utilizations of Bollinger Bands (swing trading based on price patterns or trend analysis based on behavior of primary and secondary trends, retracements, or exhaustion points seen in the trend), specific action points are identified in a number of ways. Remembering that the upper and lower bands are the product of standard deviation, their movement contains characteristics more meaningful than one-line moving averages or price pattern signals. A typical Bollinger Bands analysis added to a price chart is shown in Figure 2.2.

Source: Chart courtesy of StockCharts.com Figure 2.2: Bollinger Bands

As the chart for Caterpillar reveals, Bollinger Bands closely track the movement of price. For the purpose of identifying turning points in the trend, several predictive elements appeared during the sideways movement of 2013. The price approached and touched both upper and lower bands repeatedly between late April and December. In December, the price moved above the upper band during most of the month, an initial indication that bullish momentum was underway. This should be confirmed by additional signals, but based solely on what this revealed, the six-month bullish trend through June 2014 was not surprising. During that bullish move, the breadth of trading was above the middle band and close to the upper band for most of the period. This added to the strength of the bullish trend. In late July 2014, an initial indication of a bearish move—either retracement or secondary trend—appeared with two instances of downside gaps. This predicted a strong downside trend that did not materialize until September and October. At that point, the price was close to the lower band. The volatility during the final six months could have been difficult to interpret without the addition of Bollinger Bands.

Bollinger Bands 

 31

Key Point: Indicators like Bollinger Bands aid in interpreting price trends even when volatility levels are high.

Numerous signals can be taken from Bollinger Bands beyond just tracking a trend. Actual reversal is also signaled with a variation of well-known technical indicators similar to the well-known double tops or bottoms, gaps or head and shoulders patterns. A variation of this is seen in two Bollinger Bands formations called the W bottom and M top. On the lower side of a trading range a W bottom occurs when two reaction lows occur during a downtrend. This takes place in four steps. First, price declines to and touches the lower band. Second, price next moves up toward the middle band. Third, price once again moves down to a new low price while remaining above the lower band. Fourth, price responds to the exhibited weakness of the downtrend and moves strongly higher, potentially to a break above resistance and the upper band. The W bottom is a variety of the widely recognized double bottom, and is a bullish signal. For example, a typical W bottom is shown in Figure 2.3.

Source: Chart courtesy of StockCharts.com Figure 2.3: Bollinger Bands, the W bottom

On this chart, two distinct W bottoms appear. The first closely conforms to the requirements of the W bottom concerning price and the lower band. It comes close to actually touching it. And on the bounce, the price moves to the middle. However, the strongest element is found in the single upper shadow moving above the upper band at the beginning of November. The second W bottom follows the bullish rally from February through June 2014. As price begins falling, it actually moves below the lower band briefly but strongly. The middle bounce exaggerates the movement, going close to the upper band. The second decline (forming a double bottom) also moves below the lower band.

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 Chapter 2: Statistically Speaking: Trends by the Numbers

Both of these W bottom cases can also be analyzed in connection with support. If support was established in June 2013, at approximately $58.50 per share, the subsequent declines demonstrate how Bollinger Bands interact with other technical indicators. The period between August 2013 and February 2014 moved price several points below support, but the 2014 rally moved price back into range. The second attempt at a bearish move was more typical of a double bottom attempt, with price declining to the established support level twice before rebounding. So in this chart, Bollinger Bands and the W bottom also confirmed the strength of support. Key Point: The W bottom is a variation of the better known double bottom in technical analysis. The M top is a version of the double top.

On the higher side of a trading range, an M top occurs when two reaction highs occur during an uptrend. This takes place in four steps. First, price rises to and touches the upper band. Second, price moves down toward the middle band. Third, price once again moves up to a new high price while remaining below the upper band. Fourth, price responds to the exhibited weakness of the uptrend and moves strongly lower, potentially to a break below support and the lower band. The M top is a variety of the widely recognized double top pattern, and is a bearish reversal signal. For example, an M top pattern with Bollinger Bands is exhibited in Figure 2.4.

Source: Chart courtesy of StockCharts.com Figure 2.4: Bollinger Bands, the M top

The M top formation on this chart is volatile compared to the previous W bottom. However, it also confirms the activity expected with a double top. Following both occurrences of the M top, price levels declined. The chart has many examples of price moving outside of the upper and lower bands, exhibiting higher than average volatil-

Bollinger Bands 

 33

ity for the company. Any type of double top, whether the well-known signal by itself, or found within an M top, may be thought of as a lesson that after two tries at breaking higher, the likelihood is that price will next continue downward. This has importance in terms of how stable a trend is and what you might expect to occur next. The progress of a trend is likely to include numerous instances of price touching upper or lower bands, or both. These moments by themselves are not signals of changes in the trend. However, when a touch of price to bands forms up as part of larger signal, such as W or M patterns, it is more significant. Even greater in meaning is when movements of price are above the upper band or below the lower band. Price moving above the two standard deviations of the upper band, or below the two standard deviations of the lower band, will not remain there for long. The extreme move outside of two standard deviations invariably leads to price retracement within the bounds of the upper and lower bands. A reasonable expectation is that as trends progress, as much as 85 percent to 90 percent of all price movement should be contained within the range from upper to lower bands. If and when movements outside the band begin to occur, it signals increases in volatility and may forecast a reversal not only of a swing trade but also of a secondary or primary trend.4 Key Point: With the expectation that a high degree of price movement is going to remain within the range of Bollinger Bands, movements above or below are signals of a coming reversal.

Bollinger Bands present a visual summary of how price interacts with its well-developed moving average (expressed within two standard deviations). This is one indicator that allows you to manage what statisticians refer to as multiple random events. With stock prices, a number of these variables are at play with one another, including earnings reports, market perceptions of growth (and the resulting supply and demand for shares), and price patterns relative to the trading range itself. The fact that everyone dealing in stocks goes by these rules make it a self-fulfilling prophesy. Traders bail out or jump in when prices move outside of the bands’ zones, and this applies to all stocks. The use of these bands to track averages of price sets up a simplified but revealing probability matrix in which the likelihood of a change in the trend can be spotted. As the bands widen or narrow, the action of price in the middle range, notably as it approaches, touches, or moves through either the upper or lower band, may be found not only at times of high price volatility but at times when a reversal is likely. At times, however, price moves outside of the band zones, often because of rumors floating in the market or in anticipation of earnings surprises, but quickly return to lower volatility and trading closer to the middle band (the average). Such a reversal may be relevant only to the swing trend, either as a short-term reversal or shorter-term retracement. It may also be more than a reversal of these momentary prices as reflected in the changes to price patterns, meaning that a reversal

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 Chapter 2: Statistically Speaking: Trends by the Numbers

can signal the beginning of a new trend. To confirm this, additional signals should be found. Common among these are volume spikes, large price gaps, and strong candlestick signals. It will also be found as an initial or confirming signal when a primary or secondary trend is nearing a reversal point. So, when price moves through upper or lower bands, it sets up a form of conditional probability. An analyst following a trend may observe that this volatility implies that a reversal is coming; but confirmation is also required before assuming that a signal of reversal is valid. In price and moving averages analysis this probability is expressed as the “probability of trend reversal” versus the “probability of price reversal” given the observed violation of resistance or support, momentum oscillators confirm a likely reversal, and other forms of confirmation for both price patterns and the larger trend. The differences between price and trend reversals must be remembered. A momentum oscillator often will be used to observe price volatility, regardless of the strength or weakness of the trend. The oscillator measures the speed and strength of price movement, but does not test or quantify the direction of movement.

Statistical Tendencies The rationale for tracking price trends statistically through moving averages is to manage the volatility seen in short-term prices. For many, the price patterns and their highly chaotic and unpredictable nature explain why so many people subscribe to the random walk hypothesis (RWH). However, there are important differences. A truly random price pattern should consist of no discernible pattern at all or of a non-repetitive pattern developed coincidentally. This does not occur. Many patterns occur frequently and some do lead to reversal a majority of the time. Many of these like the W and M patterns observed in Bollinger Bands are highly predictive and work as a method for quantifying variables to a likely range. In this range, analysts can take the risk of assigning high confidence to the correlated pattern and its proximity to resistance or support. Key Point: Proximity of reversals to resistance and support are crucial. This is the point where reversal is most likely to occur.

When the same observed pattern recognition is applied to secondary and primary trends, the same rules can be applied. Just as short-term chaos is managed through price patterns and confirmation, long-term trends are just as likely to act predictably given a set of conditional probabilities that are realistic. For example, combining price trend analysis with other technical signals such as P/E, revenue and earnings trends, and other fundamentals change are then searched for in the price patterns with a trend. When you spot broadening or narrowing breadth of trading, violations

Trends and Averages 

 35

of resistance or support, and statistically calculated overbought or oversold conditions, it often points to the trend slowing down and reversing. The tendencies of price patterns apply equally to the tendencies of trends. No trend continues forever in the same direction, with the same slope and strength, or within the same breadth of trading. These tendencies are observed statistically through Bollinger Bands, momentum oscillators, and volume indicators and subject to confirmation, they are the tools for predicting and confirming the end of trends, just as they apply to predict the end of swing trends and the emergence of a new trend moving in the opposite direction.

Trends and Averages Stock trends can not be analyzed like most populations in statistical analysis. When analysis is applied to a well-known and finite population, sample data are then identified and isolated for analysis. In a properly selected set of data, the outcome is expected to reflect behavior of the larger population. What is the equivalent in stock price trends? Many would think that the overall market is the population and index-based averages are the sample data. This may be true for marketwide analysis, even with the imperfections of a weighted index. How is this applied to individual stocks? In the case of stock price trends, “population” means every possible price down to the penny above and below the current level of price. This is an infinite population. So to make the statistical process work, a sample is much smaller. It consists of likely price movement in a range of outcomes with further removal of each and every specific price and preference for a range. This sample is further reduced by removing unlikely outcomes. For example, if one stock has trended between $20 and $35 per share over ten years and currently is at $30 per share, what is a reasonable assumption about price levels? The range might be limited to between tangible book value per share on the low end and $50 per share on the high end to be analyzed over a one-year period. Based on the history of a 15-point range over ten years, this seems to be a reasonable range of sample data. The limits to assumptions narrowing down the sample are statistically referred to as a set of expectations. These exist within the defined finite variations of possible outcomes, and outcomes above or below that field are not considered. Expectations are developed with averages and, especially in stock trends where values are constantly evolving, the use of moving averages. The random assumption about the market states that there is a 50 percent chance of only one of two events, higher prices or lower prices. This ignores the more interesting question of how far price might move in one of those directions. Moving beyond the rather simple random assumption, trends are identified and used to create that finite data set that applies assumptions to possible movement between a “worst case” decline and “best case”

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appreciation of price, not infinitely but in a realistic and finite world of possibilities. This becomes the data set against which a trend can be tracked. Key Point: For investors interested in how trends move, the duration question often is far more interesting than price direction, which is going to move higher, lower, or sideways. Duration is much less tangible.

This data set is then exposed to a set of variables. These include a selected list of fundamental indicators as well as technical properties (including price, volume, and momentum) and then tracked within a trend over the following year. As long as the assumptions about the sample and the appropriate selection of variables are realistic, a starting point is inserted into the immediate analysis of the trend. The basic questions to keep in mind concerning this analysis should include: 1. How long will the trend continue? 2. How are changes to the trend recognized and confirmed? 3. Is a change in direction a swing trade, retracement, secondary trend, or a new primary trend? 4. What processes can be applied to make immediate distinctions between price patterns (in swing trends or retracements, for example) and new secondary or primary trends? The analysis of the trend is similar to the analysis of price patterns, with distinct differences as well.

Trends versus Price Price is a constantly shifting and moving reflection of supply and demand for shares of stock. The market reacts to a huge array of information, both true and false, concerning current and future earnings, competitive stance and changes in management, mergers and acquisitions (rumored and completed), regulatory problems, product recalls, and dozens of other factors. In comparison, a trend is a reflection of the collective factors influencing price. The very existence of trends—easily visible through a glance at long-term stock charts—demonstrates with profound clarity that there is nothing random about price movement. In fact, the easily observed reality of trends in many shapes and duration completely destroys the intangible theory stating that price movement is random. Key Point: Recognized trend attributes apply to all durations and can be observed and predicted with consistency. This demonstrates that price movement is far from random.

This reality points to the great advantage investors hold. You can predict the behavior of stock price in both short-term price patterns and also in longer-term trends.

Strength and Weakness of Trends 

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This has long been recognized by swing traders whose three- to five-day swings are based on overreaction to immediate news about a company. On a longer timeframe, the same observation applies equally well if not better. That longer timeframe builds in a recognizable shape to the trend providing a large view of where price levels have been and where they are moving. As long as focus is on the day-to-day movement of price, the longer-term trends are most difficult to recognize. In fact, swing traders have no interest in what a stock’s price is likely to be next year or next month. They only care about the timing of current entry and exit. This system works well for swing traders moving in and out of positions with high volume. However, for a permanent portfolio, defined for this purpose as equity positions held indefinitely, and as long as assumptions causing the position to be opened continue to apply, the issue is not timing of short-term entry and exit but identification of changing risks. If last year’s promising investment has declined in value when the same criteria are applied today, the portfolio manager will want to sell the position and replace it with a new equity investment that contains more acceptable risks and the potential for higher income (through capital gains and dividends). This requires focus on the primary and secondary trend. This does not mean swing trends should be ignored because they constitute part of changes to the longer-term trends. It does mean that in tracking the primary and secondary trends the underlying causes of short-term price patterns and price movement are not a point of interest. The portfolio manager is better served by continuously applying profit and risk criteria to ensure that the equity position remains viable. This is the primary difference between trend management and price pattern prediction.

Strength and Weakness of Trends As the recognition of a shape associated with the trend—breadth, slope, duration— is important to recognize, it is also important to recognize the weakness to any trend. A trend, when viewed as a risk model, offers correlation between outcomes that may cover a wide area of possibilities. This makes price trends more difficult than a fixed field of a sample population. Every time a price changes, the moving average has to be updated to reflect the change. So, unlike a product sample in which consumers are offered choices between fixed products and their differences, prices are by no means fixed. If the taste of a food product changed every time it was tasted, it would be impossible to apply the rules of fixed sampling to determine how consumers will or will not buy. Key Point: Breadth, slope, and duration are the attributes of trends. However, the great challenge is that the population (stock price levels) changes every day.

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In estimating the average of a fixed field, the challenge is not difficult. This is why the expectation of trend analysis has to be based on evolving and changing information because the trend is dynamic. It is convenient to blame the problem of prediction on randomness in price movement or even on efficiency of information discounting. Neither apply well enough to explain why observed long-term trends often have an orderly appearance. It consists of a very consistent trading range, slope of increase or decrease in breadth, and interruption of a trend only with the occasional (and equally predictable) retracements typical of the stock trend. Even though a long-term primary trend may appear consistent over time, there continues to be a serious weakness in trend analysis. You can not know how long it will last. The random school of thought points to this as proof of randomness, but actually there are methods for forecasting when trends will decelerate, stop, and reverse. No two trends last the same duration, and so this alone mandates that trends have to be tracked through a modified expectation model. It is based on moving averages because the sample data and population are not fixed but change constantly. The nature of stock prices makes trend analysis a form of nonparametric distribution. In parametric distribution, statisticians are able to apply a normal distribution to identify a finite set of likely outcomes, or “statistical hypotheses concerning the behavior of observable random variables.”5 This means that a sample studied under normal distribution is more or less fixed and is predictable. Stock prices are neither fixed nor predictable. They consist of continually evolving prices and a data set that will not be the same tomorrow as it is today. The random variables cannot be limited to a finite number. This weakness in trend analysis is manageable when the technical rules of price movement are applied over a period of time. If a fixed portfolio contains a number of equities that have been selected on the same criteria, they are also likely to contain the same set of random variables. Thus, you can expect two different equities to respond to evolving market information in similar ways. An earnings disappointment will have a negative effect on price in the short term, which is just as likely to correct within a few sessions. This means that a serious study of tendencies within primary and secondary trends will lead a portfolio manager into an advanced understanding not only of price behavior within the trend, but also for the nature of that consistent body of random variables applicable to all equities in the portfolio.

Pattern Cycles The predictability of a consistent set of random variables among holdings in an equity portfolio is going to be accurate under a set of further assumptions. These include: 1. The equities selected were all subjected to the same selection criteria. 2. These selection criteria affect all equity positions in a similar manner. 3. The initial criteria and effect have not changed since positions were acquired.

Pattern Cycles 

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These variables point out that even subtle differences between equities may lead to inaccuracies in interpreting factors that influence trends. The use of diversification and asset allocation build in normal differences among equities in initial selection criteria, their affect, and consistency over time. This variability of portfolio holdings also points to the problem of cyclical patterns affecting long-term portfolio value and response to market influences on price. For these reasons, a technical observation of trends relies on price patterns including double tops and bottoms, breakouts, large price gaps, and violations of resistance or support. In other words, portfolio managers have developed a series of signals they consider to be reliable in predicting how price is likely to reverse direction. This practice recognizes that the patterns popular with swing traders also apply to longer-term trends. Key Point: Patterns in price behavior are found in trends of all lengths. This makes trend analysis applicable equally for short-term traders as well as long-term buy-and-hold investors.

This is the basis for criticism of technical analysis among proponents of the efficient market hypothesis (EMH) and the random walk hypothesis (RWH). The criticism is put forth that technical analysis relies on the assumption that past price behavior will be repeated in future price behavior, that chartist techniques attempt to use knowledge of the past behavior of a price series to predict the probable future behavior of the series. A statistician would characterize such techniques as assuming that successive price changes in individual securities are dependent.6 However, this is not always what swing traders do, nor what trend analysts rely on for timing of subsequent trades. In practice, portfolio managers tracking primary and secondary trades attempt to pinpoint reversal based on the appearance of familiar reversal signals. The difference, though, is that unlike the assumed behavior based on past price movement, technicians and trend analysts are more likely to use known signals and confirmation to determine when a trend is about to turn or has already turned. Tracking specific signals that have historically led to reversal more often than not is an intelligent approach to the timing of trades in the short term and also to the timing of a likely trend reversal. It is not the expectation that past price behavior will be repeated but the acknowledgment of predictable signals marking weakened trends that is most useful. These include three concurrent observations: (1) price patterns, volume indicators, and momentum oscillators mark likely points when the trend is going to slow down, stop, or reverse; (2) confirmation with signals at least as strong as the initial signal; and (3) proximity to the price level of resistance or support, which are the most likely times for price patterns and for trends to actually go through reversal. Key Point: Every trend study relies on three key elements: recognizable patterns, confirmation, and proximity.

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 Chapter 2: Statistically Speaking: Trends by the Numbers

Market Sentiment Expressed in the Trend The current sentiment of the market (bullish or bearish) is evident in the characteristics of every trend. This applies to markets overall and movement of indexes; it also applies to individual stocks. When investors are confident and optimistic about a company, its stock trend is going to move upward. This is true even when price movement is not supported by the fundamentals. For this reason tracking of price-based range indicators is one form of trend analysis. Is the price justified by current and potential earnings? Tracking the P/E provides the answer. When the range is between 10 and 25, it is a reasonable mid-range level. If P/E moves above this level, the stock begins to become expensive; below the mid-range, there is little or no interest in the company. P/E is an odd but useful indicator. It is odd because it compares a technical value (price) to a fundamental value (earnings). As price is divided by earnings, the resulting multiplier represents the number of years of earnings in the current price (based on latest reporting earnings). However, whereas price is current, earnings are historical. So, the best way to use P/E is to study its year-to-year range from high to low over a long term, such as ten years and to then compare the trend reflected in this range to the current P/E. For example, a comparative summary for five years range in P/E for two companies is shown in Figure 2.5. Target (T) 36 P 32 E 28 24 r 20 a 16 t 12 i 8 o 4 0

Costco (COST) 36 P 32 E 28 24 r 20 a 16 t 12 8 i 4 o 0

2010 2011 2012 2013 2014

2010 2011 2012 2013 2014

Source: Prepared by author based on CFRA Stock Reports Figure 2.5: Annual P/E range

Target’s range remained narrow in the period selected, within 5 points for the four latest years. It also remained in the mid-range, which you would expect to see for P/E. However, the Costco range was much wider, as much as 8 points; and the last four years’ high were above the 25 level. So even though the Costco P/E was not extremely out of range in this period, the stock was more expensive based on P/E than Target was. This is a good example of how tracking fundamentals over time, especially on

Momentum Trading 

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a comparative basis, provides insight into the strength of a company. In this case, the fundamental (earnings) showed how the technical side (price) behaved, and the degree of change over time. Key Point: P/E ratio should be analyzed in two ways: the range from high to low and the trend of range over many years.

Another way that market sentiment is reflected in the trend is a change in volatility. As investors become fearful, a bullish trend is likely to slow down or reverse. However, uncertainty most often leads to a sideways movement, a pause in the trend. If the uncertainty dissipates, the trend is likely to return and if the uncertainty worsens, the bullish trend could reverse and be replaced by a bearish trend. Market sentiment is always present, even when investors are uncertain. This occurs during a bear trend as well, when the price decline pauses and begins moving sideways. This reflects a sentiment of uncertainty about the bearish trend and may be a precursor to bargain hunting and, eventually, to a new reversal and bull market in the individual stock.

Momentum Trading Short-term trading (swing trading) relies on both overreaction to surprises and to momentum within a short-term trend. Chapter 12 examines momentum in the context of longer-term trends. It is closely associated with short-term buy and sell activity, often involving only a two- to five-day turnaround. Momentum often is the impetus for closing trades even if the original intention was to keep the position open longer. Momentum is the strength and speed of any movement. In a football game, an interception gives the team in possession immediate momentum, and the other team loses momentum. In stock trading, a strong and swift price movement gains movement as long as that movement continues in the same direction. Eventually, momentum declines, seen in a leveling off of price and one of three following conditions: resumption of the movement in the same direction, reversal and movement in the opposite direction, or an indefinite sideways movement (called consolidation). Momentum is the measurement of strength and speed of price movement, but it is not concerned with the direction of price movement. Momentum is a popular method for determining whether to open a position and, once opened, when to close. It is a binary index, a statistical summary of a moving average equated to an artificial index. A specific index value marks overbought conditions and another marks oversold. In a majority of oscillators, these ranges create a condition in which an orderly trend will remain in the mid-index of the oscillator. As long as this remains true, the momentum-based rationale is that the trend is in effect and is not changing. However, if the oscillator’s index value moves into the over-

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bought or oversold range, momentum traders will close existing positions or exploit the condition by opening new ones. Key Point: Momentum is the analysis of the strength and speed in price movement, but not its direction. As momentum moves into the overbought or oversold range, it signals likely reversal.

For example, Figure 2.6 includes an example of how a momentum oscillator (Relative Strength Index or RSI) confirms a likely reversal occurring at resistance.

gap and breakout resistance

overbought

Source: Chart courtesy of StockCharts.com Figure 2.6: Relative Strength Index

On this chart, several examples of movement in the RSI into overbought and oversold territory appear. However, they are for the most part very brief, and the index quickly returns into mid-range. However, at the beginning of November, price gaps high and moves through resistance. The potential for a reversal is always great at such occurrences, but it is made even more likely by what RSI does. The index moved strongly into overbought range, not only above 70 but on two occasions exceeding the 80 index value. Most significant, RSI remained above the overbought line for six weeks. Looking at the previous charted period, it is clear that RSI rarely stays out of the mid-range for long. So this event, coupled with the gap and high move, indicates a very strong possibility of reversal. This was a good example of how momentum is used to confirm the likely reversal in a trend. That may be a new primary or secondary trend, a retracement, or a swing trade. Tracking RSI and other momentum oscillators helps to understand trend behav-

Statistical Measurements and Trend Behavior Distinguished 

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ior over many time periods. For example, the Visa chart revealed a six-month duration in which the stock was overbought. Even though momentum is relatively simple to follow and the “rules” are quite clear, it presents only one of many trend indicators. No decision should be made concerning the end of a trend without confirmation, and that takes many forms. The Dow theory version of confirmation is the same—reversal between two indexes. For individual stocks, confirmation will be found in momentum oscillators, volume indicators, and price pattern signals (both Western and Eastern, or candlestick-based).

Statistical Measurements and Trend Behavior Distinguished Traders generally understand that markets do not always behave as expected, even when strong indicators are tracked and monitored. Statistical measurements are attempts at bringing order and predictability to an otherwise chaotic world. This is accomplished through identification of likely outcomes or probabilities and applying statistical measurements to arrive at a conclusion. Key Point: Despite a desire to create predictable analysis through the use of indicators, the great variable remains unpredictable behavior among investors.

Trend behavior contains so many random variables that the statistical world is of only limited value. Many tools such as moving averages, especially those based on comparisons of ranges to price and standard deviation, are especially useful in trend analysis. However, with most statistical models, the effort is based on a study of sample data drawn from a fixed population. Stock prices and trends are dynamic and the population itself changes with every trade made in the overall market. With the complexity of the statistical challenge in trend analysis, the limitations to statistics have to be accepted. In fact, trend behavior, even with a strong data set and statistical analysis, is not going to behave in conformity with an assumed range of outcomes. The problems of a large number of variables make it impossible to accurately and reliably pinpoint the range of outcomes when it comes to stock trends. The most likely way to use statistical means for tracking of trends is with indicators like Bollinger Bands and its three data sets (average, upper bands, and lower bands). The application of two standard deviations from the middle band can not predict where the trend is heading, but it can reveal moments when the direction of the trend is in jeopardy and when a reversal has become more likely.

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Spikes and How to Manage Them One principle of statistics is that within a range of values, notably unusual instances should be removed. These spikes distort the average, whether simple or exponential. For example, in a series of stock ending prices within a trend, if the normal breadth of trading is between $25 and $30 per share, a one-time spike to $50 should not be considered typical. To consider something a spike, it should be unusual and it must not be repeated. It is an aberration in every sense and in order to maintain accuracy of a statistical analysis, it should not be included in an analysis of price behavior. However, a spike in a stock trend also presents potential problems that should not be ignored. For example, is the spike truly an aberration or does it forecast volatility in the near future not otherwise predicted in the breadth of trading in the current trend? An analysis of the trend has to allow for this possibility. So on the one hand, statistically a spike is removed to maintain the order of an otherwise “typical” range of outcomes. No special significance is assigned to the spike itself. However, looking at the issue from a different point of view, does the trend have a meaning outside of the statistical movement of the trend itself? Because the population of a range of stock prices is changing continuously, a spike could have meaning outside the trend, especially compared to a trend based on a fixed population with a fixed set of possible variables. Key Point: Volume spikes often accompany reversal, but in analysis of trends the spike itself has to be discounted when it distorts the more typical average.

For example, in tracking a multiyear trend in the P/E ratio, identifying the trend between high and low, the outcome tends to remain in a range of 6 to 8 points, between 20 and 26 or 28. In one year, the P/E spiked to 45 during a period of high volatility in the stock price. This has two distinct meanings. First, statistically speaking, the spike would be removed from the analysis because it was not typical. However, in the year in question, a rapidly moving price curve making the stock too expensive would tell an investor to expect a correction. If the price remained out of range of a reasonable P/E, then it would also remain overpriced and that is good information for anyone wishing to avoid the correction that must come eventually. So the second meaning of a spike is that, even beyond statistical treatment of non-recurring aberrations, the spike changes the valuation of the stock. As such, it may be a temporary problem that self-corrects. However, if it does not self-correct, a portfolio manager would have to consider taking profits and moving to the sidelines and wait to see how price acts in the future. Spikes occur often in volume and signal a likely reversal. So, if a trend experiences a spike in volume in an otherwise stable trend, it could be a “power spike,” reflecting the known relationship between price and volume. A volume power spike

Spikes and How to Manage Them 

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should not be ignored in the context of trend behavior, but it might be necessary to overlook the statistical implications, remembering that the price population is not a typical one for statistical analysis. The power spike could have great significance and even signal that the trend is about to reverse. For example, the one-year chart for Amazon.com marked four distinct volume spikes, each accompanied by clear reversal signals. This is shown in Figure 2.7.

gap gap

double bottom

inverse head and shoulders support

Source: Chart courtesy of StockCharts.com Figure 2.7: Volume spikes

The first of four spikes occurred at the same time as a double bottom. The resulting reversal was short in duration and was followed by a six-week bearish move. This concluded with the second volume spike occurring in a two-day formation, which is unusual. This also marked the first of three segments in an inverse head and shoulders, a bullish indicator. This occurred as price trended below support, strongly hinting at a likely reversal, which occurred immediately. The third spike occurred as price peaked and then gapped lower by 40 points from the mid 360s down to the mid 320s. After this, price continued to decline until it met established support. The fourth volume spike occurred as price gapped below support once again. The combination of the gap, breakout, and volume spike were a convincing signal and confirmation. Amazon.com is a particularly volatile stock; and volatility also means uncertainty as the gyrations of the one-year chart exhibit. Investors do not like uncertainty in a permanent portfolio, and the spike represents uncertainty. For investors, uncertainty and risk are the same because both draw attention to concern about what happens

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next. So, a spike is an opportunity to manage the trend statistically, but it is also a signal that risks are greater as long as the volatility remains. Considering the dynamic nature of trends, the statistical approach is not as appropriate as a technical view that a spike could signal a coming change in the trend.

After the Spike: Breakouts and Reversals In attempting to manage a trend, changes and corrections should not be ignored. Even so, investors are constantly aware of retracements and of price behavior at or near resistance and support. When price moves through one of these, it tends to reverse and return into range. This reversal is also called a pullback. The potential for this to occur is the orderly assumption applied as long as the trend remains in effect. When a breakout succeeds, a new trading range is set. This could expand the trend into further territory with increased speed and for an extended period. The tendency in the market is to think of this in terms of bullish rallies; however, it also applies to bear markets on the downside. Key Point: Successful breakouts lead to bullish reversals when resistance is violated; the same rule applies to bear market breakouts below support.

Reversals, whether temporary or permanent, are most likely to occur close to the edges of the trading range. A breakout characterized by long days (long between open and close) and moving up toward resistance or moving down toward support increases the chances for reversal, especially when that long day is also a spike. Second, when the breakout is accompanied by a price gap between sessions, this also increases the likelihood of reversal. The larger the gap the greater the likelihood of reversal. While this observation about breakouts and reversals is clearly applied in swing trading, it also has application in longer-term trends. Trend analysis requires constant monitoring, so investors seek both reversal signals and confirmation that a trend is ending. Beyond price, volume indicators and momentum oscillators may be used as confirmation for the possibility of a trend coming to an end. However, numerous weaker signals will occur during the trend, with primary trends offset by secondary ones and secondary trends offset by swing trends. So the end of the single-stock trend (like the end of an index trend) is not clear-cut and demands analysis and study of related signals.

Statistical Analysis of Fundamentals Trend-following is almost always associated with technical analysis and, specifically, price patterns. It is used more as a timing device for swing trading than as a

Game Theory Applied to Trend Analysis 

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longer-term method for portfolio management. However, it applies to both varieties when focused on price. Beyond the technical trend, the fundamentals are also tracked over time. This makes sense when following any number of indicators, although a short list could be limited to only a few strong signals. Using a five- to ten-year trend ensures that a picture of fundamental strength or weakness will emerge. Among the signals that are most useful in fundamental trend analysis are revenue and earnings (not only the trend of each but the relationship between the two); dividend yield and payout ratio; P/E range over a period of time; and debt/equity ratio, representing the trend in increasing or decreasing long-term debt as a percentage of capitalization. Key Point: Most trend analysis is focused only on price and volume behavior. However, fundamental trends also affect price movement, although a time delay is also likely.

An example of a fundamental trend was previously shown in the comparison of P/E high and low ranges for two companies over five years. The trend is revealing but so is the comparison between two companies, especially if they are in the same sector. This type of fundamental trend analysis may serve as a decision point for a trade decision in the equity portfolio. Once positions are opened, continuing fundamental trend analysis reveals whether fundamental criteria are continuing to be met, or if not, when a particular position should be closed and replaced with a company with stronger fundamentals. Trend analysis and its many components are based on application of statistical principles even with its limitations. The statistical “rules” as applied to stationery populations bring order to the analysis of sample data. However, for a dynamic population such as stock prices within a trend, many of those statistical rules have to be mitigated through confirmation. This includes volume spikes confirmed by double bottoms or inverted head and shoulders, for example, or the application of W bottom and M top to identify the strength and continuation (or end) of a trend relative to Bollinger Bands patterns. Statistical principles are strong tools in trend analysis, but these become useful in context when viewed as part of a behavioral study. This is where game theory can help a portfolio manager to improve the understanding of how decisions are made.

Game Theory Applied to Trend Analysis An element of statistics is associated closely with game theory, a science involving the mathematical and statistical decision-making process. It is “the study of mathematical models of conflict and cooperation between intelligent rational decision-makers.”7 The underlying assumption of game theory is that decisions are made in an intelligent and rational manner. Part of the culture of the market

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is based on the often irrational behavior of market participants at large versus the minority of contrarian investors. Contrarians act as they do not just to go against the majority but based on analysis and rational conclusions versus the impulsive and emotional approach used (unconsciously for the most part) by a majority of traders and investors. The starting point in appreciating game theory is the zero-sum game. This is any situation in which the sum of gains on one side are equal to the sum of losses on the other. Many participants in the market assume that it is a zero-sum game, that an individual’s profits are gained at the expense of losses on the other side. However, this is not the case. Because growing companies increase their capital through profits, growing stock prices are generated and not taken from someone else. The market is not a zero-sum game; however, if it is treated as if it were, then the resulting decision process will be flawed. Key Point: Price movement is not a zero-sum game with set values exchanged between one group and another. The expansion of value resulting from profits is more complex.

Application in trend analysis of statistically model game theory concepts requires several elements. First, there must be players of the game (investors, who may win or lose). Second, at specific decision points there must be a payoff (profit or loss). Third, each player has access to the rules of the game (information, for example, about specific companies and their stocks) and fourth, actions have to be available (buy, sell, hold of specific stocks and selection of stocks based on the information set that is available). Some analysts of game theory use a decision tree, a set of binary actions that determine whether you win or lose. The decision tree simplifies the “game,” however, because it often is based on the assumption that players make decisions in precise steps, and one at a time. In investing, you face a potential range of decisions concurrently, and actual decisions might not be made in any particular order. (Buy and then sell is one idea, but so are incremental trading, short selling, and wait-and-see.) Game theory is worth studying because it demonstrates how the human mind approaches problems and arrives at decisions. By reducing this complexity to mathematical models, the process and outcomes are more easily understood. An analyst following a trend is not merely looking for a moment when the trend will reverse and set up a new trend in the opposite direction, although that is one result you expect to find in the trend, or more to the point, to anticipate through recognition of forecasting signals. When you are able to anticipate what is likely to occur beforehand, you gain an advantage in the timing game. Trend analysts, like players in many games, do not necessarily make decisions in a sequential manner such as those on a decision tree. The decision tree works for simple and binary forms of games like tic-tac-toe, in which a predictable set of outcomes is known in advance. A properly played game will always be a tie, meaning

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 49

that no player with equal knowledge can gain an advantage over an opponent. Investing is on the far end of the spectrum from the simplest form of game. Some games are instructive in demonstrating how difficult it is to make decisions without full access to all information, including the thinking process of other players. This is illustrated in the prisoner’s dilemma. In this game, two prisoners are captured and are being interviewed by the police. There is not enough clear evidence to get a conviction without a confession. So an offer is made to each: betray the other by testifying against him for a reduced sentence. The possible outcomes: If both take the deal, each gets a reduced sentence. If one agrees but the other does not, the latter gets a longer prison sentence. If both remain silent, they are likely to both go free or serve a lower sentence on a reduced charge.8 The dilemma for each is lack of knowledge. Is the other one cooperating? If so, then the smart move is to also cooperate. Is the other remaining silent? If so, also remaining silent makes more sense. Applied to trend analysis, you can not possibly know what other investors are deciding about a company and its stock, and you also can not know how the stock price will react to the collective knowledge. You are left with a similar dilemma. If everyone is going to turn bearish, you should sell now. But if everyone remains bullish, you should hold or even buy more shares. The prisoner’s dilemma demonstrates why “the crowd” of the market tends to trade based on irrational rather than on rational motives. Investors are constantly trying to anticipate the mood of the market and, as a result, investing poorly and with bad timing. This is why contrarian investing is rational. Contrarians do not play the prisoner’s dilemma but time their trades based on observed trend behavior. In other words, contrarians take a third choice beyond those offered to the two prisoners. They act independently and refuse to rely on the rest of the market. Knowing the market is compulsive and irrational, the contrarian does not fall into the prisoner’s dilemma because it is not a game that can be won consistently. Key Point: The prisoner’s dilemma is instructive for stock market investors. Contrarians are in the minority because they do not accept the two choices offered to prisoners. Contrarians take a third choice based on analysis and logic.

Game theory can not provide a guiding force in trend analysis, but it can help to explain behavior among investors. This is useful when reduced to statistical and mathematical modeling, without which trends can not be understood very well. So, game theory expands the statistical appreciation of the game itself, without taking over from practical application of statistics or common sense about the nature of risk. The trend reflects broad-based attitudes and beliefs, and a contrarian studying a trend may be likely to spot changes as they begin to occur and before a trend actually ends and starts moving in the opposite direction.

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 Chapter 2: Statistically Speaking: Trends by the Numbers

Magical Thinking and Trends The opposite of scientific thought (game theory as one aspect of statistics) is a far less logical range of ideas collectively referred to as magical thinking. This describes casual relationships between events and subsequent responses or actions, which are not justified in a rational manner. Success due to good luck tokens, repetitive actions, and compulsive assumptions is widely believed and practiced, but it is not scientific. Assumed correlations between ritual and result defy statistical observation, the application of the scientific knowledge, inquiry, and objective analysis. Even so, the market culture is characterized by frequent examples of magical thinking or, as it is often called, wishful thinking. To many, this has religious overtones. A worthy person will be rewarded by profits, whereas an unworthy person (one who sins, is selfish, or unkind) will have bad outcomes in the market. Even though magical thinking is irrational, it is often unconscious. Investors may act on the basis of magical thinking without being aware that they are doing so. The ultimate in magical thinking is found in a belief that specific thoughts can and do bring about actual results: “Thinking that one’s thoughts on their own can bring about effects in the world or that thinking something amounts to doing it.”9 So under the doctrine of magical thinking, an individual can cause a trend to continue or reverse due to their actions, rituals, or even thoughts. This “associative thinking” confuses an ideal connection with a real connection. So magical thinking takes on greater power than analysis and observation, and outcomes are controllable beyond the hard work of analysis and tracking.10 Magical thinking often occurs when “mental activity is too little differentiated for it to be possible to consider ideas or images of objects by themselves apart from the emotions and passions which evoke those ideas or are evoked by them.”11 Key Point: Magical thinking is a destructive force in trend analysis. The assumptions of magical thinking are irrational but are widely accepted in market culture.

Even though this is clearly irrational and clinically associated with primitive thought, this type of thinking does exist in the market culture. It distorts a perception of decision-making and risk. Many investors, both individual and institutional, operate on the belief that a loss should be followed by a greater risk in order to achieve some form of justice. The fact that even experienced investors might fall into this fallacy of thought is disturbing. A rational view of a loss is that it should be accepted and if any change to strategy is to be made it would be prudent to exercise greater caution to reduce the chances to recurrence. Another instructive aspect of loss is the lesson that cutting losses early rather than seeing them through makes more sense than magically thinking the outcome can be influenced apart from rational cause and effect. This fallacy also applies when investors tell themselves that losses occurred because they deserved to suffer or that losses are instructive on a moral or even reli-

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gious level. However, trend analysis is a scientific method for identifying changing attributes in trends, such as a weakening of the cure in a trend based on indicators and confirmation. Ignoring such signals does lead to missing a reversal as it occurs. There is nothing magical in this; trend analysis involves study and an understanding of both supply and demand and technical influences of price and the trends in which price moves. For the serious investor, being aware of tendencies toward magical thinking is useful in the sense that even logical and rational analysts may develop blind spots. For example, if an investor experiences an exceptionally high profit on one trade, the human tendency is to look for actions that preceded a decision and to try and repeat them. If those actions were based on analysis, this is a logical process. But as a subtle aspect of human thought, it is all too easy to fall into the blind spot of post hoc, ergo propter hoc. In that case, even while thinking logically, the analytical process could be affected by magical thinking. The next chapter examines the nature of resistance and support and how these trading range borders bring discipline to trend analysis. When trends remain within well-defined trading range borders, the conclusion is that the trend remains healthy and will continue. However, you will learn just as much about the duration of a trend and potential reversal when price breaks out of these borders. Knowing whether price will retreat back into range or set up a new higher or lower range is essential to trend analysis.

Endnotes

1 Fisher, Gregg S. “How to Protect Investments from Cataclysmic ‘Fat Tails.’” Forbes at www.forbes. com (October 14, 2009). 2 Walker, Helen. Studies in the History of the Statistical Method. Baltimore, MD: Williams & Wilkins Co., 1931, pp. 24–25. 3 Bollinger, John. Bollinger on Bollinger Bands. New York: McGraw-Hill, 2001. 4 Grimes, Adam. The Art & Science of Technical Analysis: Market Structure, Price Action & Trading Strategies. Hoboken, NJ: John Wiley & Sons, 2012, pp. 196–98. 5 Clark, C.A. “Hypothesis Testing in Relation to Statistical Methodology.” Review of Educational Research, 33 (1963): 455–73. 6 Fama, Eugene. “Random Walks in Stock Market Prices.” Financial Analysts Journal, January– February, (1995): 75–80. 7 Myerson, Roger B. Game Theory: Analysis of Conflict. Cambridge, MA: Harvard University Press, 1991, p. 1. 8 Poundstone, William. Prisoner’s Dilemma. New York: Doubleday, 1992. 9 Colman, Andrew M. A Dictionary of Psychology, Third Edition. Oxford, UK: Oxford University Press, 2012, p. 436. 10 Glucklich, Ariel. The End of Magic. Oxford, UK: Oxford University Press, 1997, pp. 32–33. 11 Lévy-Bruhl, Lucient. How Natives Think. New York: Knopf, 1925, p. 36.

Chapter 3 Resistance and Support: A Trend’s Moment of Truth Breadth of trading defines volatility. A larger number of points between resistance and support points to higher volatility, compared to a smaller breadth of trading and lower volatility. The trend itself can exist only because the levels of resistance and support are recognizable. However, this can take many shapes and sizes, and duration of a trend relies on whether or not the breadth of trading holds up. For swing trends, the levels of resistance and support might be only a few sessions; or the swing trade itself is likely to occur within the current breadth of trading as prices rise to resistance and fall to support without breakouts. For secondary trends, breadth of trading may involve testing of either resistance or support. A price move opposite the direction of the secondary trend may be a retracement, a swing reversal of varying duration, or an actual change in the trend. For a primary trend, a consistent and long-lasting breadth of trading indicates that the trend is going to continue; once the breadth of trading broadens or narrows, it is a signal that the primary trend might be coming to an end. If a breakout occurs, it could be the first sign of a reversal or, if the breakout holds, it could signal strong continuation. Momentum and volume are strong confirming signals at the point of breakout.

Tests of Breadth To understand the behavior of resistance and support, a starting point may be the analysis of advances and declines in the market as a whole. This is most useful for comparing the behavior of an individual stock in comparison to the larger market. Key Point: The advance-decline (A/D) line for individual stocks is more reliable than weighted index trends. It focuses on one stock rather than on a group of stocks.

The A/D line is a measurement of all stocks on an exchange or index. This measure offsets the tendency for weighted index influence from a few issues and provides a picture of how the market is behaving and on how an individual stock is likely to follow suit with the broader market. This line is a cumulative sum of the day-to-day differences between advancing and declining stocks. However, one potential flaw is that it measures only the number of stocks advancing versus those declining, without adjustment for the extent of change in values for either group.

DOI 10.1515/9781547401086-003

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 Chapter 3: Resistance and Support: A Trend’s Moment of Truth

The formula for the A/D line is: (A – D) + P = A/D A = number of advancing stocks D = number of declining stocks P = previous advance/decline line The A/D line identifies whether market participation is stronger among buyers or sellers. This is applicable to a large number of stocks, so the usefulness of the A/D line by itself is limited when analyzing a single stock’s price behavior. If the market has a series of straight upward or downward movements, the applicable A/D will reflect the trend. However, there are always advancing and declining stocks in any market condition. Each day’s advancing (minus declining) outcome is added to the previous (P) line. When the market line is compared to the trend of an individual stock, it demonstrates how that stock compares to the overall market.1 The A/D line can set up a form of divergence with individual stocks (or with other index measurements). A divergence appears whenever the overall market and individual stock move in opposite directions. For example, buyer participation appears to be dropping for the overall market but an individual stock’s breadth of trading is on the rise. This is a bullish divergence. When the opposite occurs (increasing advancing issues versus a decline in the breadth of trading of the stock), it is a bearish divergence. Although significance is given to divergence by many technicians, it often merely points out that large-scale movement is nothing but an average. Each stock moves for its own technical reasons and cannot be expected to conform to broader market trends. Divergence, as a result, might not hold special significance. However, it is one aspect of a stock’s beta (represented by the Greek symbol β), or a tendency for a stock to move with the market or more (or less) than the market. Assuming the overall market holds a beta of 1, stocks can be compared. A stock’s beta below 1 indicates either lower volatility than the broader market or a lack of correlation between the stock and the broader market. For example, the price of gold often moves opposite of the market. So testing gold through an ETF like GLD, the beta is likely to be quite high (either positive or negative) because gold will not follow the market for stocks.2 Beta is also useful in quantifying the immediate risk or volatility within a stock price based on beta over a range of dates. One writer proposed that under a method for evaluating a portfolio, “risk would be defined in terms of uncertainty, rather than simply as risk of loss. . . . Any portfolio involving risk above [beta] would, by definition, be speculative.”3 When applied as a method for measuring risk, beta aids in spotting the associated risks in current trends. This is more insightful than the A/D line, which provides directional conclusions without including scale. The A/D line is not especially useful if looked at in isolation. It provides confirming or contradictory information about single stocks relative to the broader markets, but nothing more. When diver-

The Nature of Resistance and Support 

 55

gence appears, analysts should look for signals that forecast reversal or continuation and strong confirmation of patterns in price, volume, or momentum. The A/D line by itself is not specific to the stock and should not lead to any decisions without further investigation, including a study of beta. However, when the A/D line changes from one side to the other, the influence of the overall market on individual stocks is one of many important signals. If similar but subtle changes are observed in the breadth of trading, it could foreshadow trend changes to follow. Among the reasons to use the A/D line cautiously is the lack of distinction between small or large moves in either direction. It is simply a count of the number of stocks advancing versus those declining. So a large move in the broad market looks the same as a modest move. Looking at this in another way, it means that a move in a $200 billion capitalization company is counted in the same manner as a move in the same direction for a company with only $10 billion in capitalization. The differences in the significance of advances or declines between these companies is obvious, but the A/D line makes no distinction between them. As a breadth indicator, the A/D line is limited in its application. It measures participation in either direction. Its degree of movement has to also be taken with caution, however. Much of the relative movement of the line depends on the timing of a starting point. This is accumulative measurement, meaning it will appear differently when dissimilar starting points are used. Key Point: A drawback in the A/D line is that its results rely on the selected starting point for the analysis.

Given the limited applicability of index-wide measurements like the A/D line, it should be recognized as only one of many possible indicators to judge the condition of the market as generally bullish or generally bearish. While individual stocks might tend to follow the overall market’s direction, there is no hard-and-fast that they must. Each stock reacts to the company fundamentals, momentum, and technical signals as well as to the larger market.

The Nature of Resistance and Support A definition of support and resistance should be agreed upon in order to delve into a more advanced discussion. To define both: “Support is a level or area on the chart under the market where buying interest is sufficiently strong to overcome selling pressure. As a result, a decline is halted and prices turn back again. . . . Resistance is the opposite of support.”4 Trends are defined by the attributes of resistance and support. The price points of these borders to the trading range are visual representations of supply and demand, and activity of price within these two prices reflects the short-term effects of many

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influences. Earnings, mergers, and dividend announcements are examples of fundamental events that directly influence price movement and continuation or reversal of all types of trends. Technical signals include double tops and bottoms or head and shoulders patterns based on the idea that a failed breakout leads to price movement in the opposite direction; candlestick signals add an even richer variety of reversal and continuation signals and confirmation. Although these signals are closely associated with swing trade timing, it is equally crucial to determine whether or not the current trend is likely to continue or end. Signals are also found in price patterns formed as moving average signals, volume signals, and momentum oscillators. All of these will be found within existing trends and all may be found as trends weaken and start to forecast reversal. An initial understanding of the supply and demand forces points out that excessive supply of shares at the current price will drive prices down and that support is the lowest price in the supply cycle. A scarcity of shares at the current price drives prices up and resistance is the highest price in the demand cycle. However, a point eventually occurs in which either supply or demand side price activity gathers momentum and crosses over resistance or support. The causes for this are many and cannot be simply assigned to distortions in supply and demand. Among the influences is market psychology, a tendency among traders to overreact to current news and to follow the trend rather than to anticipate when the trend is likely to end. Much of the signaling that is used to identify turning points in trends, whether swing, secondary, or primary, is likely to occur at resistance or support, especially when price gaps through in a breakout. At that point, reversal is most likely. However, if continuation signals are found and confirmed, the breakout is likely to succeed. However, any confirming signals should be confirmed with equally strong additional signals. The proximity of price to resistance or support is the most important determining factor in where price moves next, and in whether or not a current trend will continue or reverse. Key Point: Resistance and support levels and price proximity to them are the points where reversal is most likely.

In understanding resistance and support, the initial significance is a factor of supply and demand characteristics; however, there is much more to consider in the technical attributes of a trend. Resistance is the price level where selling activity is likely to prevent price from moving through that border. As price advances close to resistance, buyers become less inclined to buy, knowing that the likelihood of price continuing beyond resistance are slim. At the same time, and for the same reason, sellers are more likely to enter sell orders as price moves higher. So this weakening of the bullish move by both buyers (less inclined to buy) and sellers (more inclined to sell) explains why resistance is more likely to hold up than to break down. This is why breakouts,

The Channeling Trading Range 

 57

especially with gaps, are aberrations in the orderly interactions between buyers and sellers and why reversal is most likely at that point. Support is the exact opposite. It is the lower border of the trading range representing the price at which demand remains strong enough to prevent any further price decline. As price reaches support, buyers are likely to pick up buying activity because prices reach bargain levels. And sellers become less likely to sell. So this combined activity tends to cause price to hold at support and to move back toward the middle of the trading range. Just as price may break through resistance at the top, it can also break through support at the bottom. A breakout accompanied by price gaps is most likely to reverse. Swing traders look for such moments, realizing that proximity to support with gapping price movement is the most likely point for reversal. However, if continuation signals appear at this point, it is possible that a new, lower trading range will be established. These “rules” of supply and demand are simplifications of how price movement works. Many additional influences are at work in determining trend behavior, and supply and demand cycles are only one of those influences. Both fundamental and technical causes are equally influential in how trend movement occurs, both in the short term and over many months in a primary trend.

The Channeling Trading Range When a stock is trading within a dynamic trading range, it is a “channeling” stock. Thus, a stock’s price may rise or fall in the channel without changing the breadth of trading. This is the distance between high and low price, and even as a stock’s price moves up or down, the distance remains constant, thus the description of a channel. However, unlike a flat, sideways-moving resistance and support level, in the channel, both resistance and support rise or fall in unison. It is a set of two trend lines (one each for resistance and support, evolving but maintaining the breath if trading) moving in the same direction and to the same degree; this is commonly found in stock charts and channel lines (this is illustrated in figures found in Chapter 4) and not distractions from the current trend, but strong confirmation that the trend is consistent. As long as it is on the move (a) in the same direction, (b) with the same breadth of trading, and (c) without breakouts in either direction that persist (other than shortterm retracements), it adds strength to that trend. Key Point: Channeling prices—trending with an unchanging breadth of trading—visually identify the continuation of the current trend.

In a channel, the trading range is well-defined, meaning that the distance between top and bottom remains the same even as the price rises or falls. Channels may be ascending, in which the breadth of trading holds to the same point spread but prices

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are on the move upward. They may be descending, in which the price levels decline. And they may be flat, with sideways price movement representing a period of uncertainty, a struggle between buyers and sellers. An example of a chart containing both flat and ascending channels is seen in Figure 3.1.

Source: Chart courtesy of StockCharts.com Figure 3.1: Resistance and support—flat and ascending channels

The year 2012 was represented by a flat channel with only a 10-point breadth of trading. However, for most of 2013, an ascending channel was in effect but with the same average breadth of 10 points. In 2014, the trend hit a plateau and returned to the flat variety, still with a 10-point breadth. Although the three-year price trend moved dramatically, the 10-point breadth of trading was witnessed both in the flat periods (2012 and 2014) and in the channel trend (2013). The consistency of this pattern, not only in duration of each of the three phases, but also in the breadth of trading, demonstrates the strength of channeling stocks. In the chart, three distinct secondary trends occurred, flat during the first and third years and ascending in the second year. An examination of Boeing’s chart before and after the period reported shows that the stock was in a long-term primary trend: Year Range 2009 $40–$55 2010 $55–$60 2011 $60–$67 2012 $67–$75 2013 $75–$135 2014 $135–$135 2015 $135–$150 (2.5 months)

Reaction High and Low Prices 

 59

The pattern goes from flat to ascending, repetitively. So between 2009 and the first quarter of 2014, the overall trend was between $40 and $150 per share, a 375 percent growth in the price over 6.25 years.5 The remarkable aspect of this channeling stock trend is how consistently the breadth of trading held through several years. The levels of resistance and support between 2012 and 2014 were easily identified, both in periods of flat and ascending channels. This makes tracking and prediction based on the resistance/support relationship very dependable. You can not know how long the flat or ascending period is going to last, however. For example, in two and a half months of 2015, the stock price rose 20 points, twice the rate of the previous six years. This is a potentially troubling change. It could signal the coming of an adjustment, especially since the company had no downtrends of any duration for the entire period. It could also be a temporary change in the breadth of trading that will settle down into a more familiar pattern like the one established between 2009 and 2014.

Reaction High and Low Prices Both resistance and support can be identified by location of reaction high and reaction low prices. A reaction high is a price peak appearing during an in-range movement in price. The movement itself may be sideways or trending up or down; however, reaction highs are likely to occur following a downward movement, and the high price will set resistance. A single occurrence is not enough, however; resistance can be drawn on a series of reaction high prices. The reaction low is the opposite. It is a price downward spike occurring within range, often offsetting (reacting to) a short-term rise in price. To set support, find a series of reaction low prices. Key Point: Identifying a new level of resistance or support depends on two or more price spikes after a movement to a revised breadth of trading. Once the established breadth is violated, the previous resistance or support becomes invalid and a new level is set.

The reaction levels—both high and low—represent failed attempts at breaking through resistance or support. For short-term trading, these points clearly draw the “line in the sand” where trading is thought to not violate. However, swing traders seek moments where price does move through those established reaction prices (especially with price gaps) so that the timing of a reversal trade makes sense. For longer-term trend analysis, reaction high and low prices mark resistance and support for the duration of the trend. These may be violated through retracement moves in either direction, especially in narrow breadth of trading. However, once price begins repeatedly breaking through and then retreating, it implies that breadth

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of trading is broadening, or that a breakout will eventually succeed. So the current trend may be ending or, on the other side of the range, expanding. To interpret reaction high and low moves correctly, they have to be confirmed with other price, volume, or momentum signals. However, the activity surrounding resistance and support levels does indicate the threat that a current trend may be ending. Tracking the reaction moves within the trend often reveals coming breakout. A problem with reaction price movement is that rather than signaling trend movement, it could simply be an attribute of a particularly volatile price situation. Such charts are difficult to read. When prices continually test resistance and support with reaction high and low moves, it is difficult to determine whether the trend is in effect. It is equally difficult to determine which direction a breakout will take. Reaction high prices may consist of a series of “M” high or double top formations, offset by a series of “W” low or double bottom signals. When this offset occurs repeatedly without price breaking out, the contradiction in signals negates both. Rather than viewing the reaction price movement as a signal, it is more likely to signal volatility and uncertainty in which direction price will move. Although volatility of this character often is associated with short-term price activity, it also may exist in longer-term trends and create a chronic state of volatility. Such patterns may exhibit breakouts, but these may be short-term in nature and offset a high breakout with a low breakout. Even for longer-term trends, the excessive reaction pricing is difficult to predict.

The Bouncing Price within a Trend The offsetting reaction high and low price pattern is especially difficult to interpret when resistance and support are both moving in a flat progression. With rising or falling price trends, the offsets can be interpreted by comparing price to volume and momentum signals; however, when the reaction bounces between an established high and low levels, you may see breakouts in both directions, repetitively and without identification of any clear trend to follow. The longer this situation endures, the less trust should be invested in the appearance of any price movement that seems to be holding. The past experience of shortterm breakout makes the sideways trading range stronger, but adds great uncertainty to the ability to forecast any new trends. While some signals are strong and specific, the bouncing range is both volatile and uncertain. For example, Figure 3.2 included a sideways-moving bouncing range for more than one year, with short-term breakouts in both directions.

The Bouncing Price within a Trend 

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Source: Chart courtesy of StockCharts.com Figure 3.2: Resistance and support—bouncing range

The trading range in this three-year period was volatile. It ranged between $90 and $135. The year 2013 and beyond was characterized by a sideways-loving range from resistance of slightly above $120 to support slightly above $110. Price within this range consisted of four reaction high moves culminating in a breakout lasting three months and three reaction low price moves resulting in a two-month breakout below support. Key Point: Trends do not always emerge after a volatile price pattern. Reaction high and low trends may indicate the lack of a new primary trend.

As of year-end 2014, it was impossible to determine any emerging trend or direction for the price. Volatility continued. By mid-2015, CVX decline under $65; by early 2018, it rose to $130. And by January, 2019, it had fallen to $109. The activity between high and low reaction prices was not only volatile, but contradictory as well. In a case like this, determination of whether to trade or forecast any trend, you would need more information about volume and momentum; however, indicators confirming price are only valuable when clear trend movement has been underway and you seek confirmation of reversal. In this case, no clear trend existed. So the best course would be to wait until a primary or secondary trend becomes established and to then analyze price and attempt to confirm the strength or weakness of the trend. Until volatility settles down, this is a challenging requirement and could be difficult or impossible.

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The Flip One of the most revealing patterns in resistance and support is the flip. This occurs when previous resistance becomes a new support level or when previous support forms as new resistance. In these occurrences it often becomes clear which direction a trend is taking. It is also true that after the flip the newly established resistance or support level tends to be exceptionally reliable—not always, but often. To draw this conclusion, you should rely on not only price action but also on confirmation. The exceptional aspect of the flip is that it signals a transfer from demand to supply (on the downside) or from supply to demand (on the upside). This is a strong transfer, which translates to strong newly established price limits on either side. An example of a flip from resistance to support is found in Figure 3.3. This bullish trend is strengthened and confirmed by the clear transfer. The three tests of newly established support on October 2013, February 2014, and October 2014 were all weak and none succeeded. Price continued to rise in a firmly established bullish trend.

resistance

support

Source: Chart courtesy of StockCharts.com Figure 3.3: Resistance and support—flip (resistance to support)

The upward trend actually began in July 2012 when price had dipped below $80 per share. By the end of 2014, price had risen to $145. Based on the strong and long-term growth in the stock price, and also on the flip to new support at $120 per share, the bullish primary trend in this case appears to be well established. It is not likely to change unless that support level is successfully violated and confirming bearish signals appear. A bearish move may consist of a flip from previous support to new resistance. An example of this was seen in a more volatile pattern shown in Figure 3.4.

Wedge-Shaped Trends 

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resistance support

Source: Chart courtesy of StockCharts.com Figure 3.4: Resistance and support—flip (support to resistance)

The previous trading range, lasting more than two and a half years, moved in a 33-point breadth of trading, between $167 and $200, with some limited failed breakouts above. A triple bottom formed between October 2013 and February 2014, creating reaction lows. However, price following this remained below $195, a sign that the range was narrowing. Price gapped lower and fell below support to set a new resistance level below $165 per share. This newly established resistance level held for at least two and a half months, so it clearly was a flip from support. Key Point: When resistance and support levels flip, it often points to a stronger than average hold on those breadth levels.

The volatility within range preceding the flip had ramifications for long-term trend analysis. The price was range-bound for so long that the move below support, occurring for the first time in nearly three years, was notable, not only due to the duration of prior support, but also due to the strong decline with a nearly 20-point gap but also a steep decline from above $190 down to as low as $150 in only three months.

Wedge-Shaped Trends The wedge is a commonly appearing pattern with two lines, one sloping upward and the other sloping downward. The pattern shows price range narrowing as the lines move toward one another. Some wedges are not especially strong signals, however. The more pronounced the slope of the wedge and the more rapid the narrowing range, the stronger the reversal signal is likely to be. The wedge is used as a confirming pattern in swing trading, but repetitive wedges also forecast coming reversal in longer-term trends.

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The rising wedge is bearish and anticipates reversal once the breadth of trading has narrowed. In order to work as a legitimate bearish reversal, the wedge must appear after a period of bullish price movement. In a primary trend, the wedge may take six months to one full year, and in a secondary trend you would expect the wedge to average three months in duration. However, there are no set rules for its duration. You also expect to see two or more reaction highs form the wedge’s resistance level. On the bottom side of the wedge expect to find at least two reaction lows to form support. The turning point occurs once the established support line is broken after which price is expected to decline in confirmation of the bearish nature of the wedge. An example meeting these criteria is found in Figure 3.5. The bullish trend began with the low price under $60 at the end of June 2012. Since that point, prices rose for two years through June 2014. The wedge formed from mid-2013 to mid-2014. The resistance level was marked by two reaction highs, at October 2013 and at April 2014. Support was marked beginning in June 2013 with reaction lows at February 2014 and in March 2014.

Source: Chart courtesy of StockCharts.com Figure 3.5:  Resistance and support—rising wedge

The support line ended once prices declined in September 2014 and the bearish wedge was confirmed as prices fell below previously established support. A falling wedge is bullish and has to follow a bearish trend. A strong example meeting the criteria of a falling wedge is found in Figure 3.6.

Triangle-Shaped Trends 

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Source: Chart courtesy of StockCharts.com Figure 3.6: Resistance and support—falling wedge

The downtrend began after the high price level of $95 in September 2012. The decline lasted until April 2013, with the falling wedge marking the bear trend clearly. Several reaction lows are found along the declining support and reaction highs were found along the declining line of resistance. Confirmation of the bottom of the bearish trend is found in the double bottom forming in April and July 2013. Key Point: Wedge formations—narrowing breadth trends—forecast reversal, although the timing of the actual reversal relies on confirmation.

After the bottom was confirmed, a strong uptrend followed for the next eighteen months through to the conclusion of this chart. This pattern demonstrates an exceptionally clear reversal, anticipated by the falling wedge and confirmed by the double bottom. In this chart, the bear trend between 2012 and 2013 was probably a secondary trend, but the last eighteen months of the charted period represent a net bull primary trend for this stock. During this time the stock price more than doubled.

Triangle-Shaped Trends Another formation, potentially setting up strong continuation patterns, is the triangle. Unlike the wedge, which is a reversal, the triangle is a continuation pattern. The ascending triangle is bullish. This means it has to be found during an existing uptrend. It consists of a flat resistance with at least two reaction highs and rising support with at least two reaction lows. The triangle narrows until price levels break through and rise above resistance, ideally forming a new support on a flip from resistance. An example of the pattern is found in Figure 3.7.

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new support

Source: Chart courtesy of StockCharts.com Figure 3.7: Resistance and support—ascending triangle

The uptrend began at the same time as the rising support of the ascending triangle, at the beginning of June 2012. It continued for more than a year, making it likely that this was either a secondary trend or the beginning of a new bullish primary trend. Resistance contained several reaction highs but was not violated until late May 2013. Support contained two reaction lows at April and June 2013 before price fell lower temporarily in late August. However, the continuation was confirmed as the price level rose strongly above the previous resistance of $87.50 per share. Resistance flipped to become support, and this level of $87.50 was tested with three attempted breakouts, but none held. This strengthened the assumption that this support level would hold. Following the period shown, price did test support twice more, on February 15 and between January 28 and 30, 2015. However, none of these breakouts held and price continued moving higher. The descending triangle is an equally strong continuation signal in a bearish market. It requires existence of a current downtrend. An example of this pattern in a primary bearish trend is seen in Figure 3.8.

Triangle-Shaped Trends 

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Source: Chart courtesy of StockCharts.com Figure 3.8: Resistance and support—descending triangle

The period beginning in 2012 does not clearly mark a downtrend. Looking back, the price of USO was at $47 per share in May 2011 and declined from that point to the beginning of the period shown. The overall trend is bearish, with the chart concluding below $20 per share, a drop of more than half its value from beginning to end of the chart. Key Point: Wedges are reversal signals, but triangles indicate continuation of the current trend.

The flat pattern from late 2012 until late 2014 represents a pause in the bearish trend. The resumption of the price drop was anticipated by the descending triangle appearing between July 2013 and October 2014. This consisted of level support with reaction lows in December 2013 and in January 2014; and a breakout below this established support level in early October 2014. On the top side, the descent of resistance occurred in two steps, from October 2013 through February 2014, and again between July 2014 and October 2014. Both of these falling resistance lines included at least two resistance high points. This could be viewed as two separate descending triangles, or as one long with a rally in between. In either case, the longer-term trend was a primary bear trend, and the descending triangle confirmed it. The third type is the symmetrical triangle. This is the least useful of the three types as it can be either bullish or bearish. Although it is supposed to act as a confirming signal, it can also represent reversal of a secondary trend. The unclear meaning of the symmetrical triangle—as either bullish or bearish and as either reversal and continuation—makes its usefulness less than clear. An example of this pattern is seen in Figure 3.9.

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 Chapter 3: Resistance and Support: A Trend’s Moment of Truth

Source: Chart courtesy of StockCharts.com Figure 3.9: Resistance and support—symmetrical triangle

The longer-term history of this stock appears to be bullish. It moved from about $1.50 per share at the beginning of 2009 to $3.25 in 2010 and $3.70 in 2011. So the long-term trend appears to be bullish. However, during 2014, the price fell from above $11 down to about $4 per share by the end of the year. Therefore in this example, this makes the symmetrical triangle a reversal. In analyzing the trend, relying on the symmetrical triangle by itself is not suggested. You need stronger signals and clear confirmation before deciding whether a pattern means continuation or reversal.

Support and Resistance Zones Although resistance and support are most often represented as single lines, they may also be shown on charts as zones. Typically, the lines are drawn between reaction high and reaction low points. In some patterns, zones more accurately show the likely formation trend. Because precise resistance and support levels are not always apparent, the zone approach allows you to map out the course of a trend without rigid compliance with rules. For example, if price breaks a trendline, does that mean the trend itself has ended? This could signal the beginning of a reversal formation, but not necessarily. Every price pattern and every form of confirmation sets up in its own way. So trend analysis has to be a flexible science based on a combination of observed developments, signals, and confirming indicators. The resistance and support zone can aid in this process. Key Point: Clear price points for resistance or support are not always apparent. At such times, resistance and support zones add flexibility to trend analysis.

Support and Resistance Zones 

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An example of resistance zone is found in the chart in Figure 3.10.

resistance zone

---

-

--- - - ort - -g- supp in - - ris ---

---

---

-

Source: Chart courtesy of StockCharts.com Figure 3.10: Resistance and support—resistance zones

The range between $55.50 and $56.75 is treated as a resistance zone in this chart. The location of resistance elsewhere is less certain. The prices of $55, $56, and $57 could all be considered as resistance on the basis of recurring reaction high prices. However, the multiple M high formations touching all those price points create doubt concerning the appropriate resistance price. When viewed within the zone, however, those M formations at July–August 2013, October–December 2013, April–May 2014, July–August 2014, and August–September 2014 all approach different high price levels before the breakout on October 2014. In comparison, the support price does not need to be expressed as a zone, as it is clearly set at $50 per share throughout the period charted. The resistance zone applied here not only adds certainty to analysis of the sideways movement of price in the 5- to 7-point range. It also highlights the repetitive “M” tops. The attempt followed each “M” top to lead to price decline failed to move below the $50 support. In fact, starting in June 2014, support appeared to be rising, setting up the appearance of an ascending triangle against the resistance zone. This predicts the strong price breakout that quickly followed. Support zones function in the same manner, often clarifying the true level of support as a price range rather than as a specific price. Figure 3.11 provides an example of a chart with not only one, but two distinct support zones.

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 Chapter 3: Resistance and Support: A Trend’s Moment of Truth

f - -a-lling r - - - esis - - - tanc --- e ---

f - -alling - - re - - sis - - tan - - ce ---ce - an ist - es - gr -lin fal - - --

support zones

---

Source: Chart courtesy of StockCharts.com Figure 3.11: Resistance and support—support zones

The first support zone extends between $42.75 and $47.50 per share. An attempt to select a single-price support zone within this range presents several problems. Support at about $43 per share could work based on the eighteen-month extension, but in between several other prices appear to provide interim support levels as well. So $45.50 and $46.00 per share could have worked as support levels if there were more consistently in the duration. The resistance fell twice within the period of the support zone, setting up descending triangle patterns foreshadowing a price decline. The third instance of falling resistance set up the second support zone between $32.50 and $33.50 per share. At the same time, resistance price appeared to stabilize at $37.50. Support could have been selected to reside at several points during this six-month period; however, using a support zone made more sense because it held and brought the appearance of order to the chart. Key Point: When specific price points are not obvious, resistance and support zones provide the same clarity in defining the breadth of trading.

Dynamic levels of resistance and support often are difficult to interpret. A level and firm price line moving sideways is easy to test based on whether or not price is able to breakout above resistance or below support. However, when resistance and support are both rising or both falling, it is not as clear how strong or weak the trend is, especially a long-term trend.

Breakouts as Signals of Supply and Demand Adjustment 

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Breakouts as Signals of Supply and Demand Adjustment The entire nature of trends is changing constantly even as the trend moves consistently. When the trend is moving sideways for an extended period of time, analysis and forecasting is more difficult because there is no dynamic trend to reverse. However, when trends are rising or falling, a key indicator is a breakout. By definition, resistance and support are supposed to prevent breakout from succeeding, confirming that the current breadth of trading is holding. If a breakout does succeed, it means something has changed. When a breakout succeeds in the direction of the existing trend, it not only confirms the trend but accelerates it. In an uptrend, successful breakout above resistance means that even while buying pressure (caused by excess demand) was in control, that pressure has increased. In a downtrend, successful breakout below support means that selling pressure (caused by excess supply) was in control of the trend, and that pressure has increased. Any time that price moves outside of the established breadth of trading, it causes concern. The typical understanding of breakouts in a direction opposite of the trend is that a reversal has begun. However, it could represent one of three events. First is a complete reversal in the primary or secondary trend; second is a temporary offsetting trend (secondary within the primary or swing within the secondary); and third, the offsetting price could be a retracement in which case price should return to its established range. Even with these observations of shifts in supply and demand (with breakout meaning one side has lost and the other has won), many additional causes lead to reversal. These may be well beyond the forces of supply and demand and may include market competitive position, fundamental changes, and technical aberrations in price. Many price moves occurring over the long term are factors of beta. A number of trends, especially secondary trends, may exceed the overall market’s trend in the same direction. The extent to which individual stocks are influenced by the market, and to which that influence is reflected in beta, is not a precise matter. It is also likely to change over time. Beta explains a lot in the short term, but for longer-term trend analysis, the price range and trend direction are more likely to be influenced by the fundamentals: revenue and profit growth, P/E ratio, dividend yield, and control over the level of long-term debt as a percentage of capitalization. Aiding in interpretation of dynamic breadth of trading are the trendline and channel line. These technical tools help trend analysts to (a) spot duration, (b) see changing slope as the trend evolves, and (c) distinguish between reversal and retracement. The next chapter explores the nature of trendlines and channel lines.

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Endnotes

1 Dworkin, Fay. “Defining Advance-Decline Indicators.” Technical Analysis of Stocks & Commodities, July 1990. 2 To find a stock’s beta, use an online calculator like the one at https://www.buyupside.com/ calculators/beta.php 3 Rizzi, Joseph V. “Portfolio Theory, Capital Markets, and the Marginal Effect of Federal Margin Regulations.” Loyola University, Chicago Law Review, 8, issue 3 (Spring 1977), at http://lawcommons.luc. edu/lucli/vol8/iss3/3 4 Murphy, John J. Technical Analysis of the Futures Market: A Comprehensive Guide to Trading Methods and Applications. New York: Prentice Hall, 1986, p. 59. 5 www.StockCharts.com, through first quarter, 2012.

Chapter 4 Trendlines and Channel Lines: The Shape of Things to Come Trends are clearly shown through drawing of trendlines and channel lines. These are among the most basic of indicators and they bring the trend to life by outlining the slope and duration of a trend with great clarity. Even though the trendline and channel line are easily viewed and understood, they also support numerous related indicators, notably highlighting the differences between retracement and reversal and how trends are managed by analyzing shortterm patterns like flags (which are four sided) and pennants (which are triangular).

Signal Patterns versus Trends A price pattern tends to be short term in nature and points to the immediate tendencies of price. For example, a double top or double bottom strongly forecasts reversal in the direction of price, and these are especially compelling when occurring at resistance or support levels. However, they reveal only what is occurring in price strength or weakness of the moment. Key Point: A price or signal pattern is an immediate indicator of change, but not always a sign of trend reversal. It may indicate a move within the current trend’s breadth.

The same is true for candlestick signals, momentum oscillators, moving averages, and volume levels. All of these, by themselves, relate to price patterns and are useful as part of a swing trading strategy. However, for longer-term primary and secondary trends, these short-term signals are of limited value by themselves. Used in combination, however, these signals can forecast primary and secondary trend reversals. For this to effectively signal a change in the trend, several elements should be in place, including: 1. Proximity to resistance or support. The closer to these all-important price levels you find reversal signals, the greater the likelihood of that reversal occurring. This applies to swing trends but also to primary and secondary trends, assuming other elements are also present. 2. Signals of exceptional strength, preferably multiple signals. The price signal is one possible way to forecast reversal; however, volume, moving average, and momentum should also be considered in determining whether a reversal signal is minor or major. This also helps distinguish between reversal and retracement. DOI 10.1515/9781547401086-004

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A retracement tends to appear with no specific signal and is likely to act like a swing trend, lasting only a few sessions in most cases. 3. Confirmation of equal strength to the signal(s). Confirmation is essential in the establishment of reversal. Just as the Dow theory requires confirmation between separate averages, individual stocks rely on confirmation between separate signals. 4. Strong trends that are likely to reverse. Statistically, the longer a trend moves in one direction, the more likely it will slow down or reverse. When you have tracked an especially strong trend (strong in the sense of angle and time), you seek exceptionally strong reversal and confirmation signals. The strength of a trend often is associated with the strength of the reversal patterns and signals. 5. Combinations of signals, including price, volume, moving averages, and momentum oscillators. All these signals are useful in timing swing trades, but when used together to seek reversal for primary and secondary trends, they provide a powerful combination of signals. In comparison, a weak signal or worse yet, contradictory signals, confuse the issue and are likely to give out a false indicator about reversal. In making a distinction between primary or secondary trend reversals, and the shorter-term gyrations and swing trades most stocks experience, specific attributes create short-term uncertainty, contradiction, and retracement. These include a tendency for many traders to follow the popular current move, also called “herding,” in which a short-term trend is prolonged due to greater activity—in a sense, jumping onto the trend in the belief it is going to continue. However, herding invariably is short term. So, unusual moves in price are likely to work as swing trends and lacking strong reversal signals in combination should be ignored or traded contrary to the popular actions of other traders. Key Point: A tendency toward crowd following, or herding, leads to ill-timed trades and errors in understanding what a price signal means.

The reasons for patterns as they emerge are not immediately clear; however, they can be observed in charts and used to time swing trades. For longer-term trades, the emergence of price patterns, notably for reversal, presents a problem. Distinguishing between a short-term reversal or retracement and a longer-term primary or secondary trend change is elusive. One study pointed out that, “While many technical trading rules are based upon patterns in asset prices, we lack convincing explanations of how and why these patterns arise, and why trading rules based on technical analysis are profitable.” The study also noted that confirmation bias is likely to “play a key role in other types of decision making.”1

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The tendency, especially among swing traders to seek confirmation for what they believe is occurring rather than for what is truly occurring, is self-deluding and leads to poorly timed trades. In analyzing short-term price patterns, anyone can find a signal that fits with their belief; acting on it, especially when tracking primary or secondary trends, is an error. Even so, this behavior is a chronic problem in trading. Longer trends experience the short-term jumps in price in both directions, but lacking confirmation in several forms, the swing trend should be ignored by those who want to protect permanent equity portfolio positions and prevent ill-timed trades. Some programmed trading is based on models in which selling activity increases in down markets and buying activity increases in up markets, even when trend analysis might suggest taking the opposite action. A contrarian will ignore the activity that makes no sense based on trend analysis; however, this risk management-based automated trading activity has the effect of extending intermediate trends. Focusing on primary trends requires paying very little attention to swing trends and only cautionary awareness of secondary trends. Effective trend-following requires observation of trends on both the technical side and the fundamental side. When price moves well beyond what the fundamental trends justify, the result is easily measured by rising P/E ratio and related tests. Investors who follow trends only with technical indicators are prone to make mistakes in the timing of trades. Fundamental analysis—the study of profitability, capitalization and working capital of a company, in other words, all things financial—provides a strong base for identifying long-term trends and levels of price volatility growing from or contradicted by fundamental volatility. However, timing of what you gain from the fundamentals is less certain: The advantages of fundamental analysis are its systematic approach and its ability to predict changes before they show up on the charts. Companies are compared with one another, and their growth prospects are related to the current economic environment. This allows the investor to become more familiar with the company. Unfortunately, it becomes harder to formalize all this knowledge for purposes of automation (with a neural network for example), and interpretation of this knowledge may be subjective. Also, it is hard to time the market using fundamental analysis. Although the outstanding information may warrant stock movement, the actual movement may be delayed due to unknown factors or until the rest of the market interprets the information in the same way.2

By “outstanding” information, the statement above refers to “known” information about the company. The observation was offered that when it comes to the fundamentals, information and reaction may lag so that an immediate impact is not always seen. As a technically based management tool for long-term trends, the trendline and channel line are starting points for further investigation. Upon viewing what appears a possible slowing down or reversal of a trend, further confirmation should be found and fundamental trends checked to confirm what appears to be changing in the price trend.

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Key Point: Trendlines and channel lines provide a structure for further analysis, but changes in these lines require confirmation before action is taken.

Trendlines and What They Reveal Trendlines are straight lines drawn under a rising price move or above a declining price move. The points from end to end are the low points (in a rising trend) or the high points (in a falling trend). The “perfect” trendline ends as soon as the price level stops the line from moving farther without running into daily activity. Temporary retracements or spikes violating the line can be overlooked in the greater interest of tracking longer-term price movement. For example, in Figure 4.1, a bullish trend was underway for the last two years of the three-year period charted. The line was disrupted in February 2014 before the trend resumed. For five months, the pattern was unclear until the upward movement again resumed in November 2014.

Source: Chart courtesy of StockCharts.com Figure 4.1: Uptrend line

Many attributes of the trendline are like those of resistance and support. However, a distinction is that either of these trading range borders may last longer than the trendline or may also be established for shorter periods of time. For example, in the chart in Figure 4.1, a case could be made to set a series of shorter-term support and resistance levels even as price levels continued to rise. The tendency for resistance and support to set up points at which attempted breakouts fail do not always apply to trendlines. A declining trendline may also last for many months or, in the case of the chart in Figure 4.2, show up as a series of declines with some shared characteristics (gaps, rapid price movement, and other price patterns).

Trendlines and What They Reveal 

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Source: Chart courtesy of StockCharts.com Figure 4.2: Downtrend line

The chart in Figure 4.2 is such an example. During the downtrends, price fell rapidly and sharply. This was not a signal of a bearish overall trend, however, noting that between August 2012 and December 2014 (nearly two years) the price range was similar. This is more like a very volatile sideways price movement (a consolidation trend) spanning 10 points. Key Point: Volatile interim movements within a consolidation trend may be deceiving; understanding the prevailing trend is the first step.

The 10-point move between $37.50 and $27.50 lasted from May 2012 through December 2014. An interesting departure was seen between November 2012 and August 2013. At the beginning of this period, price gapped sharply upward nearly 5 points and remained between $52.50 and $37.50 for the next nine months. This was followed by a sharp downward gap of 7 points. This is an unusual pattern that could be defined as a secondary trend but appears more like an aberration in an otherwise established longer-term primary trend with a lower range. The volatility throughout this period, characterized by sharp downturns in price as well as by large price gaps, supports the suggestion that the middle-range price move was not typical of the trend for this stock. However, the volatility itself makes it very difficult to predict the next price move. The trends are not long term, and they are not consistent. The repetitive downward trendlines provide little guidance to management of the volatile price. However, most of the price movement occurred in a 10-point range. That is quite volatile given the typical price of this stock; but it is not as volatile as a similar pattern would be for a higher-priced stock. A far more orderly version of trendlines is found in Figure 4.3, which demonstrates a consistent level of secondary trends alternating in direction. The first year was a bearish trend, followed by two years of a bullish trend. Identifying the turning

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point for this trend would involve studies of price, volume, moving average, and momentum indicators.

Source: Chart courtesy of StockCharts.com Figure 4.3: Alternating lines

The price gaps and large downward dips in price ranges at the very bottom of the downtrend provide a clue that a reversal was about to occur, but to call this as the turn of a primary or secondary trend would demand in-depth analysis of all signals and confirmation. There was a volume spike at the very bottom as well as a price gap. Both characterize a reversal, but lacking more signals it was not clear whether this was merely a swing trend reversal or a major primary trend change of direction. The fact that the pattern did set up a new primary trend was not evident merely from the volume spike and price gap. The repetitive price gaps found over the next nine months as price rose strongly were more reliable indicators of the new trend, especially with the newly established trendline.

Price Increments on Charts In determining whether trendlines exist in a high-volatility price pattern or a low-volatility price pattern helps determine whether the trend has stability and is likely to continue. However, recognizing the level of volatility depends on the scale of the chart. Charts prepared through an online free charting service are scaled automatically. The scaling is based on the time and the total range of prices with the goal to fit all trading activity into the chart’s rectangle. This means that with a narrow range, scaling will also be narrow and with a very broad range, scaling will be much greater. A consequence of this automatic scaling rule is that comparisons of volatility are diffi-

Price Increments on Charts 

 79

cult. What appears highly volatile might represent price movement in a narrow range from high to low price. Key Point: Scaling is set by trading range, so comparisons of price movement or volatility between two or more stocks is not accurate unless scaling is identical.

For example, Figure 4.4 contains a stock chart with a narrow scale of prices ranging between $80 and $52.50 over three years.

gap

gap

gap

spike

spike

spike

Source: Chart courtesy of StockCharts.com Figure 4.4: Narrow scale

Although the price patterns on this chart appear to be volatile, the degree of change rarely is greater than 20 points. In this instance, volatility is limited to a small price range but it is nonetheless a volatile history. Several trendlines are identified, most of which were steep. A secondary pattern also was found. In three instances, a sizable price gap was accompanied by a significant volume spike. These two signals together were compelling and tended to set up island periods of trading. In these periods, one from January to July 2013 and the other from June to August 2014, were initiated by the gap/spike sequence. These could be considered as secondary trends and both had another interesting characteristic. After the initial gap, the trend moved opposite the previous price direction. A chart such as this is difficult to track because the trends within it were inconsistent. However, it would seem a good candidate for a swing trading strategy. The long-term primary trend moves from a low price under $52 to a high of nearly $80, so

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it is bullish over the three years. With so much inconsistent price movement within that trend, prediction is less certain than for many charts. A wide-scale example makes an interesting comparison. Figure 4.5 reveals a bullish trend of nearly two years with little variation.

Source: Chart courtesy of StockCharts.com Figure 4.5: Wide scale

The level of volatility in this chart is like the previous one in terms of breadth of trading. Even so, it was more predictable due to the greater scaling. The previous chart scaling in 2.5-point increments and this one is scaled in 10-point increments. Another oddity is that the scaling itself narrowed as the price range rose. The chart gaps between $80 and $90 per share and between $190 and $200 were considerably different. This distorts the scaling and could deceptively create the appearance of lower volatility. This is a problem with trendlines on charts scaled differently and when the scaling itself is altered within the chart. The slope of this trend was much different than it appeared due to the narrowing of spaces between price points. If the gaps were reported consistently, the trendline would be shortened and would reveal a lower slope of change during 2014, a year in which the degree of change was lower than for 2013. This chart reflected a three-year change in price levels from $75 up to $200 per share, a 125-point move. Volatility was considerable despite its lower-volatility appearance. In trendline analysis, changes in the slope caused by point spacing not only distort the nature of the trend but may also bring into question the significance of reaction high and lows. To evaluate these properly, consistent scale is of great importance. On the chart in Figure 4.5, the reaction level does not appear to be significant. However, considering the narrowing scale during the 2014 price range, the trend was more sideways than up, and reaction high and low activity was volatile. This indi-

Trend Angles 

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cated that the primary trend that began in March 2013 was slowing down. By mid-February, the stock’s price was close to the level at the end of the period charted. Key Point: What appears as a dynamic price movement may be nothing more than a slight move in the larger picture.

Analysts aware of how the changed price spacing affects the appearance of the trendline might view 2014 not as part of a continuing uptrend but as the beginning of a consolidation period. This could also affect trade decisions based on likely changes in the primary trend. The change in a trendline’s angle is partially a factor of price spacing but also demonstrates differences in trend volatility.

Trend Angles When angles decrease as a trend develops, the tendency is for support and resistance to strengthen. Conversely, when the angle becomes steeper, resistance and support tend to weaken and may disintegrate entirely as volatility throws the trend into chaos. This makes forecasting more difficult as steeper trends represent growing volatility and uncertainty about price patterns and the trend’s continuation. An example of a low angle in trendlines is shown in Figure 4.6.

Source: Chart courtesy of StockCharts.com Figure 4.6: Low angle

This chart reveals a series of short-term trends, all but one moving upward as part of a primary bull trend. Over three years, price moved from a low of $31 per share up to as high as $45. Although the interim price patterns appear volatile, the chart is spaced in 1-point increments. A 3- or 4-point move looks extreme even when it is not. Over the

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entire period of this chart, support (represented by the dotted line) rose consistently. The short-term trends were applicable to swing trend activity or could be treated as secondary trends, but as a separate matter, support confirmed the bullish primary trend. Much less certain was the long-term trend for the next chart, shown in Figure 4.7.

Source: Chart courtesy of StockCharts.com Figure 4.7: High angle

This stock chart was priced in 2.5-point increments. Even though the price spread was not substantial, the short-term changes in price level and direction were steep. It was also consistent in the back-and-forth changes between uptrend and downtrend. Most lasted only two to three months. It appears that the moves marked by trendlines were secondary trends within a primary trend that was a consolidation not favoring either bullish or bearish direction. From start to finish the price ranged over 35 points, but the net change was only 15 points, not much movement over three years (from a starting price of $87.70 to an ending price of $72.50).

Internal Trendlines Trendlines cannot always be drawn to reflect an orderly and consistent trend. At times, reaction high and low prices spike outside of an otherwise recognizable trend. In these cases, an internal trendline may clarify what is occurring in the broader trend. Key Point: Short-term volatility obscures the current trend so that trendlines are not easily located.

This is a method in which the interim price spikes are ignored in favor of showing what is occurring in a sensible manner. For example, in Figure 4.8, several price spikes made it difficult to spot the secondary trends taking place. However, by ignor-

Validation of the Trend 

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ing those spikes the trendlines made the situation obvious. A series of three secondary trends (alternating between bullish and bearish) characterized this chart.

Source: Chart courtesy of StockCharts.com Figure 4.8:  Internal lines

Another interpretation of this pattern would be to call the first and third bullish trendlines part of a continuing bullish primary trend, with the middle bearish trendline marking a secondary trend. The price moved over three years from an initial low of approximately $29 per share up to a high approaching $42 per share. The internal trendline is appropriate only if the violations of the line are true spikes. A spike must be an aberration, meaning the price levels should return to the defined range rapidly. In statistics, removing the spikes from a field of values is recognized to reflect an accurate average of “typical” values. Including spikes distorts that field. The same applies in the use of internal trendlines. Strict adherence to the rule of the trendline (it begins at a clear point and ends when the slope of the line is violated) is applicable in many situations but is also inflexible when applied rigidly. This exception to the trendline rule should be used only when it clarifies the situation. In the example, ignoring the spikes helped to recognize the movement of price over time in a generally bullish long-term direction. This direction is clarified by identifying the rising level of resistance (broken line on the chart) over the entire period charted.

Validation of the Trend Not every chart makes it possible to draw a valid trendline. You need at least two connecting points, preferably uninterrupted by reaction high or low price moves, to call a price move a trendline, and more to the point, to use trendlines to spot a

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trend. A trendline is simply a range of price changes shown by the line itself, without running into an offsetting price direction. For Bollinger Bands, the trend is defined by upper and lower bands representing two standard deviations from the center band; but in the trendline, which is intended to validate the trend, the levels are defined by drawing straight lines from point to point and without running into a reversal in price. Three rules of validation also help in this task. First, the more price bottoms or tops that can be connected in a single line, the stronger the trendline and the greater its significance. When three or more price points are connected in a straight line, this represents advancing support (in an uptrend) or declining resistance (in a downtrend). Second, the greater the duration the trendline holds, the stronger the underlying trend. Third, angle counts in the trendline. An unbroken steep angle is a strong signal that a secondary trend is underway or, with equally strong confirmation, that a new primary trend has begun. Changes in scale and price increments will change the appearance and degree of volatility. The trendline exists only when the straight line can be drawn (under a rising trend or above a falling trend), but it cannot run into the price as price reverses. In drawing a trendline, a chartist can decide where to begin and end, but the most accurate versions will adhere to the rule that the line itself should be close to the evolving price level. This enables analysis of testing the trendline without violation. Key Point: Trendlines are validated by the number of times its border is tested without breakout.

Validation also applies to the number of times the trendline is tested without price moving through. This applies to uptrends as well as to downtrends. The stronger a trendline holds, the more it begins to act like rising support or falling resistance. The longer a trendline continues without price penetration, the stronger the trend. Applied rigidly, this should exclude internal trendlines as exceptions. Another form of validation occurs when a trendline is violated with repeated spikes, meaning the internal trendline is weakened by excessive spikes. When the frequency of spikes increases, they cease to be exceptions and the validity of the trendline must be questioned. This repetitive pattern might also forecast a change in direction rather than just an exception to an otherwise consistent trendline. When the trendline is less than clear, due perhaps to excessive spikes, one of the best confirmation tests is to include volume with the test of the trendline. If spikes are far apart and accompanied by volume spikes, but price returns to the level within the established trendline, it confirms its validity. However, when price persists in violating the trendline, it could mean that a reversal is underway when volume spikes recur just as often. Price gaps make this a near certainty.

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Retracement versus Reversal Retracement is a short-term price adjustment against the prevailing trend. The small change in price direction signifies nothing permanent, and retracement often works as a form of continuation signal. There are several ways to distinguish retracements form reversals. First, they are very short term, and price quickly resumes the prevailing trend. It is likely to test resistance or support without success. Finally, retracement tends to occur with little or no reversal signal. A reversal, in comparison, is forecast when a clear signal occurs and is confirmed. Flags and pennants are found at moments of retracement and represent price continuation. As short-term signals with sideways movement, these signals are useful for short-term price movement, notably retracement. A flag is a rectangular movement set up with resistance at the top and support at the bottom. A pennant is a triangle with a narrowing range culminating in top and bottom very close together in breadth. The pattern of flags and pennants appears in a direction opposite the prevailing trend, and then just as quickly, the pattern resumes. Although the concept of consolidation applies, some flags and pennants occur in patterns moving first in one direction and then in the other. In that sense, they may retrace a prior retracement, which is confusing and a signal of short-term volatility. Flags are parallel rectangular lines moving sharply away from the trend and may occur in rapid succession when the trend is undergoing a consolidation pattern. For example, Figure 4.9 reveals an extended consolidation pattern of two years after conclusion of a bullish trend, characterized by a series of flags.

Source: Chart courtesy of StockCharts.com Figure 4.9: Flags

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The initial bullish trend moved from $25 to $34 over a period of seven months, after which the consolidation began and continued for the next two and a half years. During this time, price ranged back and forth between $29 and $36, with retracement marked by a high volume of flags, retracing swing trends in both directions. Between May and December 2014, a set of upward price patterns retraced over and over, and price was not able to penetrate resistance. Key Point: Flags (rectangles) and pennants (triangles) are short-term patterns characterizing retracement patterns.

Pennants play a similar role to flags in retracement patterns, setting up symmetrical triangles of very short duration moving sideways or opposite the swing trend immediately preceding it. The chart in Figure 4.10 provides an example of this short-term retracement pattern.

Source: Chart courtesy of StockCharts.com Figure 4.10: Pennants

The symmetrical shape of pennants adds uncertainty to the current trend. This chart revealed an uptrend during most of 2012; however, the two years from 2013 to 2014 contained a narrow range moving sideways with strong support at $32.50 per share. The pennants appeared at, or immediately after, price made a very short-duration strong move. The pennants held price within the narrow range setting up an unusually long consolidation for this stock. Flags and pennants often are associated with strong dynamic trends. When the trend is moving, the flag or pennant works as a retracement. However, as the chart in Figure 4.10 reveals, these may also appear in long-term consolidation patterns.

Fibonacci Retracement 

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Fibonacci Retracement In identifying trendlines, retracement presents a problem. If short term, the retracement may be explained away with identification of flags or pennants and reaction high and low spikes can be ignored with the use of internal trendlines. However, longer-term retracement—lasting between one and three months—presents greater difficulty. It may easily be misidentified as a swing trend or even as a secondary trend due to its duration. One method for tracking these price patterns against the prevailing trend is with Fibonacci retracement analysis. Leonardo Fibonacci (1170–1250) was a mathematician who developed an observation of numerical patterns that came to be called the Fibonacci sequence. The sequence consists of the sum of the two preceding numbers in the count: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, etc. By itself, this is nothing more than a predictable mathematical sequence. However, upon further examination of the properties in this sequence, it can be used to make accurate predictions about statistical trends and, especially, about retracement. For example: 1. Any number in the sequence, divided by the previous number, equals approximately 1.618. This value, 1.618, is called the Golden Ratio and is found in art, biology, architecture, and nature. 2. Any number divided by the number that follows, equals approximately 0.618. 3. Any number in the sequence, divided by the value two places higher, equals approximately .382. Referring to the previous calculation, it is also true that 1 – 0.618 = .382. 4. Any number in the sequence divided by the value three places higher, equals approximately .236. These values or percentages often appear as the level of retracement after a price move. If a price moves several points and then retraces, it often will move in the opposite direction by 62 percent, 38 percent or 24 percent (rounding the outcomes above) of the initial price move. For example, Figure 4.11 provides a chart with examples of retracement between one and three months.

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69.00 64.00 60.25

62.50 59.00 56.00

49.00

Source: Chart courtesy of StockCharts.com Figure 4.11: Fibonacci retracement

The first instance is a move from $49 up to $60.25, or 11.25 points. It then declines to $56, or 4.25 points. When the retracement of 4.25 points is divided by the original move of 11.25 points, the result rounds up to 38 percent: 4.25 ÷ 11.25 = 37.7% The second instance begins at $56 and rises to $64, or 8.00 points. It then declines to $59, a drop of 5 points. When the retracement of 5 points is divided by the original move of 8 points, the result rounds down to 62: 5 ÷ 8 = 62.5% The third instance begins at the price of $59 and rises to $69, or 10 points. It then declines to $62.50, a drop of 6.5 points. When the retracement of 6.5 is divided by the original price move of 10, the result is 65, close to 62: 6.5 ÷ 10 = 65% These examples demonstrate a tendency for retracement greater than a few days to closely match the relationships of the Fibonacci sequence. At the time of analysis, it is difficult to decide where the retracement will conclude, and in some cases it will turn out to move more or less than one of the sequence values. A problem with this mathematical calculation of retracement is that by selecting the beginning and ending price levels, these may become self-fulfilling prophecies. It is difficult to rely on Fibonacci retracement to time trades with consistency and accuracy.

Channel Line Types 

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As a method for managing the trend (but not necessarily for timing trades), the Fibonacci sequence is a worthwhile indicator. In the chart, the overall three-year trend clearly is bullish, rising from $42 up to nearly $70 over three years with consistency—even though the periods of retracement are substantial and have durations that could represent secondary trades or even reversal of the primary trend itself. Key Point: Fibonacci retracement is useful for predicting a degree of price moves, but its usefulness is also limited.

One of the flaws in using Fibonacci retracement is that, with three possible markers, not to mention an additional 50 percent possible retracement also recognized as a significant price point, it is easy to make a case for the Fibonacci sequence as a certain indicator. In practice, it is difficult to spot in the moment of the retracement, and it serves as only one possible tool among many for identifying the condition of a current trend.

Channel Line Types While trendlines mark rising support in a rising breadth of trading and falling resistance in a falling breadth, channel lines further define a dynamic trend. When a trend moves in a bullish or bearish manner but maintains its breadth of trading, it is exceptional. The controlled volatility of such a move adds strength to the trend; it also provides a method for identifying when the trend is leveling out or likely to reverse. The channel lines consist of two parallel lines drawn above resistance and below support. The narrower the breadth and the longer the channel persists, the stronger the trend. Like trendlines, both channel lines are drawn at low and high points and are connected. For example, Figure 4.12 shows a rising channel lines formation lasting eighteen months. The breadth of trading was 15 points from high to low throughout this timeframe.

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Source: Chart courtesy of StockCharts.com Figure 4.12: Rising channel

The end of this uptrend was clearly marked at the beginning of February 2014 when the price declined sharply lower and broke through the lower channel (support). Even though price rallied back into the established range, the trend was over. Price began declining once again after a gap at the beginning of August and continued downward until mid-December. In this formation, the trend was apparent, and an analyst could assume with confidence that it would continue until a clear reversal signal emerged. The breakout below the lower channel was precisely this type of signal. Upon confirmation of the reversal from other signals, it was the time to adopt a bearish posture on this stock. The gap at the beginning of August 2014 was a compelling signal that warned of further declines, notably since very few visible gaps were found throughout the three-year period. A falling channel provides the same assurance in the opposite direction. Duration varies in all trends, but the channel lines provide a clear signal of prices trending in one direction for as long as the channel holds. An example of falling channel lines is seen in Figure 4.13.

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Source: Chart courtesy of StockCharts.com Figure 4.13: Falling channel

This chart shows two distinct bearish channels with volatile price patterns in between. Prices first moved sideways and then trended upward strongly, but quickly resumed the downtrend. In the first falling channel, which lasted nine months from the beginning of the period charted, the breadth of trading was about 5 points. Some isolated spikes broke through on either side but did not persist beyond single sessions. The second channel lines were also 5 points in breadth and lasted approximately ten months. Key Point: Channel lines may be drawn even with price moves violating the lines if those are only spikes and price retreats inside the channel.

In the first example, the downtrend ended with a bullish turn above the falling resistance marked by the upper channel. However, the second channel ended with further price decline below the falling level of support. A second interpretation of this falling channel would be to mark support three points lower and call it an 8-point breadth. This lower channel is stronger since it involves no breakouts; however, the starting point is not a precise low-price level. Even so, this demonstrates that channel lines can be manipulated to aid in visualizing a trend and in spotting potential reversal points. A flat channel example is shown in Figure 4.14. This chart contains two instances with a very brief upward price movement in between.

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Source: Chart courtesy of StockCharts.com Figure 4.14: Flat channel

The first consolidation pattern had a breadth of trading of just over 30 points and lasted for the entire year of 2012. The next three months trended upward, and the remaining period of over two and a half years revealed a duration of approximately 45 points. The price bounced back and forth between resistance and support during both flat channel periods, making this an excellent candidate for swing trading activity. For long-term analysis, more information would be required to determine the next direction for price. Channels are more than just merely interesting formations. They are useful for identifying emerging overbought or oversold conditions that point to forecast of reversal within the channel, which are pullbacks within the longer-term trend. They also may be tracked to identify likely points at which primary trends are ending and likely to reverse. Figure 4.12 provides an example of this in which a long-term bullish channel ended decisively, after which a downtrend followed. An investor with a long position in that company might have identified the violation of the lower channel line as the first signal that the trend was over and sell long positions to take profits. Key Point: Channel lines often highlight overbought or oversold conditions for in-channel price patterns.

A normal formation of channel lines is expected to eventually lead to reversal and channel lines are among the easiest to spot, since a clear violation of one of the two lines is easily detected. When the breakout is in the direction the channel lines are moving already, it could mean an expanded and accelerated trend, or it could forecast a reversal in the opposite direction. This would be the case if specific reversal signals were present, such as double tops or bottoms, head and shoulders; one of the many candlestick reversal patterns; volume spikes or indicators; moving average crossover; or momentum oscillators entering overbought or oversold condition.

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Expanding with the t-line The trend can be tracked with considerable accuracy when using Bollinger Bands in conjunction with the t-line. This signal is represented by an eight-day exponential moving average (EMA). Most online charting services allow you to set up automatic EMAs of any duration. Placing the t-line on a chart along with Bollinger Bands is simple. The t-line is based on a premise that crossover marks a change in trend direction. When the t-line is below price and crosses above, closing above for two days, it is a bullish reversal signal. When the t-line is above price and crosses below to close below for two days, it is a bearish signal. As far as it goes, the t-line is a tracking average, and is interesting but not entirely reliable. However, when it is added to Bollinger Bands as indicators on the chart, the combined signals become exceptionally reliable. On most charts, the t-line will appear as a solid line and of a color different than the three Bollinger Bands. An uptrend consists of the upper Bollinger bands serving as resistance and the t-line as support. A downtrend consists of the t-line as declining resistance and the lower Bollinger Bands as support. These two signals operating together tend to set up very narrow channels. Once price moves above a declining channel, it strongly indicates a bullish reversal. And once price moves below an advancing channel, it is an equally strong indication of a bearish reversal. For example, Figure 4.15 provides three examples of downtrends and reversals.

Source: Chart courtesy of StockCharts.com Figure 4.15: T-line with Bollinger Bands

In each case, the narrow channel is easily seen. The first lasted two weeks, the second one month, and the third two weeks. In each case, the t-line marked declining resistance and the lower band was declining support. In each case, the downtrend con-

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cluded when price moved above the t-line and closed there for two days. Price behavior in September and October foreshadowed the strong bullish trend that began in November and moved price 16 points to the upside. Some traders use a technique called t-line scalping. In this strategy, the t-line is combined with a twenty-day simply moving average. A position is opened once price establishes itself either above (bullish) or below (bearish) the t-line for two closes. The channel is defined in a way like that used for the more reliable Bollinger Bands method; however, this form of scalping is redundant since the middle band of Bollinger is a twenty-day moving average; the comparative indicator exists. However, basing the channel on the relationship between t-line and upper or lower bands (which are developed using standard deviation), provides a superior signal. The method using Bollinger Bands may be considered a form of t-line scalping but with more reliable signals. The t-line, like many indicators, is weak by itself and does not provide certainty about the change in trend direction. Most charts contain many false starts based on the t-line. As a result, most analysts give the t-line little attention. However, when placed on the chart with Bollinger Bands, it adds exceptional predictive benefits and highlights reversals effectively. This applies most accurately in swing trades, which is where traders are most likely to enter or exit positions. This is where the value is found in the t-line and Bollinger combination. One of the more challenging tasks for the analyst is distinguishing between swing trend reversals and secondary or primary trend reversals. The question of reversal identification for trends is the topic of the next chapter.

Endnotes

1 Friesen, Geoffrey C., Paul A. Weller, and Lee M. Dunham. “Price Trends and Patterns in Technical Analysis: A Theoretical and Empirical Examination.” Journal of Banking and Finance, 33, issue 6 (June 2009): 1089–100. 2 Lawrence, Ramon. “Using Neural Networks to Forecast Stock Market Prices.” University of Manitoba, Department of Computer Science (December 1997), p. 5.

Chapter 5 Reversal Patterns: End of the Trend The confirmation of primary trends in the Dow Jones Industrial Average (DJIA), obtained by tracking other Dow Jones indexes, is far from clear. A turn in price is controversial, and there is no universal agreement about whether a reversal is a secondary trend or a new primary trend. The same problem is found in tracking individual stocks. When does a primary trend end and how do you spot it? This is the core problem of trend analysis. A reversal may represent a new direction for the stock for coming months or years. It may also be a secondary trend, with the primary trend in effect for the longer term. It could be a swing trend that will last only a few days, or merely a retracement. Key Point: A reversal can have numerous interpretations. Therefore, trend analysis depends on insight and strong confirmation.

This chapter explores many different types of reversals and their attributes and provides a starting point for identification of what price patterns mean in the larger context of the trend. It explains many of the configurations of Western or Eastern reversals and explores some of the more reliable and frequently occurring signals. While swing traders can focus on the very short-term signal and its confirmation, how do investors apply reversal indicators to spot primary and secondary trend activity? The answer may be found not only in single or double signals, but in the occurrence of numerous signals in the same timeframe. This chapter explains many of the most frequently seen reversals: –– Head and shoulders –– Inverse head and shoulders –– Gaps –– Rounding top and bottom –– Rectangle top and bottom –– Double top and bottom –– Diamond formation –– Long white and black candlesticks –– Dragonfly doji –– Gravestone doji –– Hammer and hanging man –– Inverted hammer –– Engulfing pattern –– Harami and harami cross –– Doji star DOI 10.1515/9781547401086-005

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Piercing lines Meeting lines Three white soldiers and three black crows Morning and evening stars Abandoned baby Squeeze alert

The Dilemma: Minor or Major Reversal Investors tracking prices on charts have many tools available for determining whether a trend is continuing or growing weaker. For example, the use of trendlines and channel lines, Bollinger Bands and other statistical tests, and observations of price in proximity to resistance and support, all help to spot a trend’s longer-term health and strength. Once the price activity diverts from an orderly and identified trend, it is likely to signal a coming change. That may be represented by a period of consolidation or outright change in a trend’s direction. Trendlines and channel lines track the direction and duration of the trend and set up a disciplined and predictable course—until it all changes. Once the trendlines are stopped or channel lines break down, it is time to consider the possibility that the trend is about to conclude. One of the most significant changes occurs not only when price violates the rising or falling breadth established by channel lines, but also when the breadth of trading expands rapidly. A broadening breadth of trading, the visualization of growing volatility, signals the potential for the struggle between buyers and sellers to exhaust the current trend. When resistance or support lines are broken, price behavior also provides insight. As discussed earlier, one of the strongest signals of a new direction in the trend is the flip of resistance to support (on the upside) or from support to resistance (on the downside). This flip sets up exceptionally strong new borders to the trading range even with higher volatility. Price behavior at or through these lines signals a high likelihood of a change in the trend’s direction. Key Point: The flip between resistance and support is a compelling signal that also adds strength to a revised trading range.

Price gaps occurring at resistance or support are strong signals of reversal, if only to the extent that price will return to the previously defined trading range. However, price gaps may also occur when the trend is accelerating to higher momentum or when reversal will take place not only into range, but through the range and in the other direction. Resistance and support are the price points where longer-term trends are most likely to face challenges and where reversal is at its most likely point. This proximity is worth noting. Most reversals will be strongest when they occur at resis-

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tance or support, especially if price has gapped through those trading range borders. Proximity marks the most likely timing and placement of reversal. Signals, confirmed with Bollinger Bands, added candlesticks, double tops or bottoms, or many other signals, add to confidence that reversal is more likely than average.

Reversal versus Consolidation Observing that reversal is somewhat predictable based on the broader markets, where a starting point in analysis can be developed. Many stocks follow the index-based market represented by the DJIA, S&P 500, and NASDAQ, for example. Stock reversal should take into account the condition of the market. Even so, it is not safe to assume that a specific stock is undergoing reversal merely because the overall market appears to be doing so. The interpretation of index movement is flawed for many reasons, including the distortions that index calculations cause. Due to weighting of stocks in the DJIA, for example, three companies (Boeing, UnitedHealth Group, 3M) account for more than 21 percent of the DJIA movement (as of January 2019). This makes it difficult to apply index-based mood of the market to any one stock, with consistent reliability.1 Clearly, if a majority of stocks are down for a day or a week, the short list of positive-moving stocks should be noted. It means that either those are exceptionally strong companies, or that it is just a matter of how the average work out—some stocks rise and some fall. Market behavior has so many variables that it is not easy to estimate where individual stocks or averages are going to move next. This becomes more difficult considering that reversal and retracement might look the same when they first appear. Accurate interpretation is a constant challenge in distinguishing between a reversal and retracement. When a trend comes to an end, it may reverse with immediate speed, turn out to be only a retracement or swing trend, or may move into a period of consolidation. This sideways-moving period of consolidation may not be short term but could last a year or longer. During consolidation, it is most difficult to interpret price activity due to the lack of indicators. Without a dynamic trend in effect, there is nothing to reverse in terms of price direction; a reversal signal cannot be called in the same way as during bullish or bearish movements. Resistance and support are likely to be flat, perhaps for an extended period, meaning that no breakouts occur; or if they do, interpreting their meaning in terms of a possible trend is quite difficult. In periods of consolidation, investors are forced into a wait-and-see period if only because the price levels are range-bound. You must look for signals of a true breakout and establishment of a new trend. At some point, either buyers or sellers will emerge in control, and recognizing this moment is key to also recognizing the start of a new trend. However, in recog-

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nizing consolidation as one form of trend, a trend reversal (versus a price reversal) is possible, with consolidation reversing into either bullish or bearish movement. When a pattern emerges that looks like reversal and does not follow through but pauses and contradicts what the indicators forecast, it might turn out to be a consolidation rather than immediate reversal. In virtually any reversal pattern it is an error to expect immediate price movement. Although immediate movement frequently does occur, it is not a certainty. Relying on weak indicators, or those with more than one interpretation, also adds to the uncertainty of how price acts during what appears to be a reversal. In traditional Western technical analysis, a symmetrical triangle, for example, may be bullish or bearish making it of dubious value in confirming reversal. In candlestick analysis, a long-legged doji or spinning top also are unclear in their meaning. They may be bullish or bearish depending on (a) where they appear in a trend and (b) other signals and what they forecast. Key Point: Response to a reversal signal is not always immediate. Even with strong confirmation, a delay is not uncommon.

An example of an apparently strong reversal signal and confirmation that did not lead to actual reversal is seen in Figure 5.1.

gap breakout

resistance

spike

spike

Source: Chart courtesy of StockCharts.com Figure 5.1: Delayed reversal response

At the beginning of this chart, the stock price was ranging between $8 and $11 per share. However, during the preceding year, the price had been as high as $17 per share.

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A downtrend had occurred prior to the period shown. The downward-moving gap accompanied by a volume spike marked what could be interpreted as a point of reversal. Once the price held strongly at just below $8 per share, even when tested between May and August 2012, it would have been reasonable to expect a bullish reversal. However, the price moved into a consolidation pattern that lasted eighteen months. Only in December 2013 did the price break out above resistance and move higher. The breakout was confirmed a month later in January 2014 with a strong volume spike. The bull trend moved rapidly higher to more than $17 per share, doubling share value in less than one year. This chart provides an example of a delayed reaction for an extended period of consolidation. In this example, eighteen months passed before the forecast reversal occurred. This demonstrates that an immediate reaction after a reversal signal does not always occur as expected, or may not occur at all.

The Time Element: Momentum of Reversal Another question investors must ask is what to expect after a long period of consolidation. Will the eventual reversal be strong or weak? How long will a new trend last? A desirable answer would be that the characteristics of consolidation dictate the size, shape, and duration of the trend that does follow. Unfortunately, that is not the case. However, momentum is expressed in the deferred reversal, eventually. In the case of the chart in Figure 5.1, the exceptionally long consolidation led to a strong uptrend. To some degree, this range-bound period might have influenced the new trend and might have gathered a high number of interested buyers. However, even in hindsight it is impossible to quantify the role of consolidation in the strength of the new trend. In analyzing dynamic (bullish or bearish) trends, the momentum of an original trend is most likely to affect the momentum of a reversal. However, in consolidation, because price is limited to a small trading range, it has no momentum until a breakout occurs and a new, dynamic trends begins. For this reason, the pattern and duration of consolidation cannot be judged in terms of how it affects the new trend that follows. Some consolidation leads to bullish trends, others to bearish trends. A third group replaces one trading range of momentum with a higher or lower range of momentum. Investors must rely on the reversal itself to judge not only when a trend will begin but how strongly it will behave. For example, referring once again to Figure 5.1, there are some clues anticipating the breakout in December 2013. First was the spike in late October, occurring as price bounced off the low in what could be considered the final line of a W bottom. This forecast a rise; however, several previous signals appearing like W bottom formations occurred during consolidation. Like many examples of range-bound price movement, there were no clear signals anticipating the successful bullish move. This was a case of hindsight rather than of forecasting insight.

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Reversal in Western Patterns In periods of consolidation, just like all moments in a stock chart, you must rely on the strength of reversal signals and confirmation from secondary signals. The Western technical signals used by so many traders can be used by long-term investors as well. However, knowing which signals are applicable to swing trends and which are applicable to primary or secondary trends, is a considerable challenge. You need to rely on how compelling a set of signals is before deciding that a primary or secondary trend is reversing. The likely reversal points often depend on proximity to resistance and support, the points where reversal is most likely. Key Point: Reversal can occur at any point in the current trend, although at resistance or support the chances of successful reversal are far greater.

Head and Shoulders One of the best known reversal patterns is the head and shoulders. The concept in this pattern is that it tests resistance and, upon failing to break through successfully, price will then retreat in the opposite direction. The bottom of the three attempted breakouts is called the neckline, which serves as a form of interim support. Once price moves below the neckline, the bearish formation of the head and shoulders is confirmed and the price is likely to continue falling. For example, in Figure 5.2, two examples of head and shoulders were revealed, both with clear neckline price levels and both followed by a price decline. The first of the two head and shoulders formations spanned two months and the second spanned four months. Some head and shoulders patterns occur quickly and are more typical of bearish signals within swing trends. When a pattern takes a longer time to develop, it is more likely to present a bearish secondary trend.

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neckline neckline

Source: Chart courtesy of StockCharts.com Figure 5.2: Head and shoulders

This chart appears to be in a long-term bullish trend from a price around $52.50 at the beginning of 2012, up to $85 by the end of 2014. However, in between were two secondary trends, both marked by the head and shoulders patterns shown on the chart. The first secondary trend lasted nine months and ended in January 2013 and the second started near the beginning of 2014 and lasted more than ten months, ending in October before prices began a 30-point bullish move in the last three months of 2014. Key Point: A head and shoulders is a strong reversal signal, but it is easily misinterpreted or overlooked.

The same pattern occurs on the opposite side on the trading range. An inverse head and shoulders (also called a head and shoulders bottom) takes place as a test of support and forecasts a new bullish trend. Like all reversals, it should be confirmed by additional patterns or indicators. Figure 5.3 shows an inverse head and shoulders developing over six months.

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prior resistance new support

Source: Chart courtesy of StockCharts.com Figure 5.3: Inverse head and shoulders

The time required for this pattern to emerge indicates that it is part of a primary trend reversal. The stock peaked above $43 in March 2011 before the period shown and then declined to about $37 per share, where a new resistance level is noted on the chart. This also serves as the neckline for the inverse head and shoulders. Assuming support was at about $31 per share while this pattern emerged, the head, dipping below to $28, was a failed breakout. When this occurs as part of the inverse head and shoulders, a new bullish move is expected. Key Point: An inverse head and shoulders is subject to the same rules as its bearish counterpart, but it appears at the bottom of a downtrend and is bullish.

In this case, the bullish move occurred and quickly rose above the $37 neckline and resistance. Confirming the new bullish trend and adding strength to the bullish breakout was a flip from prior resistance to set up new support. The new support level was tested over the next year, without any serious breakouts. The activity throughout this chart was typical of the inverse head and shoulders: a failed breakout below support followed by a strong bullish rise in price breaking out above resistance and remaining there. In this case, the new support level held for the remainder of the period shown and held for several months beyond.

Gaps Another familiar formation in Western technical analysis is the gap. This is by no means a rare pattern; gaps are found often on stock charts and come in many forms. First is the common gap, which offers no significance to interpreting the price chart. One test of a common gap is to see how quickly it gets filled (meaning price

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retreats to cover the range of prices represented in the gap). It is often the case that common gaps are filled immediately or very quickly. A gap with greater meaning is called the breakaway gap because it sets up a move in price outside of the established trading range. When this occurs in a direction opposite the prevailing trend, it could be a strong reversal signal. However, because the price breaks through resistance or support with gapping action, reversal is more likely than at other points in the price pattern. The breakaway gap may also occur within a primary trend and may even set up an accelerating move within that trend. This is especially true when the gap sets up a flip from resistance to support (bullish rise) or from support to resistance (bearish decline). An example of this price pattern is seen in Figure 5.4.

breakaway gap

new

prior

ort

supp

nce

resista

Source: Chart courtesy of StockCharts.com Figure 5.4: Gaps

The gap shown in Figure 5.4 spanned 9 points and moved strongly above resistance. It was confirmed when the resulting decline failed and price continued upward. Prior resistance became new support in this case, with the trend clearly marked by the line of resistance/support and augmented by the strong price gap. While this pattern is unusual, it should not be ignored. It adds strength to an already rising trend and moves the breadth of trading into new territory. The breadth before the gap was approximately 4 points even as the price levels rose. After the gap and establishment of a higher trading range, breadth of trading fell to 2 points or less. While this could be viewed as a sign of a weakening trend, a broadening gap would be more troubling. In this example, even though prices were rising dramatically throughout the chart, volatility (as measured by breadth of trading) declined. However, the decline occurring between December 8 and December 22 approached rising support and anticipated a slowing down of the trend’s curve. During the first quarter of 2015 (beyond the charted period) price leveled out and settled in around $94 per share,

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a good indicator that this primary trend could have exhausted or was beginning to exhaust after rising 20 points over three years. Another type is the runaway gap that is caused by growing interest among buyers (on the upside) or sellers (on the downside). The enthusiasm revealed in the pattern could lead to an equally strong and even accelerated reversal. It is characterized by a series of repetitive gaps in a short period of time, with prices spiking upward or downward as a result. Key Point: Gaps indicate growing interest among buyers (upside) or sellers (downside), but also set up a volatile environment for the trend.

The last type is called an exhaustion gap. This is found near the end of a trend and signifies a coming reversal. It is identified by accompanied high volume and is likely to be found at (or moving through) resistance (in a bullish trend) or support (in a bearish trend). Proximity to these all-important price points is a strong signal. However, the exhaustion gap also needs confirmation from other signals beyond the volume spike. A change in a momentum oscillator adds convincing confirmation. A move into overbought territory anticipates a strong bearish reversal and a move into oversold anticipates a strong bullish reversal. The combined occurrence of an exhaustion gap, a breakout above resistance or below support, a volume spike, and a momentum signal, provide one of the strongest combination reversal forecasts possible.

Rounding Top and Bottom Besides the spiking prices associated with head and shoulders and gaps, some trends are found in a softer rounding effect. The rounding top or bottom mark a potential reversal but without the clear spiking price points expected in so many types of signals. A rounding top is most convincing as a signal of reversal when it “rounds” higher than resistance. In such a case, you expect to see price retreat to the downside in a new bear market. An example is found in Figure 5.5.

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resistance

Source: Chart courtesy of StockCharts.com Figure 5.5: Rounding top

Unlike the heads and shoulders with its fast-moving and spiking prices, the rounding top evolves in a less volatile manner. In this example, resistance was on the rise with some considerable volatility in the trading range. The rounded move took price through resistance and then retreated strongly. This resembles a double top; however, most analysts expect to see the top spikes in more dramatic contrast to prices immediately before and after. The decline in price following the rounding pattern was confirmed by the accelerated movement as well as the downward-moving gap in mid-April. Key Point: Rounding tops and bottoms are like spikes but without the accent on one or two sessions.

A rounding bottom has similar tendencies for less volatile contrast between prior prices and the turn in the trend. Figure 5.6 shows a rounding bottom formation.

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support

Source: Chart courtesy of StockCharts.com Figure 5.6: Rounding bottom

This stock had traded as high as $65 per share the year before, so this chart began near the conclusion of a strong downtrend. The spike in the middle of the rounding activity tested support and failed, and after this price began trending upward in a new primary trend lasting at least to September 2014, a span of two years. The price gap in October 2012 marked the beginning of the new uptrend, quickly followed by an initial climb of more than 20 points between November 2012 and February 2013, only three months.

Rectangle Top and Bottom A similar pattern is found in the rectangle top and bottom patterns. These are high or low trading ranges marked by ranges of price rather than by specific price points. The rectangle may also be marked by price gaps on both sides or by strong price moves. An example of a rectangle top is shown in Figure 5.7. Note the similarities in these formations. In the first, the beginning and ending points were marked by gaps; in the second, prices moved steeply before and after the rectangle.

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Source: Chart courtesy of StockCharts.com Figure 5.7: Rectangle top

The rectangles could be treated as marking resistance on their top, in which case the double top formed in May and August 2013 represent failed breakouts. However, if the assumption is that resistance was more likely at $165, the rectangles are failed breakouts on either side on the double tops. Key Point: Rectangle formations are yet another form of reversal signal, but they consist of a range of sessions rather than on one or two session spikes.

A rectangle bottom presents the same interesting interpretive data. In Figure 5.8, a rectangle bottom precedes a strong bullish trend.

Source: Chart courtesy of StockCharts.com Figure 5.8: Rectangle bottom

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In this instance, the first rectangle lasted for ten months and the second for four months. These are by no means short-term reversal signals; they are more likely to be breakouts below support forming secondary trends against a primary bullish trend. That primary trend began at the very beginning of the chart, when price was beneath $27. The three-year trend moved price to over $40 before retreating by the end of the period charted. In this interpretation, support would reside at about $29.70, marked by the broken line on the chart. Both rectangle bottom formations were secondary trends or, rather, secondary consolidation periods. They did not move upward or downward but remained range-bound until the final breakout in mid-November marked by the price gap. What followed was a resumption of the previous primary uptrend.

Double Top and Bottom The next formation is one often found, cited, and relied upon to spot reversals. The double top and double bottom are a set of price spikes near one another. When these are found at or close to resistance (double tops) or support (double bottoms), the likelihood of reversal is high. However, the definition of “close proximity” is far from clear. The two spikes might be found in consecutive sessions or they might be a month apart. Proximity is a relative term. When looking at a one-month chart, a spike near the beginning and another near the end could hardly be thought to be related. However, when looking at a three-year chart, the one-month separation is not as exclusionary. In this case, the two spikes are clearly associated, assuming that (a) they are in proximity to resistance or support or better yet, move through those boundaries; (b) price retreats immediately and begins moving in the opposite direction; and (c) price does not eventually succeed in breaking out but returns into range or sets up a trend in the opposite direction. Key Point: Double tops and bottoms occur often, but when found at or near resistance or support, they indicate a strong chance for reversal.

An example of the double top is found in Figure 5.9. All the requirements for a double top were met.

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Source: Chart courtesy of StockCharts.com Figure 5.9: Double top

The resistance on this chart is identified at approximately $43 per share. This is based on price holding there except for the two double top movements. The first set was separated by one month and the second by less than one week. However, once the resistance line is drawn, the significance of the failed double tops becomes clear. The double tops in this example moved through resistance, retreated immediately, and did not eventually return to break through. In some cases, double tops or bottoms do not require two sets to confirm the failed breakout. The formation on its own is a strong one, and if confirmed by other price patterns, volume spikes, or momentum oscillators, can demonstrate a strong reversal and establishment of a new trend. For example, the chart in Figure 5.10 provides a look at a double bottom that leads immediately to the expected bullish reversal and the establishment of a new primary trend. This new trend lasted at least two and a half years until the end of the period charted.

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Source: Chart courtesy of StockCharts.com Figure 5.10: Double bottom

In this case, the definition of “close proximity” again comes into play. The two bottom spikes were nearly two months apart and yet they marked the bottom of the downtrend and began the beginning of a new primary bullish trend. If this were a threemonth chart, the two spikes would not be acknowledged as relating to one another. So, “close” proximity is a relative term. This proximity issue also demonstrates that shorter-term charts may not be especially effective for recognizing long-term trends and when or where they reverse direction. Expanding on double tops and bottoms is the stronger version—triple top or bottom—consisting of three spiking price sessions at the top of a trend (signaling bearish reversal) or at the bottom of a trend (signaling bullish reversal).

Diamond Formations In some reversals located at proximity to resistance or support, the rounding, double, or rectangle formations form a diamond shape. The resulting diamond formation is noticeable by its V-shaped neckline. An example is shown in Figure 5.11, with necklines marked with a broken line. The diamond tends to appear at or near reversals of primary trends, just as these do, both for bottom and top diamond formations.

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Source: Chart courtesy of StockCharts.com Figure 5.11: Diamond formation

The diamond tends to take time to fully develop. The example includes a diamond bottom spanning five months and a diamond top over four months. In between was a primary bullish trend spanning nearly two full years. The uptrend was volatile with price gaps before and after a large price decline of one month and a series of runaway gaps ending with a large price spike. Both bottom and top also could be interpreted as symmetrical triangles. These may be bullish or bearish depending on where they appear. In this case, the diamond formation, like the symmetrical triangle, appeared at the end of each trend, strongly forecasting reversal. A problem with this observation is that it is clear in hindsight, but at the time it forms the meaning is not as obvious. Key Point: Diamond formations are variations on the rectangle and may occur often. However, their meaning depends on where they are found.

Triangles and wedges (both described in Chapter 3) may provide false signals and often are so close to one another that in shape that they can be confusing. The ascending triangle and falling wedge are considered bullish and both descending triangle and rising wedge are bearish. Because both triangles and wedges form when there is a narrowing breadth of trading, they can have contrary meaning more often than most signals. A diamond should be treated as part of the price pattern for reversal of a primary trend while triangles and wedges might be viewed with greater caution.

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Reversal in Eastern Patterns In addition to the many Western reversal signals, Eastern signals (candlesticks) also signal reversal. Like the Western patterns, candlesticks have the strongest predictive power when appearing at resistance or support and after particularly strong trends: Analysis based on candlestick patterns enhances an investor’s ability to prepare for trend changes. Being familiar with the psychology behind specific candle formations provides immense advantages. Candle signals can identify a trend reversal in one day. More often, the Candlestick signals can forewarn when a trend is preparing to change.2 The art of candlestick analysis is not complex but it does involve analysis of dozens of different candlesticks, both reversal and continuation patterns. Some indicators are stronger than others, so it also pays to be aware of a short list of signals offering the most value as signals and confirmation for reversal. Key Point: Strong candlesticks support likely reversal with exceptional reliability. However, not all candlestick indicators are strong; some only provide a 50 percent chance of success. Thus, using only candlesticks with higher success rates makes sense.

The reversal signal, whether Western or Eastern, works for all types of trends. Swing traders may time their trades based on candlesticks and other indicators and improve their effectiveness in generating profits. For longer-term trends, candlestick signals work with other price and volume indicators to warn investors about weakening trends or outright reversal about to occur. No system provides 100 percent confidence, but combining candlestick analysis with other forms of technical analysis improves your awareness of the trend and its status.

Long Candles One of the most recognizable of all candlestick signals is the single-session long candle. This is a session with a larger than average distance between opening and closing. The candlestick consists of a rectangle, which is called the real body. The bottom of the white candlestick’s real body is the opening price for that session, the top is the closing price. This is an upward-moving day. On a black candlestick (a downward-moving day), the opening price is the top horizontal line and the closing price is the bottom. The color distinctions make a chart easier to read, and finding long candlesticks is easy because they stick out. However, “long” is a relative term. A chart with 1-point scaling could report a long day with a 3-point move versus typical moves under .5 point. For a chart scaled in 10-point increments, “long” would have to consist of many

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more points. A long session compares a typical length of a day’s breadth to exceptionally expanded breadth and not to a fixed number of points. Key Point: A long candlestick refers to breadth between opening and closing price; however, depending on scaling, the number of points is not as important as the session’s breadth compared to other sessions before and after.

A long white session is bullish and a long black is bearish. When these appear in proximity to support (white) or resistance (black), they work as reversal signals. Assuming confirmation is located at the same time; the long candlestick is a strong and easily recognized signal. For example, Figure 5.12 provides clear examples of how long candlesticks appear at crucial points in trends and their reversals.

long white

Source: Chart courtesy of StockCharts.com Figure 5.12: Long candlesticks

The support level on this chart is difficult to determine because the overall trend appears to be bearish but the low levels of trading are extremely short in nature. Both support and resistance are set for limited times with volatile change in between. So even with a primary trend gradually declining, secondary trends or swing trends appear to take place over a matter of only a few months. One is found in the last two weeks of August, another in the second half of October, and a final one in the second half of December. In the last two swing trends the beginning of reversal was marked by long white candlesticks. These long sessions are remarkable due to their breadth. As resistance declines over the six months of this chart from a high of $44.50 down to the ending price of $42, support is less identifiable. The price range is not great but the interim volatility makes this stock a good candidate for swing trading. The key element of the short-term reversal is the long white candlestick. A more detailed analysis of the

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candlestick indicators on this chart reveals many confirming signals; and adding in volume and momentum signals further clarifies the strength and duration of the swing trends. The “anchor” to the turn in direction is the long white candle session. The long black candlestick session holds the same level of importance, notably when it appears at the top of an uptrend and approaches or violates resistance. In both cases, when a long candlestick appears in the wrong place (white during an uptrend or black during a downtrend) it does not represent a signal of any importance. Some candlestick analysts have made a case for treating reversal candlesticks as continuation signals when they appear in the wrong proximity; however, this is questionable as a signal of value. A confirmation signal should appear near a breakout above resistance or below support. Long candlesticks are easy to understand and to spot. They indicate movement in the direction of the candle (white is bullish, black is bearish). Finding these at the proper proximity in a trend provides a good starting point for identifying reversal for trends of all types.

Doji Formations The long candlestick is easily spotted merely due to its size. A more difficult session to spot is the doji, Japanese term that means “mistake.” This is a session with little or no real body resulting from opening and closing price being at the same level. Instead of a rectangular real body, the doji reveals only a horizontal line. Key Point: A doji consists of opening and closing prices at about the same price, forming a horizontal line in place of a rectangular real body.

The doji comes in several variations. Among these are the bullish dragonfly, the bearish gravestone, and the long-legged doji and spinning top (both either bullish or bearish depending on the context in which the session is located). These are all summarized in Figure 5.13.

dragonfly (bullish)

gravestone (bearish)

long-legged (context)

spinning top (context)

Source: Prepared by the author Figure 5.13: Doji types

The long shadows on dragonfly and gravestone reveal why they are bullish or bearish. The shadow reveals the extent of trading range during a session beyond opening

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and closing prices. On the dragonfly, selling activity is expected to move far below the opening price, but sellers might not be able to move the price lower, returning it to the opening level by the close. The gravestone is the opposite; buying activity is represented in the long upper shadow, but buyers might not be able to maintain a higher price and the session would retreat to the opening level by the close. These long shadows reveal weakness in the direction they occur. On both the long-legged and spinning top sessions, significance relies on where it is found. Either of these found at support or resistance can add to a likelihood of reversal if other reversal signals are also present. The lack of any open-to-close range on the long-legged doji and the very small range on the spinning top are only half of the meaning in these signals. The upper and lower shadows reveal a struggle for control between buyers and sellers. Ultimately, the winner is revealed in the direction that price ends up moving. Therefore, as a confirming signal for reversal, when these are found at (or moving through) resistance or support, they are compelling signals of coming reversal. By themselves, these are not strong enough to enter a trade, but with other reversal signals they provide good confirmation.

Hammer and Hanging Man Among single-session candlesticks, the hammer and hanging man are unusual. They have the same attributes and formation but are diametrically opposed signals depending on where they appear. This signal consists of a small real body and a lower shadow that extends farther than the range of the real body. The real body may be either white or black. When this appears at the top of an uptrend, it signals a reversal to the downside and is called a hanging man. When it appears at the bottom of a downtrend, it signals a reversal to the upside and is called a hammer. As with all indicators, these should also be independently confirmed by other candlesticks, Western signals, volume, moving averages, or momentum oscillators. They also apply in all types of trends: swing, secondary, or primary. An example of the hammer and hanging man is shown in Figure 5.14.

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hanging man

hammer

Source: Chart courtesy of StockCharts.com Figure 5.14: Hammer and hanging man

In the hanging man, the second occurrence confirms the first and immediately results in a one-month downtrend. The hammer appeared at the bottom of the next downtrend and led to a two-month uptrend. Key Point: Hammers and hanging man sessions have the same features and may have real body that is either white or black. They are found at resistance or support and strongly forecast reversal.

A closely related signal is the inverted hammer. Although called a hammer like the bullish variety, the inverted hammer may be bullish or bearish. The bullish version is shown in Figure 5.15.

Source: Chart courtesy of StockCharts.com Figure 5.15: Inverted hammer

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Inversion of signals adds confusion to the pattern. Unlike the “regular” hammer, the inverted hammer requires two sessions. In the bullish version, like the one shown in the chart, a black session is followed by a downward gap and then an inverted hammer. It contains a small real body of either color and an upper shadow. This forecasts a reversal and uptrend. In the bearish version of the inverted hammer, a white session is followed by an upside gap and then a hammer session containing a small real body of either color and an upper shadow at least the height of the real body, often more. The longer the upper shadow, the stronger the indicated reversal.

Engulfing Pattern Among two-session indicators, the engulfing pattern is one of the strongest. It is found often in charts and when confirmed is a valuable and strong reversal signal. The bullish version consists of a black session followed by a longer white session. The real body of the second session extends both higher and lower than the preceding black session (engulfing it). An example of the bullish engulfing pattern is shown in Figure 5.16.

support bullish engulfing

Source: Chart courtesy of StockCharts.com Figure 5.16: Engulfing pattern

Price gaps strongly upward right after the engulfing appears. This sets up a strong rally that returns price into the previously established range. An estimate of support throughout the chart is at $73.50. If this is recognized as true support, the four sessions dipping below that level culminate with the bullish engulfing and create a failed breakout below support.

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Key Point: The engulfing pattern occurs often and is among the strongest of reversal candlesticks. It should be located at proximity to resistance (bearish) or support (bullish).

A bearish engulfing pattern contains a white session and immediately after a larger black session. With both types, the shorter the first session and the longer the second, the stronger the signal. In the bullish version shown in the chart in Figure 5.16, the engulfing was exceptionally strong and led to a strong and rapid rebound. All patterns can fail, but when the size and shape of sessions within a pattern are minimal, failure is more likely. So a two-day engulfing that barely meets the pattern requirement will not be as strong as one with stronger contrast from day one to day two. An engulfing pattern with sessions close in size, appearing after a weak trend, is likely to either fail outright or lead to a slow or minimal reversal. When a strong engulfing pattern is found at the top of an uptrend or at the bottom of a downtrend, reversal is very likely. This is especially true when the pattern is right at the borders of the trading range or moves through it. In the chart shown in Figure 5.16, the bullish engulfing appeared after price violated support. This is the most likely timing for reversal, and the engulfing is one of the strongest of reversal signals; the bullish response was not surprising.

Harami and Harami Cross The opposite of the engulfing is the harami pattern. In Japanese, harami means “pregnant.” This is not as strong as the engulfing as a reversal, but when found in the right proximity and confirmed by other signals, it provides reliable confirmation of the reversal forecast. A bullish harami consists of a black session followed by a smaller white session. The first session is higher and lower in range than the white session, creating the shape of the typical harami. A bearish harami is the opposite. It is a white session followed by a smaller black session. It should appear at the top of an uptrend to work as part of a forecast for bearish reversal. Key Point: A harami is opposite in design from the engulfing. It also signals reversal but is not as strong as the engulfing pattern.

The harami cross is like the harami, but the second session forms a “cross” shape, representing a doji session. The bullish harami cross consists of a black session followed by the doji (cross), and the bearish harami contains a white session followed by the doji. An example of the bullish harami and the bearish harami cross is found in the chart in Figure 5.17.

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bearish harami cross

bullish harami

Source: Chart courtesy of StockCharts.com Figure 5.17: Harami pattern

The bullish harami appeared right at the bottom of a three and a half-month downtrend, marking the end of the trend and coming reversal. A month later, the bearish harami cross forecast a downtrend, which came only after a three-week delay. As with many signals, reversal did not occur immediately after the appearance of a price pattern indicator. The harami and harami cross often are found at the right proximity to create or confirm reversal. A bullish signal is likely to be found after a downtrend and a bearish signal after an uptrend. When these appear elsewhere within a trend, they should not be considered as having any special meaning. For reversal to be valid, there must be a trend to reverse.

Doji Star Another two-session reversal signal is the doji-star. The bullish version starts out with a black session, then a downside gap, and a doji. This should be located at the bottom of a downtrend and, when confirmed, signals a coming reversal and uptrend. Key Point: The doji star consists of two sessions separated by a gap in between. It is a strong reversal indicator due to the gap.

The bearish version starts out with a white session, then an upside gap, and a doji. Look for this reversal signal at the top of an uptrend, which signals reversal and a new downtrend. Both varieties of this signal are highlighted in Figure 5.18.

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bullish bearish

Source: Chart courtesy of StockCharts.com Figure 5.18: Doji star

The chart in Figure 5.18 tested support twice before rising from a low under $80 to an ending high at about $96. The bullish doji star foretold the bottom of the downtrend; and the bearish doji star near the end of the chart signaled a coming downtrend. However, the following period continued the consolidation pattern that started in late November. This one was difficult to call since no compelling long-term trend appeared to be in effect. The previous period, from 2012 through 2014, was a primary bull market, with the price moving from $45 to $95. The period following, the start of 2015, could be a pause for consolidation with renewed bullish movement starting in February 2015.

Piercing and Meeting Lines The next set of patterns is found often in charts. The piercing lines and meeting lines are useful reversal signals, but they should be confirmed before deciding to act. The bullish piercing lines begin with a black session and then a white session. The white session gaps lower to open below the prior close and then closes within the range of the previous day’s real body. The bearish version opens with a white session, gaps to open higher with the second day declining to close within the range of the first day’s real body. The chart in Figure 5.19 contains examples of both bullish and bearish piercing lines.

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bullish

bearish

Source: Chart courtesy of StockCharts.com Figure 5.19: Piercing lines

These are interesting patterns. The occurrence of two sets of each of these provides initial reversal forecast and then confirmation. The bullish example tests support and predictably leads to an uptrend. The two bearish piercing lines exceed the rising line of resistance and then decline rapidly to test support once again before returning to an uptrend. Overall, the chart appears to represent a long-term primary bull trend starting out in the mid-50 range and climbing above $60 per share six months later. Key Point: Piercing and meeting lines are found often on price charts but should be confirmed before trades are entered.

The meeting lines signal is similar with an important exception. The second session closes at the same price as the close of the first session. In a bullish version, a black session is followed by a downward gap and the second session opens and rises to close at the same level. In the bearish meeting lines, a white session closes, gaps higher, and is followed by a black session falling to close at the same price. Both are shown in the chart at Figure 5.20.

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bullish

bearish

Source: Chart courtesy of StockCharts.com Figure 5.20: Meeting lines

This pattern contains an important gap. It is invisible with a quick glance, but comparing the first day’s close to the second day’s open reveals the price gap. The significant aspect to this pattern is that both days close at the same price, but the direction changes. In the example, the bullish meeting lines comes at the end of a very shortterm downtrend and then marks the point where the price rises. The bearish meeting lines did not lead to a downtrend and could represent a failed signal. In fact, the price remained at approximately the same level through February 2015 beyond the period shown.

Three White Soldiers and Three Black Crows Clarity of signals is a great advantage in candlestick analysis. Among these are two three-day candlestick signals, the three white soldiers and three black crows. Although the patterns are not easily found in strict adherence to the pattern requirements, they are powerful reversals when they do occur in the proper proximity. Key Point: Three white soldiers is an exceptionally strong bullish reversal signal and useful when located close to support after a strong downtrend.

The proximity for three white soldiers is at the very bottom of a downtrend or shortly after the reversal has begun (in which case the pattern confirms the change in direction). For three black crows, the correct proximity is at the very top of an uptrend or shortly after price has begun to turn downward. Both are reversal indicators. Some analysts claim that when these are found in the wrong proximity for reversal they are continuation signals. However, this is not necessarily the case. When these occur

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during a trend (three white soldiers during an uptrend or three black crows during a downtrend), they are simply coincidences and provide no actionable information. The three white soldiers is highlighted in the chart in Figure 5.21.

support

Source: Chart courtesy of StockCharts.com Figure 5.21: Three white soldiers

This signal appears immediately after the strong month-long downtrend concluded and turned. Because the downtrend lasted for one month, it probably should be interpreted as a secondary trend. Clearly, it moved below support, which was at about $20.50 per share, with that price set at the beginning of August. After the uptrend was underway after mid-October, this support level was tested only on a single session with a long lower shadow, and the breakout failed. The long-term primary trend for this stock was bullish, with the price below $11 at the start of 2011 it was volatile, but had rising prices since that point. A strict set of attributes for three white soldiers is that over a three-day period, each session must open within the range of the previous session and close higher. Thus, the overlap from day-to-day is essential. The example in the figure meets these criteria, but just barely. The closing prices of each session and the opening prices of the following session are very close together. The longer each white candlestick and the more clearly the session opens within the previous range, the stronger the indicator. However, even though this example is minimal in meeting the “rules” of the indicator, it did work as expected, confirming the uptrend and moving price back above support. In fact, price passed above the support line during the middle of these three sessions. Key Point: Three black crows should be found close to the top of an uptrend and signals the end of that trend and reversal to a downtrend.

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The three black crows is the bearish counterpart to three white soldiers. It should appear at the top of an uptrend and mark a clear downside reversal. The pattern consists of three consecutive days, with each day opening within the range of the previous day and closing lower. Ideally, it should be found right at resistance and is exceptionally strong if it moves price through resistance and then retreats into range. An example of an exceptionally strong three black crows is seen in the chart at Figure 5.22. The long upper shadow on the third of three days indicated failed buying activity and the long candlestick in day two gave a strong bearish indication.

nce

resista

Source: Chart courtesy of StockCharts.com Figure 5.22: Three black crows

In observing that these two patterns are difficult to find, a clarification should be made. Many close patterns are seen on numerous charts, but these do not strictly adhere to the requirements of three white soldiers or three black crows. For example, on the chart in Figure 5.21 (three white soldiers), a pattern emerged at the price peak in mid-September. Three consecutive black sessions were in the right proximity to identify reversal but not every one of these sessions opened within the trading range of the previous range. It was close, but it was not a three black crows. This is called three identical crows, referencing the closing price of one session and identical or nearly identical opening price of the next session. In Figure 5.22 (three black crows), bullish patterns appear several times at the end of August (but not in good proximity to call it a reversal); at the beginning of October (again lacking downtrend to reverse and appearing more as a series of runaway gaps lacking the overlap required for three white soldiers); and at the beginning of November (also lacking a downtrend to reverse and failing the overlapping opening test). It is fair to say that many close patterns appear on charts, but strict criteria for both is more difficult to find. The strength in these patterns comes from the overlap

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created with higher open and close (three white soldiers) and lower open and close (three black crows), along with the overlapping price movement. A closely related pattern, identical three crows, also involves three consecutive black sessions. However, instead of each session opening within the range of the previous session, each opening price is identical or close to the previous day’s closing price. This is a rare pattern and a stronger one than the more commonly found three black crows.

Morning and Evening Star Additional three-day patterns that are found frequently are the bullish morning star and the bearish evening star. When found at the end of the trend, these are compelling indicators strongly identifying the point of reversal. The morning star has three consecutive sessions. First is a black candlestick, followed by a downside gap, a white session, and then an upside gap, and finally a white session. The combination of reversed direction and gaps in between each session makes the morning star an exceptional reversal signal. An example, containing two morning stars near one another, is shown in Figure 5.23.

Source: Chart courtesy of StockCharts.com Figure 5.23: Morning star

Key Point: The morning and evening stars are exceptionally strong reversal indicators due to the double gaps occurring in between sessions.

The patterns appear at the end of a six-week downtrend and were followed by a new six-week uptrend. This back-and-forth pattern of trading indicates offsetting secondary trends in a long-term primary trend. At the beginning of 2011 the stock was trading

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at $28, and after the period shown, by the end of February 2015, the price had risen to $44 per share. The evening star is bearish and consists of a white session followed by an upside gap, a black session and a downside gap, and a final black session. This marks the beginning of a bearish reversal. Figure 5.24 provides an example. A very small uptrend of two weeks culminated in an evening star, after which price declined for the remainder of the charted period. Even though the uptrend was minimal and was a swing trend, the turn confirmed the weakness in the longer-term primary trend for this company. The large upside gap of mid-September took price well above resistance, so a retreat was expected. The two-week rally prior to the evening star failed to deliver a bullish rally, so the evening star confirmed the bearish signal from a month before.

Source: Chart courtesy of StockCharts.com Figure 5.24: Evening star

Abandoned Baby A variation of the morning star and evening star is the pattern called the abandoned baby. The difference is that the middle session is a doji or near-doji. This is the “abandoned” session, so called due to the price gaps on either side. The bullish version begins with a black session and is followed by a downside gap and then the doji session. Next is an upside gap and a white session. When this pattern is at proximity to support, it marks the bullish turning point and the longer the last white session, the stronger the signal. The chart in Figure 5.25 includes an exceptionally strong signal consisting of the long white candle in the third day; this was further confirmed by an even longer long white session seven trading days later. Key Point: The imaginatively named abandoned baby, like morning and evening stars, contains gaps between sessions and a reversal of direction.

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Source: Chart courtesy of StockCharts.com Figure 5.25: Abandoned baby (bullish)

However, even with the strongly bullish abandoned baby and confirming long white session, the stock’s price moved into a consolidation pattern. The next step was unclear as of the end of 2014. However, between the bottom on October 27 and the high price in the first week of November, the price moved rapidly from $38 up to nearly $50 per share. A bearish abandoned baby is like the evening star but with a doji in the middle session in place of a white or black candlestick. Figure 5.26 contains two examples of a bearish abandoned baby.

resistance

Source: Chart courtesy of StockCharts.com Figure 5.26: Abandoned baby (bearish)

This stock was volatile through the period, with a high frequency of gaps in both directions. However, the bearish abandoned baby signals clearly marked the tops of

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short-term uptrends and resulting sharp downtrends. The first example was exceptionally strong with a price gap of more than a point before retreating from the high. Marking resistance at the point immediately after this bearish signal, it rose to $12.50. Even with this short-term volatility, the price range was only two points. And the stock was in a long-term primary bull trend. In June 2011, it traded at $6 per share before doubling in value by the end of the last half of 2014.

Squeeze Alert Another interesting pattern among the many candlestick reversals is the squeeze alert. This is yet another unusual pattern in which a set of black candlesticks provides a bullish signal and a set of white candlesticks is bearish. The bullish squeeze alert consists of three sessions, each one opening and closing within the range of the previous session. Thus, each day’s range shrinks to smaller size in both opening and closing price. The first and third session are black and the middle session’s color does not matter. The ideal squeeze alert is found at the bottom of a downtrend. Key Point: Squeeze alerts are rare. They involve three sessions, all with declining real bodies sized within the range of the previous day.

An example is shown in Figure 5.27. In this case, the squeeze alert is not the initial reversal signal, but does confirm a bullish engulfing pattern found two months earlier.

squeeze alert bullish engulfing

ort

supp

Source: Chart courtesy of StockCharts.com Figure 5.27: Squeeze alert (bullish)

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The rising line of support augments the strength of the bullish engulfing, occurring under support, and immediately leading price back into range. However, price then moves into a narrow-range period of consolidation. It appeared at first that the trend was over, but the squeeze alert confirmed the bullish indication and the bullish trend resumed. The bearish squeeze alert contains a first and third white session with the middle session of either color. Figure 5.28 includes a pattern with a squeeze alert. Although proximity is unusual here, it does meet the standard and confirms a primary bear trend in this stock.

Source: Chart courtesy of StockCharts.com Figure 5.28: Squeeze alert (bearish)

The downward price movement began in late July with a very unusual set of signals. The long white candle looked bullish but failed. After a set of four narrow-range days, price fell sharply and continued moving downward for the next two months. Once price began to rally in late September, it appeared that a new bullish move was underway. However, the squeeze alert provided a warning that the bears were still in control. After a short rally up to $56, the price resumed its downward movement through the remainder of the period charted. All candlesticks are forecasts of how patterns are likely to evolve, but they are far from certain. As the examples in this chapter have demonstrated, the reversals signaled by candlesticks must be viewed in a larger context. Many of the charts reflected continuation of long-term primary trends or marked secondary trend movement within primary trends. Any reversal must be confirmed by other signals, however, because every type of signal is likely to fail some of the time.

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Divergence and its Role in Reversal Trends Every chart watcher and analyst contends with the problem of quantifying reversal. Is a strong signal a new primary trend, a secondary move, a swing trend, or only a retracement? The answer relies on taking a view of the longer-term chart and estimating where the current price activity fits. For example, when you find a consistent primary trend, a short-term secondary trend is normal and expected but it does not signal a new primary trend. For that, you need a preponderance of signals, multiple indicators all pointing to weakness in the current trend and the emergence of an opposite movement. Within this analysis fundamentals should play a role as well. A three-year technical trend is directly affected by changes in longer-term fundamental trends. So growing strength or evolving weakness in a ten-year study, for example, would be expected to play out in price. Tracking revenues and earnings, dividend yield, P/E ratio, and debt/equity ratio over the ten-year period may reveal changes, often dramatic in nature. Weakening earnings, even considering growing revenues, dramatically increasing size and range of the P/E ratio, failure of dividend yield to keep up with earnings, or growing debt ratio are negative fundamental signs. And strong revenue and earnings trends with steady net return, stable and moderate P/E ratio, dividends per share increasing each year, and level or falling long-term debt are all strong and positive signals that also will be reflected in price. Key Point: Any instances of divergence must be analyzed closely. These moments may present stronger than average reversal indicators or just a conflict of signals.

A study of the long-term fundamental trends is instructive in determining whether current price trends are primary or secondary and where the long-term price prospects are likely to move. The two disciplines—fundamental and technical—are not separate but different symptoms of the same long-term growth or decline of a company and its stock price. The advantage for the technical side is that demerging fundamental trends are likely to precede a change in the price trend, so as the fundamentals strengthen or weaken, it becomes more reliable to quantify the current trend in perspective and with fundamentals in mind. As part of the dynamics between fundamental and technical trends, divergence is a strong indicator of trend health. Divergence is the movement in one indicator opposite what is forecast in another. This often is seen between price and momentum. Price continues to rise while upward momentum weakens and warns of overbought conditions; or price falls even as momentum reports the stock is oversold. Finding cases of divergence cannot be restricted to price patterns alone. For example, a strong bullish engulfing pattern is in the right proximity to forecast reversal, but the stock price continues to decline. This failure of the signal may be traced to a lack of confirmation, but is also represents divergence—the signal was bullish but price declined. It

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reveals the possibility that selling momentum was stronger than the price prediction in the reversal indicator. Divergence can be analyzed in the context of the predictable course of reversals. These begin with a trade set-up in the form of price tops or bottoms, gaps, and candlestick indicators. The timing of trades is very difficult to call precisely becoming a problem for swing traders, and less so for long-term investors who need only to estimate the set-up range. For example, a resistance or support zone that is clearly identified provides an adequate set-up for most investors with permanent portfolios. Trying to time profit-taking as a primary trend peaks or trying to time entry as a bargain-priced stock approaches the bottom, is not as critical for investors as it is for swing traders. In timing reversal trades, several attributes are desirable to increase success. These are: 1. A long duration in the trend. Statistically, the longer a trend continues moving in the same direction, the more likely it is to reverse. This is an observation made in a vacuum, however, because duration alone is not a signal that the trend is ending. A stock with primary trends running typically between one and two years can experience a four-year trend, and a stable stock with typically long-term primary trends can enter a volatile period of secondary trends very difficult to judge. So long duration of a trend is a positive signal due to a related tendency. As trends continue for a long time, they tend to become low in volatility. A sudden increase in breadth of trading, strong reversal signals of multiple types, and a leveling out in the slope of the trend, all anticipate a trend reversal. When the fundamentals have changed over time, this confirms the likelihood (but not the certainty) of the current trend coming to an end soon. 2. Lack of confirmation for reversal signals. When a reversal signal appears but is not confirmed by other reversal signals, it should be analyzed with great caution. Comparing price to volume, moving averages, and momentum is critical to proceed with confidence. A reversal signal by itself should provide enough confidence to assume it is valid. 3. Divergence signals, especially between price and volume. Investors expect price and volume to act in a coordinated manner. So as price trends accelerate, you expect to see higher daily volume of trading. When the price moves suddenly but volume remains low, this is divergence of the kind that should not be ignored. It probably means the price move is an aberration and is likely to settle down into the established range. It could be a speculative jump in price in either direction caused by rumor or earnings concerns. 4. Changes in trendlines or channel lines. The trendline and channel lines are elegant indicators because they are simple, and they present a case clearly. You track trends with the trendline and you track breadth of trading in the channel lines. No matter how long the trend continues, when price moves against the trendline or expands beyond the channel lines, this is a first signal that the trend is chang-

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ing. That could mean reversal or expansion, and a study of specific signals must be undertaken to determine which type of change is likely to occur. Changes in prices should not be ignored either. Even within an established trading range, when a series of very low-breadth days begins expanding, or when higher-breadth days narrow into very small breadth, these changes signal a likelihood of coming changes in the trend. 5. Sudden changes in price patterns. The trend reversal becomes most likely in the final step of a reversal. This occurs with a sudden increase in price pattern (breadth of trading or violation of resistance or support), volume, or momentum. These changes reveal that the current trend is about to reverse. There are no guarantees, but these sudden expressions of volatility should be taken as a signal of a likely reversal about to occur. Key Point: Effective reversal analysis should include signals derived not only from price but also from volume and momentum.

Reversal analysis is far from an exact science. The analysis of these signals over time and expressed in price, volume, and momentum, improve timing but do not provide any guarantees. The generalizations about signs of reversal are just that, generalizations. Even so, in hindsight, many investors have realized that in missing a reversal, the signs were there in enough time to make a move to open or close a trade and maximize profits.

Breakouts and Proximity to Resistance or Support Perhaps the strongest signal of reversal, especially for swing trends, is the breakout above resistance or below support. If this occurs with strong gapping action through the border, reversal is more likely in this location than anywhere else within the trading range. This observation dominates timing used by swing traders. The observance of resistance and support is the key to timing of trades with reversal in mind. If continuation signals do not counteract this observed phenomenon (breakout with gaps), reversal is highly probable. However, what does it mean for managers of long-term or permanent portfolios? The activity of moving in and out of equity positions often is contrary to the goal of a buy-and-hold strategy. If value investments with strong dividend yield and exceptional fundamental growth are the core of the portfolio, does a breakout above resistance indicate it is time to sell? Does a breakout below support indicate it is time to increase holdings? For the longer-term perspective on portfolio management, it is likely that reaction will be minimal or that action will be taken only if the signals are there to reveal

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a change in the primary trend. However, even the most conservative investor can mitigate risk and even take advantage of short-term reversal with the use of conservative options strategies. These include three strategies, although many additional strategies may also serve the same purpose. The primary strategies to reduce risk in expected reversal patterns or to exploit those patterns with added income are: 1. Insurance puts are put options that place a cap on the maximum loss possible. Buying one put per every 100 shares of stock limits the loss to the net of the put’s strike price less the cost to buy it. For example, buying a 50 put for 3 ($300) caps the maximum loss at $47 per share ($50 – 3 = $47). If the stock priced declined to $48, the loss on the insurance put would be $21 ($48 – $47 = $1 per share). But if the stock price declined to $44 per share, the insurance put enables the trader to sell at a profit or exercise the put. Selling the put when price of the underlying was at $44 represents a 6-point profit ($50 – $44 = $6), adjusted for the cost of the put of 3 ($6 – $3 = net profit of $3). Exercising the put enables the trader to sell shares for $50 per share, creating the same outcome of 6 points profit in the stock, minus 3 points for the original cost of the put. But even if the stock continued to decline, the maximum loss is frozen by the insurance put. Insurance puts can be purchased when the stock’s value has moved higher than expected and when you do not want to sell shares, but you are concerned about a loss in the event of a strong price reversal. Looking at the cost of the put as the price paid for insurance is an effective form of risk management. 2. Collars are the combination of a short call and a long put, opened with one of each option per 100 shares in the portfolio. The cost of the put is offset by the income from the call. This expands the insurance put by exchanging the cap on maximum loss with an offsetting cap on maximum gain. The short call’s premium limits the maximum profit to: Call strike (+) – net premium – original basis For example, you buy stock at $35 and it currently is valued at $48, a difference of $13 per share. You open a collar, paying $300 for a 47.50-strike put and getting $325 for a 50-strike call, both after trading costs. If the call is exercised, the stock is called away at $50, so the net profit on 100 shares is: $5,000 + $25 – $3,500 = $1,525 The collar limits potential profit on the upside in exchange for limiting maximum loss on the downside. If the share price falls below the put’s strike of 47.50, shares can be sold for $47.50 per share no matter how low the price of shares declines. 3. Covered calls are popular with traders. One call is sold for every 100 shares owed. If the call’s strike is higher than original basis in shares, a profit is derived from the combined capital gain, dividend yield and option premium. The covered call

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also reduces net basis in stock by the call’s premium. For example, if you buy shares at $42 per share and sell a 45 call for a premium of 3 ($300), your net basis is reduced to $39 per share.

Conclusion Reversal is at the heart of most technical analysis. Chartists seek early signals that price is about to turn in the opposite direction. The strength or weakness of a confirmation signal determines whether the initial reversal succeeds or fails. The next chapter deals with the meaning of confirmation signals and how they influence the current trend.

Endnotes

1 IndexArb, “Index Component Weights of Stocks in the Dow Jones Industrial Average,” at http://indexarb.com/indexComponentWtsDJ.html 2 Bigelow, Stephen W. Profitable Candlestick Trading. Hoboken, NJ: John Wiley & Sons, 2011, p. 21.

Chapter 6 Continuation Patterns: A Bend in the Trend Trend analysis consists of observing an unending series of reversals and continuations. Some analysts pay little heed to continuation, however. The perception is that continuation only tells you to do nothing, so there is little point in tracking it. However, continuation is much more than just a reminder to do nothing. Chapter 5 focused on reversals, the signals appearing that forecast a change in price direction. This chapter presents a different range of signals. Continuation signals forecast that the current trend is going to continue. Just as reversal must be confirmed, continuation signals are only reliable when two or more appear together. This chapter explains many of the most frequently seen continuation patterns, and has two sections: Section 1, continuation following reversal –– Head and shoulders –– Inverse head and shoulders –– Gaps –– Rounding tops and bottoms –– Rectangle tops and bottoms –– Double tops and bottoms –– Flags and pennants Section 2, continuation signal types –– Cup and handle –– Long candlesticks –– Long-legged doji –– Spinning top –– Thrusting lines –– Separating lines –– Side-by-side lines –– Tasuki gap –– Gap filled Section 1 demonstrates how continuation appears after a reversal signal. Section 2 introduces continuation signals expected to appear within an established trend. Many books on the topic of technical analysis pay little or no attention to continuation signals. Other books associate continuation patterns with consolidation (see Chapter 8), periods in which price pauses and moves sideways until it finally breaks out into a new trend. Most sources define continuation as occurring during a pause in the DOI 10.1515/9781547401086-006

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current trend. This does occur on occasion; however, continuation is more likely to be found during a strong bullish or bearish trend and provides investors with guidance about the strength and duration of that trend. The prevailing focus on reversals overlooks many of the key elements of trend analysis, including identification of whether the current trend is likely to keep moving in the same direction or is beginning to weaken over time. Key Point: Continuation and consolidation are not the same thing. Continuation is a signal about the trend; consolidation is a type of trend with prices moving sideways.

When a stock in your portfolio is undergoing a bull trend, continuation reminds you that your holdings are properly kept in place. However, it could also tell you to increase your holdings with the idea that prices are likely to rise. Out of respect for the standards of diversification as a practice to manage risk, it would not make sense to put too much capital into one issue, even when strong confirmation is found. When a stock’s current trend is falling, investors will decide to get out at some point. Hopefully, the point will be at the beginning of the downtrend and not at the end. If a long equity position has been closed, when should you move back in? Waiting for the downtrend to bottom out, it is easy to miss the reversal and see it only after it has begun. However, continuation signals allow you to monitor the downtrend looking for the bottom. Once these signals stop and prices begin to level out or bullish reversals start to appear, it probably means the timing is good to take up a new long position. Part of that decision is the result to tracking continuation and looking for it to end. For those investors taking up short positions in stock (or in their options), continuation of a downtrend has an entirely different meaning. Once in a short stock position, the more decline the stock undergoes, the more profit the short seller earns. Tracking must involve watching out for reversal, to time that all-important buy to close the order. For those selling call options, the same cautionary practice involves riding the downtrend until it bottoms out and, unless the short call expires worthless (creating a 100 percent profit in the short call), it becomes apparent when the downtrend has leveled out or begun to turn. At that point, the short option trader will want to buy to close and take profits. The opposite applies to put sellers, whose advantage accrues during an uptrend. The farther away from the put’s strike, the less value there is in the put and the greater the eventual profits. Continuation is not limited to the narrowly focused idea that no action is required or that the trend is safe. One element of the continuation signal is found soon after a reversal. For example, a trend stops and a new one begins. Will it continue or fail? Will it move beyond resistance or support? At the beginning of a new trend, after reversal of the previous trend, these questions are not easily answered. At such times, clear and specific continuation signals are reassuring because they forecast that the new trend is likely to succeed, even if it moves beyond previously set trading borders.

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For all investors and traders, continuation is more than a call to inaction. It is a tracking mechanism that advises you about the state of the trend. And once the activity of continuation changes, it signals a new reaction for timing of trades. Key Point: Continuation is not a lack of trend but a specific type of trend that ultimately signals change and a new direction.

A related problem investors face is also corrected using strong continuation signals. It is easy for investors who are succeeding in timing of trades to become overconfident and to develop biases based on their success. This attrition theory means that investors place emphasis on outcomes confirming their actions, while tending to ignore outcomes contradicting their perceptions, assigning such negative outcomes to “external noise.”1 This problem is addressed by observation of continuation signals. When an investor has become vulnerable to the bias growing from past successes, an effective method for holding that bias in check is to recognize continuation not based on belief alone but through the location of continuation signals. This chapter explores many of the reversal patterns introduced in Chapter 5 but examines them in greater detail, seeking examples of confirmation for these or for prior patterns that these reversal signals confirm.

Continuation and its Relationship to Reversal Every trend reversal should be confirmed in two ways. First, you need confirmation of the actual reversal before acting. Entering or exiting a trade without confirmation of the reversal is a mistake. This is the immediate form of confirmation and it might relate to a swing trade or even a very short-term retracement. The second form of confirmation is found in what happens to price in the next phase. Confirmation increases confidence in what the original signal predicted. The next question—after the reversal has occurred—is whether the new trend will continue or reverse yet again. Once the reversal has occurred will it continue or is it a false indicator? To proceed with confidence, the new direction must be confirmed as well. This will be found in price moves above resistance or below support, moves beyond an identified neckline (in head and shoulders patterns, for example), or in specific continuation patterns identified through candlestick signals. Traditional technical analysis focuses on reversals through head and shoulders, price gaps, double tops or bottoms, and moves related to resistance and support. Few indicators are specifically identified as continuation signals. These are limited to flags and pennants often associated with retracement or with price uncertainty in a short-term period of indecision or with the small list of other technical signals. An advantage to candlestick signals is that many relate specifically to continuation.

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With candlesticks, continuation patterns—especially when found near resistance or support—can add confidence to a decision to continue tracking the current trend, even when price moves beyond those all-important breadth borders. Just as reversal is most likely at resistance or support, continuation with a breakout is also most likely if those specific continuation signals are present. Some candlestick analysts claim that a reversal signal may also work as continuation if located in the wrong place. When a reversal occurs during a trend, but indicating the direction is already underway, the argument is that this constitutes continuation. However, this is a questionable assumption. When a reversal pattern appears, but there is no trend to reverse, it is a non-signal. Assuming strength in the trend based on a misplaced reversal signal and then assigning it the properties of continuation, is misleading and confusing. An indicator should be thought of as either reversal or continuation but not as both. Key Point: Candlestick signals are either reversal or continuation. When they appear in the wrong proximity they are not valid signals.

In addition to a signal not being valid due to the wrong placement, some formations are simply coincidences. Assigning value to these is also an error. A smart procedure for identifying reversal or continuation relies on (a) proper proximity and (b) confirmation. You expect to see a bearish reversal at the top of an uptrend and a bullish reversal after a downtrend. You also expect to see specific continuation signals that provide bullish signals in the uptrend or bearish signals in the downtrend. Like reversal signals, continuation is strongest when price has moved through resistance or support. If continuation and confirmation are found together, the trend is likely to continue and, potentially, in a new trading range established after a breakout.

Western Continuation Signals The possibility of continuation will be found following reversal and may occur immediately or over the span of the new trend. Once the reversal is complete, and price begins its new trend; the question for every investor is whether the new trend is going to continue. One form of confirmation is found after the reversal signal. Popular Western reversal indicators and the forms that continuation and confirmation take are discussed below.

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Head and Shoulders The first signal is the popular head and shoulders, introduced as a bearish reversal in Chapter 5. All too often, however, this signal appears in an uncertain environment. For example, in a bullish primary trend how do you identify a reversal attempt and legitimate head and shoulders pattern? Some price movements are not specific enough to conclusively call them a swing trade and to identify whether the pattern has taken place. The head and shoulders is among the most confusing of patterns, because it is usually identified as reversal but at times acts as continuation. With this in mind, the need for strong confirmation when dealing with head and shoulders cannot be overlooked. In Figure 6.1, what appears to be a bullish rally moving against the prevailing trend failed and moved below the neckline, confirming that the brief rally had failed. Once price fell under the neckline, it did not rise above it for the following eighteen months.

resis

tance

neckline

Source: Chart courtesy of StockCharts.com Figure 6.1: Head and shoulders and confirmation

The attempted rally was a bullish swing trend within a primary bearish trend. It took price up approximately 4 points in a chart with 2.5-point spacing, so the short-term move was substantial enough to recognize it as a move against the primary trend. The top of the move (the head) came within 2.5 points of the falling line of resistance. However, once price fell beneath the neckline with a fast price decline between September and November, the prevailing downtrend was confirmed and the head and shoulders also confirmed the primary bearish direction. As expected in a head and shoulders, the failure to break through resistance and the subsequent decline below the neckline confirmed the longer-term trend.

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Inverse Head and Shoulders The opposite of the bearish head and shoulders is the bullish inverse head and shoulders. This pattern challenges support and, upon failure, leads to an expected bullish rally. An example of this is seen in Figure 6.2.

neckline

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Source: Chart courtesy of StockCharts.com Figure 6.2: Inverse head and shoulders and confirmation

The price direction started out as bullish until the last four months of 2012. Price declined beneath support as the inverse head and shoulders formed. In the expected pattern, price rose above support and continued its bullish primary trend. Key Point: All reversal signals need to be confirmed to lead to action. Some signals, even confirmed ones, simply fail some of the time.

The trend marked by the inverse head and shoulders was confirmed as price moved strongly above the neckline, which is a check point for the head and shoulders and confirmation of the failed decline. As price moved higher than the neckline, it gapped and moved strongly, further confirming the price direction following the inverse head and shoulders.

Gaps A lot can be observed about gaps, and in Chapter 10 they are studied in detail. For the moment, gaps are examined as continuation signals for trend behavior. A gap may act either as reversal or continuation; with this in mind, the appearance of gaps has

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to be treated carefully and confirmed with other signals. Figure 6.3 displays a strong primary bull trend with a series of specific price patterns involving gaps.

support

Source: Chart courtesy of StockCharts.com Figure 6.3: Gaps and continuation

In three instances, the strongly bullish trend gaps upward as the price slope narrows. Does this mean the trend is coming to an end or just settling down into a less volatile form? This is the question investors must ask when price moves in one direction very quickly, as it did on the chart in Figure 6.3 for the first eighteen months. The pattern that repeats during this time—strong gap moving price upward and then resumption of the bullish trend—confirms the overall direction with no indication of weakness. In this pattern, the gaps are part of the continuation signal for the bullish primary trend. Gaps often are troubling for chartists, however. Their significance is not always well understood and they may easily be perceived as signs of volatility and uncertainty rather than as part of a continuation signal. The repetitive nature of these gaps and resulting price movement constitute clear continuation even during a volatile period. Price moved from $55 to $90 during the first eighteen months (35 points) and then moved about 20 points in the remaining eighteen months. For trend watchers concerned with excessive volatility in a trend, a change in direction might represent reduced volatility. A secondary symptom is lack of significant gaps in the second half of the chart.

Rounding Top and Bottom The rounding patterns act much like other technical patterns failing to move price in a specific direction. Chapter 5 described rounding patterns as reversals, however, they may be only coincidental price patterns unless strongly confirmed. For example, Figure

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6.4 includes an example of a rounding top. But the question remains: Can the downtrend be confirmed? In this case, after the third rounding top price declined sharply.

support successful breakout with gaps

Source: Chart courtesy of StockCharts.com Figure 6.4: Rounding top and continuation

The apparent reversal of this decline could be questioned at the point that price fell below support. At first, it appeared to turn again and move upward above support so that it looked like a failed breakout at support. However, confirmation of the reversal followed quickly with another decline below support, and a downward moving price gap at the end of November (further confirmed by another downward gap approximately one week later). In this case, the repetitive rounding top pattern led to a downtrend below support, which was confirmed once price established its new range and gapped even lower. Key Point: Rounding patterns are reversal signals and variations of the double top or bottom. However, in some cases they serve as continuation, making the signal unreliable in comparison to more precise signals.

The rounding bottom is a bullish indicator suggesting a coming uptrend. In Figure 6.5, an example of these patterns confirmed a clear bullish primary trend.

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Source: Chart courtesy of StockCharts.com Figure 6.5: Rounding bottom and continuation

The bottom pattern first appeared as price declined over a period of one month. This could have represented the beginning of a downtrend, however, price immediately rebounded. A second price decline to the newly established rising support created a second rounding bottom. A final level of continuation was set by the third rounding bottom well within range. A final price decline to the point of support did not break through, establishing that the primary bull trend would be likely to continue. The bullish trend continued through for the following two months as this trend and continuation predicted.

Rectangle Top and Bottom The rectangle top and bottom often are found in a trending pattern and can predict either a reversal or a move into consolidation. Like the rounding top or bottom, the rectangle pattern is not a strong or reliable signal. The chart in Figure 6.6 is typical of this price pattern.

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supp

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Source: Chart courtesy of StockCharts.com Figure 6.6: Rectangle top and continuation

It appeared, at first, that price was trending downward, but support declined without price breaking through. This could be the start of a new primary bear trend or just the end of the previous bull trend and a move to consolidation. Continuation was not established, however, until the price spiked below support. The fact that it did not hold reveals that the declining rectangle tops were not the start of a bear trend but a more likely move into a sideways consolidation pattern. The price level did continue sideways, trading between $25 and $30 for the following three months after the period shown on the chart. Key Point: Is a reversal likely to lead to an opposite-moving trend or a consolidation trend? The only way to know is by noticing the nature of confirming signals.

A rectangle bottom is a bullish signal, most likely appearing after a swing trend moving opposite the primary trend. An example is shown in Figure 6.7.

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Source: Chart courtesy of StockCharts.com Figure 6.7: Rectangle bottom and continuation

In Figure 6.7, a series of fast but short-lived downtrends occurred within the primary bull trend over three years. The failure of price to turn down for any length of time confirmed the strength of the trend. The bullish rectangles were confirmed with each subsequent rise back to resistance, and the final move upward in February 2014 was a clear continuation pattern for the long-term trend predicted in the series of rectangles. In the two months following the charted period, the stock price rose another 10 points.

Double Top and Bottom Two of the most frequently occurring signals are double tops and double bottoms. As reversal signals, these are reliable and easy to spot. Even so, to establish the success of this signal, two elements need to be present. First is the reversal itself (preferably more than just one signal) and second is continuation of the new direction taking place after the double signal. An example of the double top is shown in Figure 6.8.

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e nc ta sis re

support

Source: Chart courtesy of StockCharts.com Figure 6.8: Double top and continuation

The troubling aspect in this chart is that three distinct and strong double tops appeared before price turned downward. This brings up the possibility that the signals were not strong enough to act upon. However, by the third double top the likely bearish reversal was more certain. One thing occurring with this chart was the appearance of an evolving resistance level. During the consolidation between January 2012 and late October 2014, resistance was firmly set at $41 or $42 per share. Then price gapped upward and rapidly moved above $50, with the three double tops along the way. With each double top, price retreated immediately only to return to a new high. With the third double top, how should this be interpreted? Key Point: Some signals repeat several times before an expected reversal occurs. In this situation, the repetitive signals confirm one another.

The first two double tops appeared to set up secondary trends of only a few months. After the third double top, the decline taking place without stopping was a convincing move. However, after a long period of consolidation preceding this one-year up and down movement, it was difficult to determine the actual direction of price. Continuation was set once the declining resistance extended more than four months. Even then, the overall meaning of the trend was not easy to see. With the dip below support and immediate return above, a primary bear trend was not likely. In fact, that support level held even beyond the period shown; the double top formations earlier in 2014 were likely to relate only to the secondary bear trend from July to December 2014, with a new bullish move following. The double bottom, like the double top, often is difficult to understand. Figure 6.9 provides an example of numerous double bottom formations during a primary uptrend.

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Source: Chart courtesy of StockCharts.com Figure 6.9:  Double bottom and continuation

In this case, the primary trend extended through the entire three-year chart. No fewer than six secondary or swing trends were found during this period. In each case, the downtrend did not last long and immediately after, a short reaction ending with the double bottom formations, price rebounded. This repetitive pattern (downward move, double bottom, resumption of primary trend) was a form of continuation traders could use to predict that the established primary bull trend would continue. The established pattern did continue, in fact, into 2015.

Diamond Formation A diamond may form as either a top or a bottom. It is a reversal signal, but, like all reversals, it requires confirmation. Even with confirmation, the next step is not always clear. Once a reversal begins, the question is whether it’s a false move or can be confirmed. An example is found in Figure 6.10.

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support successful breakout with gap

Source: Chart courtesy of StockCharts.com Figure 6.10: Diamond formation and continuation

Price moved up dramatically beyond the 2012 range-bound trading between $39 and $45, forming a diamond top in the first eight months of 2013. As expected, a strong reaction followed, taking prices down to the newly established support. However, prices then trended upward in a secondary trend forming another diamond top. Once again, prices reacted by declining. At this point, the validity of this reversal was in question. However, the downtrend was confirmed with the continuation established once price fell below support and remained there. Following the upward curve of price, support held for the following two months, meaning that the continuation set with the breakout in September 2014 was a strong signal. Key Point: Diamond signals are less distinct than many reversals, so shape and proximity are the keys to recognizing a true reversal.

Flags and Pennants Previous examples of flags and pennants referred specifically to retracement formations. However, these may also provide short-term continuation signals within an established primary trend. For example, in Figure 6.11, a series of flags appeared over a two and a half-year primary bull trend. The last two in 2014 might be defined as retracements, but the first two, dominating 2013 trading, were not.

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port

sup

Source: Chart courtesy of StockCharts.com Figure 6.11: Flags

The action outlined as flags set up a secondary trend, but the narrow range forming the flag also acted as continuation signals for the bull trend. This is one example of a secondary trend setting up as a continuation signal. The narrow range reveals that short-term price channels will not last long enough to represent a new primary trend. Pennants also work as continuation patterns. Figure 6.12 was dominated by a long-term primary bull trend. However, this became volatile from the second half of 2013 through the first half of 2014. This volatility could have forecast a reversal, but the narrowing range forming the pennants contradicted this and provided continuation signals.

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Source: Chart courtesy of StockCharts.com Figure 6.12: Pennants

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The interesting attribute of this pattern is that price fell below the ascending support between August and October 2014. This was not a compelling breakout, however, since the breadth formed a narrow channel throughout this period. The strong gap upward took price back into range, adding additional continuation signals for the established primary trend. These pennants did not contain attributes of retracement. The first one moved in the trend’s direction and the second one tracked support closely. Even so, the pattern itself was a double continuation signal that was bolstered by the later failed breakout below support. Key Point: Flags and pennants are closely associated with retracement and often are found as part of a continuation signal.

Cup and Handle The cup and handle is a bullish continuation pattern with two parts. The cup is a rounding bottom and the handle that follows immediately is a flag. As a continuation signal rather than a reversal, the cup and handle is valid only if the trend continues. Figure 6.13 includes three examples of the continuation offered by the cup and handle.

port

sup

Source: Chart courtesy of StockCharts.com Figure 6.13: Cup and handle

The first continuation signal occurred as the downtrend bottomed out and began rising, forming the first cup. The handle, a flag, took up two months and set up a continuation for the trend that started three months before.

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The second example showed up as price peaked and began declining. At first, this appeared as a reversal or retracement, but as it rounded it appeared to fail as a downward move. The handle assured continuation. Key Point: The cup and handle is a specific type of continuation signal, but compared to other, less complex ones, it is not always easily recognized.

The third and final example was very similar. Price peaked just above $125 and then paused. The small cup and handle predicted accurately that the rising support was not in any danger. Two attempts at breakout at the end of the chart failed. In the period after the charted three years, support continued to hold but resistance leveled out. This formed a two-month bullish continuation signal in the form of an ascending triangle in the time beyond this chart, adding further to confidence in the primary bullish trend.

Eastern Continuation Signals The emphasis in Western signals is on reversal. And with few exceptions, continuation relates to the continuation occurring post-reversal, as the previous section demonstrated. With Eastern indicators (candlesticks), the distinction is more defined. Candlesticks are either reversal or continuation indicators. When continuation is located at or close to resistance or support, it has great significance. Proximity is one of the factors adding strength to a continuation signal. If price breaks out above resistance or below support and at the same time, a continuation signal appears, you seek confirmation in one or more forms. This may be found in a second candlestick indicator, a Western technical indicator, volume, moving average, or momentum oscillators. Also, strongly confirming continuation is the activity related to proximity itself. For example, a flip from resistance to support or from support to resistance tends to strengthen the new trend. In observing the behavior of price, additional generalizations can be made: 1. A strong trend (meaning a combination of momentum, slope, and duration) tends to lead to strong continuation signals at resistance or support and to strong confirmation. 2. The resulting continuation of the trend tends to be strong as well, notably when resistance flips to support (bearish) or when support flips to resistance (bullish). 3. A weak trend (short duration, narrow slope, slow moving) tends to offer little if any continuation signaling, and if these do appear they also tend to be marginal (barely meeting the signal criteria, for example). Confirmation may be marginal as well or even nonexistent.

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4. A weak trend and weak continuation is vulnerable to failure or may move into consolidation rather than continuing as predicted. This often creates a period of uncertainty and a narrow breadth of trading. An analysis of the popular continuation candlestick patterns demonstrates that these generalizations can serve as guidelines for the timing of trades.

Long Candlesticks Long candlesticks were previously introduced and explained as part of reversal. The length of the candlestick does not refer to a specific number of points because scaling is not the same for every chart. Rather, a “long” candlestick must be defined as a session that is exceptionally long in comparison to typical sessions before and after. Key Point: A “long” candlestick is a relative signal. Due to dissimilar scaling of charts, it is defined as long compared to other signals close by and not based on the number of points of price movement.

The long candlestick may be either a reversal or a continuation signal. As a continuation signal, the proximity of the long candlestick is crucial to its power. For example, in Figure 6.14 two long candlesticks were located, the first marking the point of reversal and the second providing continuation in conjunction with a newly established level of rising support.

resistance

ort

supp

Source: Chart courtesy of StockCharts.com Figure 6.14: Long candlesticks

The downtrend lasting six weeks concluded with the first long white candlestick. Although subsequent price movement tested the rising support level, it was apparent

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that the consistent downward price movement had been halted. But was it a reversal? The second long white session was exceptionally long, making the uptrend effective and providing continuation as well. The new support level held even as price breadth narrowed in the last part of December. As the rising support moved, the level of resistance was marked at $62.50 per share. The brief move above this level at the end of November failed, strengthening resistance at this level. It continued to hold through the next two months as well, setting up an ascending triangle. This was a strong second confirmation that the primary bull trend was holding and gaining in strength. Long candlesticks must be judged as “context” indicators. While specific reversal and continuation signals cannot be switched, several indicators (especially single-session ones) take on meaning based on the context of their appearance. Long candlesticks are one example.

Long-Legged Doji and Spinning Top Another candlestick, with only one session that also gains significance from the context in which it appears, is the doji session with exceptionally long upper and lower shadows. Both are required to create the long-legged doji or the near-doji formation called a spinning top. The long-legged doji signals continuation when a move is underway. A single example is not especially convincing, but when two or more are found chart analysts should pay attention. For example, the chart in Figure 6.15 exhibited a continuing downtrend following a flip from support to resistance.

prior support

new resistance

Source: Chart courtesy of StockCharts.com Figure 6.15: Long-legged doji

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This trend was strengthened not only by the flip but also by the strong downward price gap that moved price below prior support; and the fact that this new range held for the next two months is also noteworthy. Key Point: The long-legged doji is one of those single-session indicators whose significance depends on proximity and how (or if) it is confirmed.

The first long-legged doji appeared in the first session after the gap. This could have been either a reversal or continuation signal, depending on whether price held below the declining line or moved back into the previous range. One month later, it appeared that the new resistance line was going to hold, as price did not advance above it in any of these sessions. The continuing downtrend was strengthened with a second long-legged doji, which provided a continuation signal. In fact, one month later, price descended even further, and the long black session followed by the small session with an exceptionally long lower candlestick marked the end of the decline but predicted that the lower price level between $3.50 and $5 would hold but that prices were not likely to fall any further. Those two sessions of long black candle and long lower shadow marked a failure for price to decline any further. The period after the charted period demonstrated this to be accurate. By the end of January 2015, price was at $4.13, still within the newly set range but poised for a reversal to the bullish side. By the end of February, price had risen to $6.72, back into the original price range set the previous July before support flipped to resistance. Like the long-legged doji, the spinning top must be appreciated in context. It can mark reversal or continuation. An example of continuation with exceptional strength was located on the chart in Figure 6.16.

support resistance successful breakout support

Source: Chart courtesy of StockCharts.com Figure 6.16: Spinning top

resistance

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The first event worth commenting on was the strong breakout in October. This set up a flip from support to resistance, a move setting up a continuation signal consisting of two spinning tops shown by the October and November arrows. Further continuation of the strong downtrend was found in the form of a second support to resistance flip at the end of November. In this case, a strong downward gap took price below support and asset up a new range under $43 per share. Although the price did rally above this level over the two months following this chart, by the end of February 2015 price was within range at $42.94 per share.

Thrusting and Separating Lines The two continuation patterns in this section often are confused with two of the reversals in the last chapter. The bullish thrusting lines is a continuation signal consisting of a white session, an upside gap, and a white session opening higher and closing within range of the previous day. The gap is a key element of this pattern. This can be confusing in chart analysis, because the thrusting lines pattern has the same elements of the piercing lines reversal signal explained in the last chapter. This is one of the drawbacks in candlestick analysis. Many patterns are similar (or identical), but one represents reversal and the other represents continuation. It depends on where they appear on the chart. A piercing lines is expected to show up as a bullish reversal at the bottom of a downtrend, or as a bearish reversal at the top of an uptrend. But the same pattern is defined as a thrusting lines continuation signal when it appears elsewhere. The similarity of two signals with different interpretations reduces the reliability of both signals. In this instance, both piercing lines reversal and thrusting lines continuation are suspect. They should be used as forms of confirmation and only when additional strong signals appear at the same time. The bearish thrusting lines is the opposite of a bullish version: a black session, downward gap, and a white session opening lower and closing within range of the previous day. The same caution applies on the bearish side: Because this pattern is identical to piercing lines reversal, the bearish thrusting lines is not reliable enough to be viewed as a reliable continuation signal. Key Point: Thrusting and separating lines are continuation signals, but these formations are less reliable than other continuation signals due to their appearance, the same as piercing lines reversals.

The distinction here is placement and confirmation. Both thrusting lines and piercing lines will appear within the current trend, but they can have opposite meaning. So how can you decide whether this configuration is acting as reversal or continuation?

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In the continuation (thrusting lines), confirmation can consist of other continuation patterns or just by the failure of price to turn in the opposite direction. An example of bullish thrusting lines is found in Figure 6.17.

bullish

or

pp

su

t

Source: Chart courtesy of StockCharts.com Figure 6.17: Thrusting lines

Although price reaction is sideways and then downward at first, in both cases price stopped declining as soon as it reached support. The primary bullish trend then continued. The two instances of decline stopping right at the line of support confirmed the thrusting lines as bullish continuation. A related indicator is the separating lines, another form of continuation. A bullish version has a black first session, a gap upward, and a white session opening higher but closing at the same price as the previous day. The bearish variety begins with a white session, a gap downward, and then a black day opening lower and closing at the same price as the previous day. The pattern is like the reversal meeting lines, but each day’s color is opposite. This is what distinguishes the meeting lines reversal from the separating lines continuation pattern. An example of a bearish separating lines is shown in Figure 6.18.

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bearish

sup

po

rt

Source: Chart courtesy of StockCharts.com Figure 6.18: Separating lines

In the bearish signal, the downtrend began with a downward gap in late July, but prices immediately began moving sideways. In a consolidation pattern, it is difficult to know whether the downtrend has failed or only paused. The appearance of a strong bearish continuation pattern determines the answer. The downtrend did continue for another month until mid-October. A problem with all the reverse and continuation patterns having similar traits makes them difficult to use reliably. Reversals (piercing and meeting lines) and continuation (thrusting and separating lines) are easily overlooked because of this similarity in pattern and the resulting confusion. However, in some cases, such as the charts above, the value of the signal itself can be a determining factor in identifying a trend as failed or continuing.

Side-by-Side Lines A set of signals identified as side-by-side are forms of continuation and they come in four types. The side-by-side bullish white lines has three sessions: a white candlestick, upside gap, and two additional white sessions. The side-by-side bullish black lines starts with a white candle, then an upside gap, and two black sessions. In a bearish white side-by-side lines, the first session is black and is followed by a downside gap and two white sessions. The bearish black side-by-side lines begins with a black session and is followed by a downside gap and two additional black sessions. Key Point: The strength in all side-by-side patterns is a combination of candlestick direction and the gaps formed within the signal itself.

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Initially confusing for traders not accustomed to the subtle differences between similarly named candlestick signals, viewing these four possible patterns sets up clear distinctions. Recognizing the beginning white candlestick and upside gap reveals a bullish trend, and the black candlestick followed by a downside gap is clearly bearish. An example of bullish side-by-side lines is shown in Figure 6.19.

nce

resista

black bullish white bullish

Source: Chart courtesy of StockCharts.com Figure 6.19: Bullish side-by-side lines

The uptrend began in late July but then paused for September and October. The decline in early October could have signaled the end of the uptrend, but the white bullish side-by-side lines forecast continuation. This move was confirmed by a second continuation pattern, the black side-by-side lines in late October. The trend did not last much longer, topping out in mid-November before settling into a consolidation pattern that lasted for at least two months beyond the time shown on the chart. A black bearish side-by-sides formation appeared and was confirmed by a second one on the chart in Figure 6.20.

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resistance

black bearish

sup

po

rt

Source: Chart courtesy of StockCharts.com Figure 6.20: Bearish side-by-side lines

The first instance of a continuation side-by-side lines occurred following a pause in the prior downtrend and short-term consolidation pattern. The fact that price rose after the first black bearish signal would have caused concern except for one fact: prices rose slightly above $27 per share but failed to break out above resistance at approximately $27.50 per share. This was the initial confirmation that a continuation was underway. Final bearish confirmation was found with the second black bearish side-by-side lines pattern.

Tasuki Gap The tasuki gap is a strong continuation indicator. The world tasuki is Japanese for a sash used to hold sleeves in place and, by the same description, the tasuki gap keeps a trend intact and moving, working as a form of continuation. Key Point: A gapping price pattern is a strong form of continuation when the gap moves in the direction of the trend.

A bullish tasuki starts with a white candle session, an upside gap, a second white session, and then a black session opening lower and closing below the opening of the previous session. A bearish tasuki starts with a black session and is followed by a downside gap and another black session. A final white session opens higher and closer above the opening of the previous day. An example of the bearish version is shown in Figure 6.21.

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bearish resis

tance

Source: Chart courtesy of StockCharts.com Figure 6.21: Tasuki gap

The downtrend began in early September but was not especially steep. In fact, a rally in late November made it appear that the downtrend might be over. The decline and appearance of the tasuki gap was a convincing signal that the downtrend was still in effect. It continued even beyond the charted period, moving to $52 per share in late January before prices again moved upward.

Gap Filled The gap filled is like the tasuki gap, but with one important distinction. In both bullish and bearish versions, the final session moves into the range of the very first day, closing the gap created between days one and two. An example of the bullish gap filled is found in the chart in Figure 6.22.

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nce

resista

bullish

Source: Chart courtesy of StockCharts.com Figure 6.22: Gap filled

The bull trend began at the start of August. At the end of September, the continuation was forecast by the bullish gap filled pattern. The uptrend did continue as predicted, pausing only at the end of November before surging upward once again in December. During January, the month after the period shown, prices rose to $110 before retreating into the range shown on the chart. However, the uptrend covering six months on this chart did not end, and its continuation was predicted with the bullish gap filled signal. Key Point: Gaps that fill are strong signals of continuation. Analysts prefer to see gaps fill because it indicates strength in the trend.

A problem every investor faces in the use of continuation patterns is the awareness that all signals may fail. This observation is applied to reversal patterns in most cases, but it applies in the same way to continuation. Because continuation advises no action for those already in equity positions on the upside or those not in equity positions and waiting for the bottom to occur, they are not as exciting as reversal. Just as investors must be aware of when trends are ending, they also need to track trends as they continue. The next chapter takes reversal and continuation to the next step, which is confirmation. No signal by itself should be acted on unless and until it is confirmed by additional signals, whether forecasting reversal or continuation. When these patterns evolve in proximity to resistance or support, the likely success of the signal, once confirmed, is at its strongest.

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Endnotes

1 Bem, Daryl J. “An Experimental Analysis of Self-Persuasion.” Journal of Experimental Social Psychology (1965): 1, 199–218.

Chapter 7 Confirmation Signals: Turning the Odds in Your Favor Because technical analysis demands discipline, the very idea of confirmation is of the utmost necessity. Ironically, it often is overlooked or discounted, with emphasis on fast and immediate action upon spotting a signal, notably a reversal signal. Requiring confirmation before acting is not overly cautious but a sign of maturity in an investor or trader, an attribute of experience. Once an investor realizes how easily “sure things” can fail, an appreciation for confirmation develops and builds. However, every investor also needs to proceed with caution. The difference between strong or multiple confirmations and weak or a single confirmation is profound and may easily lead to ill-timed trades. Is there such a thing as too much caution? Yes. If you expect multiple confirmations and fail to act in a timely manner when there are “enough” confirmations in hand, opportunities are lost. Key Point: A dilemma for all investors is knowing when enough confirmations are present. A good rule of thumb is to set standards in advance, and to then act quickly.

The suggestion in this chapter is intended to overcome the emotional nature of the market in which impulsive actions often outweigh objective analysis. The tendency to overlook the importance of confirmation is one of those observable problems for investors which, if discipline is applied, can be overcome in favor of a structured approach to timing of trades and on a larger scale, to selection to strategies within a portfolio management plan.

The Causes of Price Movement A great mystery in all technical analysis is why prices move. Observing direction of movement and identifying signals is the primary activity in analysis; but why do prices move? The long view is that all elements of what appears chaotic are attributes of supply and demand, growing from fundamental trends. There is some truth in this, but there is more. Trends on the technical side often seem to develop with little or no regard for fundamental strength or weakness. Technical trends often diverge from what the fundamentals indicate. Investor sentiment is not always reflected in the numbers, so price movement is caused by a combination of supply and demand along with behavioral psychology in the market. And that contains many elements. Much emphasis in technical analysis is placed on the rationale of price movement, represented in patterns and trends. However, the uncertainties and risks of any attempt to time trades, especially for short-term price movement, can not be overDOI 10.1515/9781547401086-007

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looked. Prices move for dozens of possible reasons, and investors cannot know with any certainty what underlying causes are in play during a reversal or continuation. Therefore, reliance on confirmation is essential, not only to increase the chances for well-timed decisions, but also to combat the human element in decision-making, in which impulse, emotion, and narrow focus on only a few possible elements can easily distort judgment and lead to poorly timed decisions. For many investors, reliance on technical analysis is comforting, based on the belief that the answers are found in price patterns, trends, and marketwide strength or weakness. However, this addresses only part of the question about price behavior. A chartist, relying on price patterns and evolving trends, may easily overlook the underlying causes of change in price, even when the answers may be found with further analysis: Technical indicators do not reveal causes of market movement. They simply indicate the proximity of a reflecting boundary. We therefore use technical indicators only in context of a potential reflective boundary. When creating models we utilize data only when the data are proximate to a measured high or low, a potentially precise turning point.1

The “reflecting boundary” refers to a technique in which probabilities of specific price behavior are expressed within a range of likely movement based on past trends, resistance and support, and volatility. This, combined with identified signals and strong confirmation, adds value to the science of trend analysis. It allows you to temper the observation of a trend with an observation of how a specific stock has behaved in the past and therefore likely to behave in the future. Key Point: All signals are only estimates of likely outcomes. Even with strong confirmation, there are no guarantees.

This adds no certainty to the analysis but it does provide a framework for viewing the behavior of price within the trend. However, price behavior is only one aspect of trying to understand why prices move. Of perhaps much greater importance is understanding how humans behave and why. This often leads to a deeper understanding of why prices move, combined with the technical analysis of how price patterns evolve and reverse or continue trends. The confirmation of these movements is an attribute not only of how trends move and change but also of why the price of a specific stock has evolved in a specific manner. Anyone who is uncertain about the combination of market and human behavior needs only to compare the stock charts of any two companies. Patterns develop independently for companies, creating a behavioral tendency within the stock price, even when the fundamentals for the two companies are identical. This is a symptom of the behavioral psychology of investors and their perception of a company, its value, future growth, and even basics like quality of product, experience of management,

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corporate culture, and long-term prospects for sustained growth (in stock prices, market share, dividends, revenues, and earnings).

Behavioral Psychology and the Market The principles of technical analysis are based in logic and study in statistical and realistic assessment of price strength and weakness—in other words, in the attributes of trends and the ways in which they proceed or stop. Opposing this methodical approach to analysis is the overriding emotional and often irrational behavior of investors and traders. Too often the emotional responses, notably greed in bull markets and panic in bear markets, mask even the most obvious responses that should prevail but that do not. At times of extremes in price movement in the overall market, rational analysis is easily ignored as market participants rush to join the majority. Even when that majority has been shown time and again to be in error at such extreme times, the impulse to follow often is stronger than rational thought. This is a problem, of course, because a majority is difficult to resist. However, it is also an opportunity. A contrarian approach to investing is based not simply on the idea of moving opposite of the majority but on the more logical idea of making decisions based on analysis and study and not based on emotion. A contrarian recognizes extreme decisions made in extreme market conditions and can exploit overreactions by timing decisions based on trend analysis and not on the far less rational gut reactions of greed or panic. Key Point: A contrarian acts not just to go against the majority but based on logical and rational observation and not on emotion.

The tendency to overlook and even completely ignore facts defines the oddity of investor behavior at times when calm analysis would better serve their motives: Stock traders make decisions based on psychological factors, including emotions, and may place undue weight on specific information at the expense of other relevant data. Different emotional states can have unpredictable effects on decision-making at different times. Mood can have an impact on cognitive performance and expectations, while factors such as a series of gains or losses can have an effect on traders.2

The behavior itself may seem odd when viewed from a distance, even though investors and traders repeat the same tendencies over time. The majority is not always wrong but often makes poor decisions based on identifiable flaws in thinking. A study of 422 investors drew the conclusion that specific tendencies were repeated over time: The final results [of that study] show that five factors of psychology which are overconfidence, optimism, herd behavior, psychology of risk and pessimistic [sic] have influence on investment

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decisions. To be more detailed, excessive optimism, psychology of risk and excessive pessimistic [sic] affect positively on long-term investment of investors while overconfidence and herd behavior have the negative impact.3

To what degree do these emotional tendencies affect trends? This is a point of concern for all investors interested in tracking the trend and its outcome. If emotions are the root cause for investors to buy or to sell, do emotions also affect the trends themselves? The past has shown that the mistakes made in the “herd mentality” of the market are likely to repeat in the future, so a highly pessimistic conclusion could be that an analyst’s inability to predict the emotional mood of the market brings all analysis into doubt. The solution, however, is strong and brings analytical order to the emotional chaos of the market. The contrarian approach to timing and to trend analysis forms the logical foundation of trend analysis, not emotion. It is true that emotion has the most immediate short-term influence on price movement, and this is easily seen in even the strongest trends. The secondary trends and swing trends that offset even the strongest primary trends cannot be ignored or denied. At some point, one of those reversals becomes a new primary trend, so even the most ardent contrarian must be aware of the rationally-based analysis. Ignoring the short-term extreme behavior based on emotion, a contrarian relies on several price patterns, statistical tendencies, traditional rules of technical analysis (such as the behavior of price in proximity to resistance and support) and, more than anything else, confirmation. Key Point: Contrarian investing demands strong, cold discipline. Going against the prevailing opinion of a majority is never simple but may be right often.

The confirmation signal provides certainty in the uncertain world of stock analysis. It defies greed and panic and provides the analyst with not the certainty but the high likelihood that price will behave in a predictable manner and that trends will reflect the sum of price indicators for reversal or continuation, all based on whether the immediate signal can be confirmed.

The Flaw of Overconfidence Among the emotional components of market behavior, overconfidence may be the most destructive. It blinds the logical mind. It creates the illusion of certainty when conditions are uncertain. It convinces the investor that individual success, knowledge, and ability lead to success. Overconfidence is most dangerous among those with knowledge in a subject area. If a little knowledge is a dangerous thing, a lot of knowledge and experience can be both dangerous and blinding. Having some knowledge is invariably a flawed condition because it means an investor is not equipped to analyze the entire realm of risk involved in investing.

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However, once an investor has built a level of skill, increased success may easily lead to overconfidence. This is justified to a degree, but in a larger sense it leads to great vulnerability because the overconfident investor may easily become blinded to the risks of a decision or range of decisions. Overconfidence may easily lead to poor decisions. In one of the largest debacles since the Great Depression, Goldman Sachs was sued by the SEC for its deal involving collateralized debt obligations (CDOs) made with Paulson & Co. Paulson, which retained Goldman Sachs for a fee of $15 million to put together a synthetic CDO, which ended up containing mostly sub-prime mortgage obligations. With the collapse of the sub-prime market, Goldman lost $100 million. At the same time, Paulson shorted the arrangement through credit default swaps, which set up a conflict of interest. Certain they would make big profits on this deal, Goldman Sachs was accused of failing to disclose material facts and was fined $550 million.4 Why did Goldman Sachs enter this deal based on devices as risky as sub-prime mortgages? Why did they fail to disclose material facts? Why didn’t they recognize the conflict of interest by Paulson in shorting the plan? Was it greed, hubris, or plain old-fashioned failure to understand the risks? All these errors, made on a large scale by one of the big Wall Street firms with great expertise and resources, betray a culture of overconfidence. Compared to the actions of smaller organizations and their portfolio management team, or to highly skilled individual investors, the Goldman Sachs case is not a typical example. However, it demonstrates that bigger companies with more resources may be just as vulnerable as smaller ones to overconfidence. Key Point: Overconfidence leads to errors in judgment. This applies to large institutions as well as to individual investors.

Applying the same observation to the decisions to buy or sell securities based on observed price patterns, the importance of confirmation can not be ignored. Certainly, Goldman Sachs should have applied due diligence to ensure that the deal they entered was both legal and made with full disclosure. They failed in this. Just as large Wall Street firms with entire departments of compliance officers and lawyers may fail, so may financial advisers, money managers, portfolio managers, and investors. Everyone is at risk to become overconfident in their abilities to make sound decisions or even in their basic compliance with the law, as in the case of Goldman Sachs and their partners. Overconfidence allowed Goldman Sachs to proceed without performing due diligence, a form of confirmation that the deal followed the law and with good practices; it blinded them to the risks they faced, not only in suffering losses once the sub-prime market failed, but also in overlooking the need for disclosures and elimination of conflicts of interest. For organizations smaller than Goldman Sachs and for individual investors, confirmation exists on an entirely different level. However, the risk of overconfidence

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is universal. This is expressed in many forms. The most obvious is a tendency for investors, either individual or institutional, to overestimate their skill level in making investment decisions. Along with this tendency is a related tendency to assign success to superior skill and to rationalize failure outside of the skill set. Another symptom of overconfidence is the tendency to pick information that conforms to a set bias. This can relate to belief about a company, a favorite reversal indicator, and any other factors that influence objective thought. It is also possible to hold onto beliefs about a company or “system” for years, even after evidence reveals that those beliefs are simply false. The possession of beliefs is very comforting, true or otherwise; part of the tendency of overconfidence is to resist changing. For example, an investor who has owned shares of a company for many years continues expressing confidence in that company even as fundamentals begin to weaken and stock prices fall. Overconfidence may be a widespread problem for investors, perhaps more than many are able or willing to admit. The solution to this problem is most likely to be found in application of sound analytical principles. In terms of trade timing and trend analysis, confirmation is one of the tools you can use to improve confidence in observed signals and in determining the true status of the current trend. As a starting point in identifying when signal confirmation is the most valuable in the process, resistance and support should be considered. The principle of proximity is one of the keys to accuracy in trend analysis and can be used to ensure objective analytical conclusions in place of overconfidence or emotional reaction.

Resistance and Support as Keys to Confirmation Proximity The role of resistance and support in both reversal and continuation patterns cannot be emphasized enough. These price points near resistance and support are the most likely for successful price movement in the direction forecasted. Confirmation is yet another factor that will be at its strongest at these points. Key Point: Just as reversal is most likely in close proximity to resistance or support, confirmation is also likely to increase confidence that reversal is highly likely.

When reversal signals appear and are quickly confirmed by additional signals, this should increase confidence. However, when reversal is found right at resistance or support, confidence should approach 100 percent never quite reaching it because anything can happen but getting as close as possible. This also assumes that the reversal and confirmation signals are strong enough to convince you that the likelihood of success is high. An example of reversal and confirmation taking place right at these key price points is found in Figure 7.1.

Strong and Weak Confirmation 

resistance

bullish abandoned baby

 169

support

upside gap filled suppo

rt

spinning top

double bottom

Source: Chart courtesy of StockCharts.com Figure 7.1: Proximity—resistance to support flip

Support began falling in mid-August and continued downward through mid-October. At both beginning and end of this support trend, the price was tested, only to be met with strong bullish reversals: first a bullish abandoned baby and then a double bottom (confirmed by a spinning top). However, the most impressive confirmation was found at the point that price moved through resistance and formed a resistance -to-support flip and a new trading range. Normally, price moving through resistance would be viewed with caution. However, the upside gap filled as a strong bullish continuation signal, and as expected, the breakout succeeded. The strength of this type of signal is invariably strong. In this instance, the resistance-to-support flip and the upside gap filled signal presented creating a convincing form of confirmation.

Strong and Weak Confirmation Another way strong confirmation results occur is when signals combine to make the case. Confirmation can be set up with any combination of signals, including Western and Eastern technical signals, volume, moving averages, and momentum oscillators. For example, in Figure 7.2, price dropped below support and immediately gapped even lower. This is a troubling signal, often forecasting a fast reversal back into range. But the gap needs to be confirmed.

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support

gap below support volume spike

long white candlesticks

Source: Chart courtesy of StockCharts.com Figure 7.2: Strong confirmation—gaps and spikes

Two strong forms of confirmation appeared immediately after the initial gap. First was a volume spike, one of the more reliable reversal signals. Second was a set of two long white candlesticks, which created a likely bullish move. As expected, price returned to its previous range with a breakout lasting less than three weeks. Another form of multiple signals setting up strong confirmation can be seen in Figure 7.3.

runaway gaps

bullish white side-by-side lines

bullish harami

Source: Chart courtesy of StockCharts.com Figure 7.3: Strong confirmation—runaway gaps

long white candlestick

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The bullish harami was the first reversal signal worth noting on this chart. If the assumed support level of approximately $103 was accepted (although it held for only two months), the five sessions below represented a failed breakout with strong signals. The bullish harami was confirmed initially by the long white candlestick two sessions latter. Further confirmation came in the form of runaway gaps. Key Point: Confirmation takes many forms, but failed breakout is one of the strongest, since the reaction tends to move price in the opposite direction from the attempted breakout.

The combination of long candlesticks and runaway gaps was especially noteworthy given the extremely narrow trading range that preceded this volatile move. The breadth of trading was about two points through September, unusually low given the price range around $100 per share. Breadth began expanding in early October before the breakout below support, indicating that a change was coming. However, what at first looked like a possible bearish trend turned out to be a bullish breakout, settling into an expanded range between $110 and $125 (this range lasting beyond the period shown). The breakout above resistance was also confirmed by a continuation signal in the form of a bullish white side-by-side lines pattern. Assuming that resistance was at about $109 per share, the breakout occurred after the runaway gaps and the sideby-side lines appeared immediately after the breakout. Just as reversal confirmation at resistance or support is at its strongest, so is continuation confirmation. The combination of reversal and confirmation at support in the mid-$90s and continuation above resistance at $110 makes a convincing case for the value of proximity of confirmation signals to both support and resistance. Strong confirmation contains specific attributes, including the strength of price patterns followed by equally strong confirmation signals. The opposite is also true. Weak confirmation includes attributes like poor proximity or misplaced signals, weak patterns, and the failure to break out above resistance or below support. An example of weak confirmation is provided in the chart at Figure 7.4. In this case, the flip from rising support to new resistance did not lead to a strong bullish trend. In the period following the one charted, prices evolved into consolidation, range bound between $80 and $84 per share. The question for analysts is whether this weak outcome could have been anticipated in what occurred in the preceding six months.

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three black crows

tance

resis

ort

supp

bullish harami

Source: Chart courtesy of StockCharts.com Figure 7.4: Weak confirmation

The chart appeared promising for bulls at first. Support was rising, and during October the price range expanded rapidly. However, it did not hold. The signal identified as three black crows also failed to set up a downtrend for two reasons. First, it was not a perfect signal and should be defined as a near-three black crows. Second, it appeared after a period of consolidation and not at the end of an uptrend. Lacking the correct placement, this is either a weak signal or a non-signal. Once the flip from support to resistance occurred, the price pattern settled again into a consolidation pattern. The bullish harami appeared to present a case for price to rise strongly, but it was not able to make a move or hold prices above $84 per share. The bullish harami by itself is not an especially strong signal and works best when accompanied by strong confirmation. In this instance, a weak bullish signal was not confirmed and the resulting price move failed.

Momentum and Timing of Preceding Trends Another way in which prices evolve is through a short-term cyclical pattern of movement. This often involves waves of alternating bullish and bearish secondary trends or swing trends. These are ideal for swing trading, but for the longer-term direction you need to review a period longer than six months. Key Point: Momentum is effective in identifying the rhythm of short-term trend cycles, whether swing trends or secondary trends.

The chart in Figure 7.5 contains no fewer than seven sets of signals over six months. The price pattern alternates between uptrend and downtrend.

Momentum and Timing of Preceding Trends 

bearish evening star (reversal)

 173

dragonfly doji (bullish confirmation)

bearish abandoned baby (reversal)

bullish piercing lines (reversal)

bullish engulfing (reversal)

bullish tasuki gap (confirmation)

hammer (bullish reversal)

Source: Chart courtesy of StockCharts.com Figure 7.5: Cyclical secondary trends

The movement of price on this six-month chart reveals the role played by confirmation. The first bullish reversal highlighted was a piercing lines pattern. The resulting uptrend lasted less than three weeks before the bearish abandoned baby signal appeared. After a brief consolidation, a bearish evening star presented another bearish signal, confirming the abandoned baby. At the bottom of the downtrend, a bullish engulfing forecast trended upward, and this was confirmed quickly by the bullish tasuki gap signal. A second decline ended with an exceptionally strong hammer, presenting bullish reversal. This was followed by an upside gap and a dragonfly doji, which confirmed the hammer’s bullish forecast. Even with these short-term trends moving back and forth, the big picture revealed a broader view of what was going on with this company. The six-month chart was a consolidation period ranging narrowly between $23.25 and $26.75 over six months. Even though the volatility was apparent, a broader view demonstrated what took place throughout 2014, compared to the primary bull trend in 2012 and 2013. This is shown in Figure 7.6.

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retracement flags

consolidation channel

a

prim

lish

ul ry b

tren

d

Source: Chart courtesy of StockCharts.com Figure 7.6: Two-year trend

The entire period shown in the previous chart represented the last six months of 2014. The longer-term chart reveals that the entire year of 2014 was the consolidation following a two-year primary bull trend. The noted retracements were strong, and in this case, flags represented not only retracement, but continuation patterns. With the breadth of trading within a two-point range during the uptrend, a similar breadth characterized the consolidation during 2014. This comparison makes an important point concerning all forms of chart analysis, notably with confirmation signals in short-term time spans. What appeared at first to be a highly volatile period was only movement of the secondary trend within a very narrow breadth of trading during consolidation. Once the primary bull trend ended, the cyclical secondary patterns took over. The problem with consolidation is that it becomes difficult to identify new trends, since there are no long-term trends to reverse. Referring to the six-month chart, none of the secondary confirmation signals provided strong primary trend indications since price was range-bound throughout the period (and beyond). Key Point: Confirmation is challenging within a consolidation trend, since indicators must be interpreted without a bullish or bearish trend to reverse.

A final example of momentum makes another point concerning trend analysis. The term “momentum” normally is applied to the mathematical effects of momentum oscillators, which measure not the direction, but the speed of a trend. There are instances, however, when momentum has a somewhat different meaning. Figure 7.7 presents a case in which declining support was part of a broadening price formation. As support fell, resistance rose slowly but steadily. As price broke out below support, a harami cross signaled reversal and strong confirmation followed quickly with a white side-by-side lines bullish signal.

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resistance

support

supp

ort

white side-by-side lines (confirmation) harami cross (reversal)

Source: Chart courtesy of StockCharts.com Figure 7.7: Trend momentum

The momentum in this set of signals included not only a return into range, but replacement of declining support with a new, higher level above $60 and, like resistance, on the rise. A previous declining support pattern experienced a drastic change once the breakout failed. It led to replacement at a higher level, and throughout the six months resistance continued rising in a steady way. The momentum here was all price-based and revealed a dramatic upward adjustment in the trading range.

Divergence Analysis and Confirmation Confirmation provides signals of trend reversal or continuation with the strongest and most reliable forms located in close proximity to resistance or support. This is especially the case when the price gaps above resistance or below support and if signals appear in the proper location within the trend. A few important rules apply: 1. A bullish reversal is valid only when it appears within a downtrend. 2. A bearish reversal is valid only when it appears within an uptrend. 3. A bullish confirmation is valid only when it appears within an uptrend. 4. A bearish confirmation is valid only when it appears within a downtrend. All these observed rules are naturally associated with proximity. Price action at resistance or support, or moving through those price levels, is invariably more significant than when the same signals are located elsewhere. The opposite of confirmation is divergence. While confirmation follows and validates reversal or continuation, divergence provides a signal even when price moves in the unexpected direction. The concept of divergence is more often associated with moving averages (see Chapter 11) or momentum oscillators (see Chapter 12). However, a more basic form of divergence is found in unconfirmed signals that fail. When

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signals and price do not agree, the price usually ends up having greater validity than the unconfirmed signal. For example, in Figure 7.8, two distinct confirmation signals, both bearish, forecast downtrends that did not materialize.

downside gap filled (continuation) bearish thrusting lines (continuation)

Source: Chart courtesy of StockCharts.com Figure 7.8: Divergence

The first, a thrusting lines signal, appearing during a downtrend, led to a price decline for three weeks, but the decline quickly reversed. Looking back to the period before what is shown here, the first session, a long-legged doji, signaled bearish reversal and was the highest price point in an uptrend. Key Point: A weak trend should lead to caution since it is the most likely type to experience weak confirmation—and even failure.

However, the downtrend itself was weak. Breadth of trading was small, only about one-half point in most sessions. And by the time the confirmation signal appeared, the downward movement had been in effect for less than three weeks. This was not a strong downtrend, and its duration was not convincing enough to accept the confirmation signal as a valid indicator of continuation. The second instance occurred in November after an uptrend had ended and another downtrend had begun. The same problems were present in this case as before. Breadth was about one-half point and the downtrend lasted only four sessions before the downside gap filled continuation signal appeared. Price did not fall after the continuation signal but instead began rising. Another important point to make about this chart is its limited overall breadth. During the entire six months, it moves only 12 points from bottom to top. This is a weak series of price patterns without any substantial price movement. Over the pre-

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ceding three years the same narrow range was in effect. Although prices did gradually rise, the overall pattern was a modified consolidation trend without breakouts of any significance. The continuation patterns on the chart diverged from price movements and, even without any strength in long-term trends, the divergence signals provided no real guidance for price direction.

Fundamental Analysis and Confirmation For the technical analyst, the problem with fundamentals is a matter of timing. By the time the latest fundamentals have been published, considerable time—usually several months—has passed. The value in fundamentals for stock selection must involve the analysis of several years of fundamental trends. Knowing that a lag time makes fundamentals ineffective for analyzing current prices and for confirming trend reversal or continuations, the fundamentals serve a different purpose in technical analysis. Specifically, a correlation between fundamental volatility and technical volatility points to degrees of risk and the strength of all signals—reversal, continuation, and confirmation. This lag time is forever present, although changes in fundamental indicators do eventually become reflected in the price and in trends of a security. No one knows how long that will take, but fundamental trends in dividends, cash flow, and profitability are going to affect price trends in the future: “We know from experience that eventually the market catches up with value.”5 Those valuable fundamental indicators can be studied over several years, and the volatility of trends over time reveals a lot about volatility in stock prices as well. The areas worth studying include revenue and earnings (especially comparative analysis of how the two results grow or shrink together); dividends (per share and yield); P/E ratio (especially annual ranges from high to low); and debt to total capitalization ratio (seeking a steady or declining percentage of long-term debt to total capitalization). These are the key fundamentals useful for stock selection and for identifying reasons for technical volatility. The more certainty you find in fundamental trends over many years, the more certainty you will also find in stock trends. This translates to lower volatility. Key Point: A short list of fundamentals helps identify a company’s financial strength or weakness. This is reflected, ultimately, in price strength or weakness.

Applying fundamentals to technical analysis is elusive. However, fundamental analysis can be used effectively to select stocks. Once a company’s stock has been added to a portfolio, its market risks are tracked through technical analysis and close observation of short-term and long-term trends. This is where the marriage of fundamental and technical analysis makes sense. The reliability of fundamental trends is reassur-

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ing to a market whose participants are easily disturbed by any surprises. Even positive surprises, such as better than expected earnings, add to the uncertainty about an investment’s long-term risks. The fundamental trends lead the way and the technical trends follow and set the course for monitoring risks.

Confirmation Bias No matter how much caution you take in your role as technical analyst, and no matter the quality of confirmation you locate, it remains possible to find exactly what you expect and to ignore all else. This confirmation bias makes trend analysis an uncertain science with many pitfalls along the way. There is the tendency “for people to seek information and cues that confirm the tentatively held hypothesis or belief, and not seek (or discount) those that support an opposite conclusion or belief.”6 In chart reading, confirmation bias translates to a tendency to see specific patterns that confirm reversal or continuation, even when the pattern is not strong or is not actually present. A study of confirmation bias produced several primary results, including location of price patterns that validated their trading strategies, even when legitimate forms of those patterns did not exist.7 This conclusion is profoundly disturbing, especially to anyone who is sincere about tracking price trends. Who is vulnerable to confirmation bias? How can it be guarded against? The answer is reliance on a set of confirmation signals that conform to strict standards. These include: 1. A confirmation signal must validate an initial reversal or continuation signal in proper placement within an existing trend. 2. The signal is considered strongest when near resistance or support. 3. An especially strong trend preceding the initial signal and confirmation is granted more validity than a marginal, short-term, or weak preceding trend. 4. Whenever confirmation signals are questionable in terms of strength, or when divergence also exists, the best course of action is to discount the value of confirmation; at such times, investors should rely on longer-term trends and wait for stronger indicators. The danger of confirmation bias is not limited to finding the signal desired to fulfill trend expectations (reversal or continuation). Every investor and trader is vulnerable to specific trade errors. However, a larger problem, “escalation of commitment,” is a form of confirmation bias affecting a specific course of action. For example, a portfolio manager may be committed to populating a permanent portfolio with stocks having specific attributes, such as recent history of high bullish movement. However,

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as the market conditions evolve, those very stocks might turn out to be the most vulnerable to reversal and participation in a bear market. Key Point: Confirmation bias misleads all investors. Once a reversal signal is spotted, a close call looks more like confirmation when it is in fact a weak or even coincidental price pattern.

An investor or manager overly committed to an aggressive strategy might not recognize the error, therefore, “confirmation bias” not only prevents recognition of the high risk but could even create the escalation of commitment making matters worse. So, instead of diversifying the portfolio to move away from high-risk positions, the manager tends to increase similar positions in the belief that the overall strategy will eventually work out. This is a set of behaviors broadly called “cognitive dissonance.” The tendency has been compared to an individual with a weight problem who enjoys eating doughnuts. Seeking conformity between reality and expectations may lead to four types of behavior: 1. Change behavior or cognition (“I will not eat any more of this doughnut”). 2. Justify behavior or cognition by changing the conflicting cognition (“I’m allowed to cheat every once in a while”). 3. Justify behavior or cognition by adding new cognitions (“I’ll spend thirty extra minutes at the gym to work this off”). 4. Ignore or deny any information that conflicts with existing beliefs (“This doughnut is not high in fat”).8 Cognitive dissonance in portfolio management is potentially a severe problem if the manager does not recognize the flaw in thinking. This begins with confirmation bias and could easily evolve into escalation of commitment, even to a failed strategy. Many theories expanding on this idea, or contradicting it, attempt to rationalize human behavior. However, most investors who have experienced both profits and losses recognize confirmation bias as a force in decision-making. Becoming committed to a favorite type of stock or a specific company, to a strategy (stocks selected based on high dividend yield, recent primary bull trends, or stocks with rising revenue and earnings history, for example) may lead to subsequent losses when strategies are subject to different market conditions. No one is immune to error, but analysts may be able to modify their behavior upon realizing that their past assumptions do not apply to all markets or to all strategies. It may be that an investor experiencing a period of successes may come to believe that a strategy is “foolproof.” This belief is likely to continue until it stops working. At that point, the analytical investor will reevaluate previous assumptions and modify them, but some people will ignore the evidence and continue a high-risk course. This approach is seen among investors and managers unable to accept their own flawed thinking as the underlying cause for losses. It only makes sense to approach the situ-

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ation by acknowledging confirmation bias on many levels (individual confirmation in a single trade, selection of strategies, and design of a permanent portfolio) and take steps to overcome the blind spots. The tendency to develop this bias explains why many portfolio managers rely on input from several sources rather than a singular source for decisions. Key Point: Once an investor starts believing a particular “system” is foolproof, the groundwork is laid for failure, perhaps even catastrophic failure.

Individual investors do not have the luxury of consulting with a team of experts and therefore must rely on their own self-analysis and ability to spot confirmation bias. Being able to change course upon discovering the bias is essential to avoid the escalation of commitment that often follows a period of losses. This escalation may be based on continuing to believe what has been shown to be untrue, or based on anger at having had losses due to various reason. Like an inexperienced chess player who tends to become aggressive after losing a key piece (when they should become defensive), every investor is going to experience losses, and some will be based on poor judgment from confirmation bias and other blind spots. These instances can be converted to learning experiences and avoided in the future. The purpose of confirmation is to reduce errors in the timing of trades. Confirmation bias is likely to negate the value of confirmation and lead to losses that could be avoided with objective analysis of confirmation on many levels: individual trades, selection of strategies, and long-term portfolio management. The most basic form of confirmation bias—looking for the “right” kind of confirmation and then finding it— means an analyst is likely to ignore the lack of clear confirmation and to fail to recognize divergence in its many forms. However, being aware of these potential blind spots is the best way to manage them in the future. By constantly questioning the strength or weakness of a confirming signal, accepting the instances where confirmation is not found, and looking for divergence, all help to maintain objectivity. To properly and accurately track and understand the characteristics of a trend, confirmation ensures that actions are taken only when evidence is strong. This requires the process of critical analysis, looking for and eliminating confirmation bias, and acknowledging a few facts. For example, confirmation does not always appear, and even when it does the confirming signal is not always strong enough to justify a trade (or to decide whether a trend is ending or continuing). Confirmation is relatively easy to spot when strong initial signals appear. A confirmation signal is likely to follow closely if it will develop at all. This is a relatively easy process in a strong uptrend or downtrend. However, during periods of consolidation, locating signals is difficult. Because no specific bullish or bearish trend exists, deciding when consolidation is ending may be among the greatest challenges in trend analysis. The next chapter examines how consolidation patterns develop and change.

Confirmation Bias 

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1 Berg, Milton W. “The Boundaries of Technical Analysis.” Journal of Technical Analysis, Summer/ Fall, no. 65 (2008), http://www.mta.org/eweb/docs/Issues/65%20-%202008.pdf. 2 Williams, Ray. “Emotion, Not Rational Logic, Determines the Stock Market.” Psychology Today (September 22, 2013) https://www.psychologytoday.com/blog/wired-success/201309/emotion-notrational-logic-determines-the-stock-market 3 Ton, Hoang Thanh Hue, and Trung Kien Dao. “The Effects of Psychology on Individual Investors’ Behaviors: Evidence from the Vietnam Stock Exchange.” Journal of Management and Sustainability, 4, no. 3 (August 29, 2014), http://www.google.com/ url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CB4QFjAA&url=http%3A%2F%2Fwww. ccsenet.org%2Fjournal%2Findex.php%2Fjms%2Farticle%2Fdownload%2F39897%2F22142&ei=rAxe Vc6HB8bYgwS3uoP4Cw&usg=AFQjCNEfo-1AKfwR0M5AcPoRJdTK0srGqw&sig2=F059xFPKJ5UhZLm J8mSynw. 4 U.S. District Court, Southern District of New York, SEC v. Goldman Sachs, 790 F. Supp. 2d 147 (S.D.N.Y. 2011) (No. 10 Civ. 3229), 2010 WL 1508202, filed July 14, 2010; and SEC Press release, “Goldman Sachs to Pay Record $550 Million to Settle SEC Charges Related to Subprime Mortgage CDO,” July 15, 2010. 5 Graham, Benjamin. “Factors Affecting the Buying and Selling of Securities.” (Testimony, 84th Congress, 1st session), March 11, 1955. 6 Wickens, C. D., and J. G. Hollands. Engineering Psychology and Human Performance, Third Edition. Upper Saddle River, NJ: Prentice-Hall, 2000, pp. 261–62. 7 Weller, Paul A., Geoffrey C. Friesen, and Lee M. Dunham. “Price Trends and Patterns in Technical Analysis: A Theoretical and Empirical Examination.” Social Science Research Network (August 2007) http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1010&context=financefacpub. 8 Festinger, L. A Theory of Cognitive Dissonance. Stanford, CA: Stanford University Press, 1957, p. 11.

Chapter 8 Consolidation Patterns; The Sideways Pause The technical term consolidation has a specific meaning: a sideways pattern of price movement within a limited breadth of trading in which neither buyers or sellers can move price to any significant degree. This period of indecision is a third type of trend in addition to the uptrend and downtrend. Consolidation trends take up as much time as uptrends and downtrends on many charts. However, with the focus of traders on dynamic price moves, consolidation often is ignored or discounted. A problem for analysts is in finding a clear signal that consolidation is coming to an end. Any valid signal must be located within the context of an uptrend or a downtrend; the only way to spot the end of consolidation is through identification of a successful breakout. Confusion is created by a widespread mixing of terms. Many books, articles, and online references consider consolidation an alternative term for continuation, but this is not accurate. A continuation signal often involves the shape, size, and momentum found within the trading range. For example, triangles, flags, and pennants are continuation signals that also contain consolidation of price represented by a narrowing of the range. Key Point: Consolidation is a type of trend moving sideways, rather than up (bullish) or down (bearish).

Continuation implies that the existing trend is likely to continue in the same direction. A consolidation trend and confirmation are valuable pieces of information letting you know that it is not time to close long positions (in an uptrend) or to enter a trade (in a downtrend). The continuation signal is a “wait and see” forecast. The confusion is aggravated by the many sources that confuse the two concepts. Many online and text sources can be found with the same confusion between continuation and consolidation. However, in analyzing stock charts, every analyst is aware of the problem of the sideways pattern, or consolidation. It is very difficult to determine when it is likely to end because the reversal and continuation signals, easily located in uptrends or downtrends, cannot exist in a consolidation pattern; and the period can last from a few weeks to a year or more. This chapter makes a clear distinction between continuation signals (technical signals forecasting that the current trend is not done yet) and consolidation (a period of sideways price movement, representing the inability of buyers or sellers to dominate price movement). There are several ways to recognize a likely end to consolidation based on volume spikes, gaps, repetitive signals after a breakout (including continuation), a plateau (or, pause) after a prior trend and before a new trend begins, and the Bollinger Squeeze.

DOI 10.1515/9781547401086-008

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Consolidation and its Meaning Consolidation is likely to be associated with, or part of, a correction or price movement against the direction of the primary trend. A correcting secondary trend may begin and then settle into a period of consolidation. The interruption in price movement is a natural part of the primary trend since the driving force (buyers in uptrends or sellers in downtrends) do not present unchanging levels of interest. Consolidation is a period in which all market participants pause to decide whether to close old positions, open new positions, or take no action. Key Point: Consolidation often is associated with price correction or rebalancing of supply and demand. However, the consolidation trend may last several months or even years, like any other primary trend.

Because price levels tend to settle into a narrow breadth of trading during consolidation, some traders view this sideways trend as less interesting than uptrends or downtrends. Some analysts refer to this as agreement between buyers and sellers that the narrow range of price is reasonable to both. However, by tracking the indicators within the consolidation trend, you may recognize early signals that a new trend is about to emerge. It is often true that once price breaks out of consolidation and starts (or resumes) a dynamic trend, price movement may be rapid and steep. The breakout after consolidation may act like a coiled spring whose tension has built up until it is finally released. Corrections are invariably described as countermoves of secondary uptrends against primary downtrends, or as secondary downtrends against primary uptrends. But overlooking the sideways correction is a blind spot because some dramatic price movement may follow this period once it has been exhausted. If consolidation is the result of approximately equal supply and demand, this makes sense; eventually one side or the other takes over. However, consolidation involves more than the supply and demand features of the market. It may include perceptions of current price as being the “right” price for a stock, affected by forces beyond supply and demand (competitive position, economic strength or weakness, or the influence of benchmark index movement, to name a few). Corrections are usually thought of as high-volatility periods, but only when they are limited to uptrend and downtrend movement. A correction evolving into sideways price movement (consolidation) has an opposite tendency, for low volatility and low volume, both in a time of narrow breadth of trading. The consolidation period begins showing signs of coming to an end when breadth of trading expands and when volume picks up, especially when it spikes. Beyond corrections, consolidation also replaces secondary trends. Rather than setting up an opposite price movement against the primary trend, a secondary trend can develop as consolidation. To many analysts, this is not viewed as a trend at all but

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as a pause between trends. However, when consolidation is treated as a secondary trend (moving sideways rather than opposite the primary trend direction) its analysis makes more sense. Most traders have a solid idea of how to react to secondary uptrends and downtrends (signals to look for, technical patterns, and confirming factors like momentum), whereas many have no idea how to anticipate the next price move once consolidation begins. The longer it continues, the less interested traders are likely to be in the sideways pattern. However, it is potentially as interesting as a secondary uptrend or downtrend because, like those dynamic trends, consolidation will eventually end, and the signals can be spotted in advance. A consolidation period is called a time of indecision, implying that it is not a trend. However, if uptrends are characterized as a time of optimism dominated by bulls, and downtrends are a time of pessimism dominated by bears, then indecision is a natural time of balance between the two sides. The “indecision trend” is just as much of a trend as an uptrend or downtrend, and it presents its own set of challenges in analysis and forecasting.

Resistance and Support as Keys to Consolidation Reading As with all types of trends, resistance and support are essential ingredients to understanding the nature of consolidation and to identifying when the period of consolidation is coming to an end. The uptrend and downtrend end when reversal patterns appear, but without any movement within the consolidation trend, the signals must take a different form. This is where the breakout is the key to tracking consolidation. Key Point: A breakout from consolidation succeeds only if a new dynamic trend is then established. Some breakouts simply retreat and consolidation does not end.

When traders do not react to consolidation as a form of trend, they easily overlook the role of breakouts. However, as in uptrends and downtrends, the breakout is a red flag and should be tracked carefully. It signals a failure and retreat, often leading to a successful breakout in the opposite direction; or it signals a success and new trend with a higher or lower trading range. In either case, the end to consolidation is possible and at times likely. With the power of resistance and support in mind, identifying breakout from a consolidation trend requires the same patterns you find in breakouts from uptrend or downtrend: volume spikes, price gaps, strong signals, and equally strong confirmation. It is also useful to locate multiple signals after a successful breakout—either showing likely reversal or continuation—since the lack of a preceding dynamic trend makes identification more difficult. Thus, price signals are needed to ensure that the newly established trend is not likely to reverse.

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Reversal itself needs to be defined for the purposes of consolidation in a different manner than in a dynamic trend. Reversal usually means a change in direction from up to down or from down to up. However, in consolidation, it is sensible to think of reversal as a change in the trend from consolidation to bullish or consolidation to bearish. Once this new definition has been accepted, reversal signals make more sense. If analysis is fixed on the idea that reversal refers solely to direction of price movement, it is impossible to spot how price breaks out of consolidation. If reversal of a current trend is the accepted definition, it makes sense to look for change in the sideways movement to a dynamic movement (bullish or bearish) as an alternative definition of “reversal.” In that case, the trend is reversed from consolidation to dynamic. As reversal signals appear in conjunction with a breakout, the pattern takes on significance and can by studied as a true signal of a change (reversal) in the consolidation trend. Breakout is always notable, no matter which kind of trend is in play. However, consolidation is a particularly difficult trend to escape. With equal levels of control shared between buyers and sellers, a strong breakout is not easily accomplished. However, the consolidation trend can be characterized by different attitudes, and these may also determine the direction of a breakout. These attitudes may be: 1. Pause in an existing trend, in which the dominant side (buyers or sellers) settle out the factors that prevent the trend from moving in a straight line. In an uptrend, this pause might be the result of profit taking and in a downtrend it might be a consequence of nervous investors cutting losses. The distinction between a consolidation of short and long duration often is found in comparisons of the breadth of trading. If the breadth narrows considerably between a previous dynamic trend and the sideways movement, it could be a pause; if the breadth remains unchanged, the consolidation could be caused by other factors. In a pause, the breakout will be a continuation in the same direction as the previous trend. 2. Uncertainty about which direction price will or should take next. This is the most popular explanation for consolidation. It generally implies that both sides are not confidant enough about their ability to continue moving price. In a larger sense, it could reflect uncertain fundamental trends. A company that has been growing steadily may have also had a growing price trend; but once the revenue and earnings growth slows down, what does that mean? Is the stock still priced fairly or has it become overpriced? A study of trends in the annual range of P/E ratio in conjunction with the revenue and earnings trends could hold the answer. This could be the most difficult form of consolidation to analyze since the breakout and new trend that eventually occurs could move in either direction. Uncertainty will end only when both sides reach consensus, meaning one side takes the reins and the other side concedes.

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3. Agreement between buyers and sellers that the current breadth of trading is fair. In this situation, a breakout is most difficult because the fundamentals probably support the price range based on earnings per share and as reflected in the P/E ratio. The “agreement” consolidation could last several months compared to the pause and uncertainly varieties that are more likely to last only a matter of weeks.

The Triangle Breakout The triangle is a bullish continuation signal in a dynamic trend. The ascending triangle forecasts upside breakout and a descending triangle forecasts downside breakout. The symmetrical triangle often is found during consolidation as the breadth of trading narrows with the outcome possible in either direction. Key Point: The triangle within consolidation takes on great importance. Any form of narrowing breadth of trading in consolidation points to a likely end of the sideways trend.

The shape and meaning of triangles were examined in detail in Chapter 3, which was focused on resistance and support as notable in uptrends and downtrends. However, in consolidation, triangles also play a role in forecasting breakout. Here, as with many patterns, the ideas of continuation and consolidation have been confused by many traders and analysts. It is true that triangles are continuation patterns and may occur within consolidation trends. When they do, they are early signals of likely breakout in the indicated direction (ascending leading to upside breakout and descending leading to downside breakout). The symmetrical triangle is of the least value in the consolidation because, even though forecasting breakout, it does not tell you which direction. The ascending triangle consists of a level resistance and rising support. This may occur within a longer-term consolidation pattern like the one shown in Figure 8.1.

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breakout

Source: Chart courtesy of StockCharts.com Figure 8.1:  Ascending triangle in consolidation

The consolidation began in mid-September 2013 and did not end until the breakout. The consolidation lasted a total of thirteen months. The dilemma for an analyst is identifying the pattern leading to breakout. Since the preceding primary trend was bullish, the ascending triangle works as a deferred continuation pattern within the period of consolidation. A consolidation trend lasting seventeen months is seen in the chart at Figure 8.2. The consolidation began in April 2013 and extended to the end of the descending triangle in late September 2014.

breakout

Source: Chart courtesy of StockCharts.com Figure 8.2: Descending triangle in consolidation

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The descending triangle began at the start of July and concluded in late September; the last five months of consolidation included this bearish continuation pattern. The previous trend was bearish, lasting from September 2012 through June 2013, a total of nine months. The identification of the descending triangle as continuation is appropriate. However, there are two different issues involved in this chart. First is the prevailing downtrend, which is easily spotted. Second is the period of consolidation with considerable duration, including the continuation pattern in the form of the descending triangle. In this case, the continuation is deferred many months after the initial downtrend moved into consolidation for over a full year. The consolidation trend could be called a primary trend, with the triangle not so much a continuation of the downtrend occurring a year before but signaling the end of consolidation. Key Point: The frustration with consolidation trends is in the difficulty of identifying change. With no dynamic trend to reverse, no reversal signals can form.

In this type of pattern, a continuation pattern like the triangle is not clearly serving as continuation of the previous trend but is acting more like a signal that the current consolidation is concluding.

Volume Spikes and Gaps Finding repetitive patterns on charts is reassuring as it raises confidence in what appears to be occurring. A good example is the combination of two of the most powerful signals: volume spikes and gaps. Figure 8.3 provides an example of an interesting repetitive pattern of consolidation and breakout.

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gaps

gaps spikes

spikes

Source: Chart courtesy of StockCharts.com Figure 8.3: Volume spikes and gaps

On the chart in Figure 8.3, the overall volume levels were low (relatively) for most of the period, with distinct volume spikes occurring at the same time as breakout gaps. The first volume and gap combination led to an upside breakout and then an eleven-month consolidation. It concluded with a downside gap and volume spike, taking price back to the range a year earlier. In this formation, the support formed during consolidation flipped to resistance, which rapidly descended from there. The next volume and gap combination occurred after a pause consolidation of three months duration, from February to April 2014. This was clearly a pause in the downtrend, confirmed by the narrowing of breadth to only 2 points. The previous consolidation’s breadth was 5 points and the price decline that followed expanded to wider breadth as well. The final instance occurred as price declined and marked continuation of the downtrend. Although volume was higher than typical volume through the two years, it was a marked difference from the strong spike marking the price gap. This confirmed a likely continuation of the primary downtrend.

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Breakout Signals In every trend, including consolidation, you seek breakout signals of convincing strength to set up a new dynamic price move and new trend. However, because consolidation is normally the most difficult trend to escape, you may also need to locate multiple signals of move, reversal, and continuation, along with additional confirmation from other signals (such as volume spikes). Figure 8.4 is a two-year chart with a period of consolidation extended for approximately six months. A brief but revealing pattern emerged. Prices broke out above resistance and remained there for three months and then retreated into consolidation range before finally breaking and remaining above resistance in March 2014.

Source: Chart courtesy of StockCharts.com Figure 8.4: Consolidation leading to uptrend

An analyst would have to ponder the reasons for the price activity between September and December 2013, the period in which the consolidation trend was ending. The chart does not reveal any reasons for the move upward or whether the breakout starting in November would succeed. Key Point: In a consolidation trend, more so than in bullish or bearish trends, the problem is one of uncertainty—of duration, breakout success, and signal strength.

Breakout from consolidation is likely to be tested just like breakout from uptrends or downtrends. This chart reveals that in the entire month of January 2014, price did retreat into consolidation range but then moved strongly into a new primary uptrend lasting for the rest of the year. The key to understanding the breakout, test, and success was found between August and December 2013. This period is shown in Figure 8.5.

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bullish engulfing (reversal)

upside gap filled (continuation)

ort

p sup

bullish thrusting lines (continuation)

volume spikes

Source: Chart courtesy of StockCharts.com Figure 8.5: Uptrend signals

The chart in Figure 8.5 is a micro view of the larger chart, showing a slice of consolidation at the point of breakout, and the relevant signals that forecast this bullish move. The first event was the downtrend from mid-July through the end of August, a secondary trend of six weeks within the primary consolidation trend. Even though there was no primary trend to reverse in consolidation, a secondary trend did provide the kinds of signals needed to forecast the end of the trend. The downtrend bottomed out and immediately provided strong bullish signals. These consisted of two bullish engulfing signals in close proximity. Next came a two-week bullish swing trade accompanied by three volume spikes. This was very unusual, especially given the difference between these three consecutive spikes and the rest of the chart’s volume levels. A bearish swing trade followed but was quickly countered with another bullish engulfing signal. From this point onward, the new primary bull trend was underway. Two continuation signals confirmed this, thrusting lines and an upside gap filled. When the chart is viewed in a shorter time span and all the signals can be viewed, the breakout and new trend are visible and strongly communicated. In the previous chart, there was not enough detail to fully understand what signals forecast the breakout or why it succeeded.

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Consolidation Plateaus The tendency for consolidation is to act as either a pause between longer-term primary or secondary trends or to replace one primary trend with another. A consolidation primary trend is an idea often not appreciated by analysts and investors. Dynamic trends often move in stages, pausing periodically while investors decide whether to take profits or cut losses. Pauses may also be caused by earnings to be announced soon but accompanied by concerns that a surprise might be arriving as well. At such times, a wait and see attitude among buyers and sellers could lead to such a pause. Key Point: Some consolidation trends represent a form of secondary plateau or pause in the primary bullish or bearish trend.

A consolidation trend is at times a pause as well but it is more likely a legitimate primary or secondary trend marking a period between uptrends or downtrends. Just as some patterns move back and forth between bullish and bearish price movement, other patterns move back and forth between uptrends and consolidation, or downtrends and consolidation. These distinct patterns, in which consolidation may last many months, are plateau trends. Figure 8.6 provides an example of a chart with two plateaus. The first plateau lasted approximately eight months before an upside breakout led to a five-month uptrend. This was followed by a shorter-term consolidation plateau of six months before a downside breakout.

breakout

Source: Chart courtesy of StockCharts.com Figure 8.6: Consolidation plateaus

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Viewing these plateaus on a two-year chart provides a good broad view. But are these breakouts easy to spot in the immediate term? How do you know when consolidation is about to end and the direction price is likely to move? Figure 8.7 provides a narrow view of the first breakout, summarizing six months of consolidation. This chart demonstrates that toward the end of the plateau consolidation, clear directional signals emerged, led by the breakout above resistance.

three white soldiers (reversal)

breakout

por

sup

t

bullish thrusting lines (continuation)

Source: Chart courtesy of StockCharts.com Figure 8.7: 2013 plateau

The breadth of trading narrowed before this breakout. In the first half of the year, breadth ranged between $65 and $53; in the second half, it narrowed between $65 and $60, less than half the previous breadth. This was the first signal that consolidation was likely to end soon. By mid-September, a two-week uptrend had formed within consolidation, repeating one nearly identical a month before. These repetitive swing trends moving price from $60 to $65 resulted eventually in the breakout. But was this a true breakout? Moves above resistance (or below support) often fail, especially when the range has been so narrow for so long. The answer was found in two ways. First, in the second half of September, the prior resistance was tested but price never fell below that level. Then, in October, two reversal signals appeared, both three white soldiers patterns, quite close together. This was a strong set of signals indicating the start of a strong bullish run. Finally, the uptrend was confirmed with a bullish thrusting lines, setting the course for the price trend through the end of the year. Referring to the two-year chart, this bullish trend continued into April before settling back into a new consolidation plateau trend.

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This second plateau could have represented a pause in the uptrend or a plateau that could lead to a new downtrend. Figure 8.8 shows a consolidation plateau with a pattern very similar to the previous example of a plateau.

bearish doji star (reversal)

bearish side-by-side black lines (continuation)

breakout

three black crows (reversal)

bearish engulfing (reversal)

Source: Chart courtesy of StockCharts.com Figure 8.8: 2014 plateau

The plateau began in March and had a range of $115 to $95. The August and September breadth narrowed considerably to prices between $105 and $95, half the breadth of the first segment of the plateau. Key Point: Consolidation trends are challenging due to the absence of reversal, but other signals—like narrowing breadth—anticipate change soon.

The narrowing breadth was the first signal that consolidation was coming to an end. However, it did not provide a specific indication of the direction of a breakout. The daily breadth of sessions had narrowed considerably, gradually evolving downward but rarely moving more than two points in any session. Once price broke below $95—for the first time seven months—the likelihood of a successful bearish breakout was presented. Two bearish reversals, both three black crows, appeared immediately. Neither of these were perfect examples of the patterns but they were close enough to indicate that price was likely to continue moving downward. Next, two additional reversals appeared, both bearish engulfing patterns. Finally, after price continued sideways for another three weeks, a bearish doji star completed the reversal cycle. These reversal signals—five in all—are examples of multiple confirmation needed to confirm that the consolidation trend has ended. A final signal was a bearish sideby-side lines, a continuation pattern. This busy chart was characterized by a lot of uncertainty. The period between the breakout in October and the final reversal signal

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in November could be characterized as a two-month consolidation trend, but it is more reasonable to identify it as the beginning of a new downtrend with residual uncertainty. This uncertainty dissipated over the two months with repetitive bearish reversal signals before finally moving down below $70 per share.

The Bollinger Squeeze The tendency for breadth of trading to narrow as consolidation ends is a variation of the triangle. This continuation signal in its various forms (ascending or bullish, descending or bearish, and symmetrical, either bullish or bearish) are additional forms of narrowing breadth; however, these patterns are more often seen in uptrends and downtrends. In a similar way, the pennant is a short-term symmetrical triangle that may reflect a coming reversal or merely a retracement of the current trend. However, pennants (and flags) are not associated as much with consolidation trends. One form of this narrowing tendency that often leads to strong breakout signals is the Bollinger Squeeze. Key Point: Narrowing breadth often is a key to the end of consolidation. The Bollinger Squeeze is a reliable pattern anticipating breakout.

Bollinger Bands were discussed in detail in Chapter 2 and are revisited here as part of the analysis of consolidation. Figure 8.9 shows a one-year chart with the squeeze highlighted.

breakout

narrowing band width

Source: Chart courtesy of StockCharts.com Figure 8.9: Bollinger Squeeze

broadening band width

price above upper band

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 197

The six-point range characterizing this period of consolidation narrows to less than two points in the month of September. Although the period of this narrow breadth is a small part of the chart, it lasts for most of the month. The squeeze reflects low volatility in anticipation of high volatility and, in consolidation, possible breakout. The Bollinger Bands width narrows, both the upper and lower, as price tests resistance, retreats to support, and finally breaks out on the top quite strongly. The success of the breakout is confirmed by the last two weeks in November when the upper Bollinger band is violated by price; and at the same time, the lower band declined far below. This reflects the averaging effect of consolidation, versus the upsurge. Taking a closer look at the breakout period, a strong bullish reversal is followed by an equally strong confirmation, both containing price gaps. These are shown in the six-month chart of the same stock in Figure 8.10.

bullish side-by-side white lines (continuation) morning star (bullish reversal)

breakout

Source: Chart courtesy of StockCharts.com Figure 8.10: Breakout reversal and continuation

As price tested resistance and then retreated down to the level of support, a bullish morning star reversal signal formed. This included a large price gap and immediate turnaround in price direction. Although this pattern occurred at the end of consolidation, the large breadth and price movement in the three sessions of the morning star provided a strong signal that a bullish breakout and new trend was likely. This was confirmed a month later by the gapping continuation signal in the form of a bullish side-by-side white lines pattern. By the conclusion of the period charted, Bollinger Bands returned to a closer tracking of price, notably the upper bands. The typical breakout tracked by Bollinger Bands occurs after the squeeze, with bands widening as the breakout occurs. This example is an exceptionally strong one because the initial upper move, followed by a downward move, sets up the bullish trend to follow. The key element of this sudden volatility was the failure of price to

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fall below support just below $72 per share. After the morning star, price fell back into a narrow range of less than 1 point for two weeks before the trend strengthened. However, the difference between this narrow range and the previous consolidation’s narrow range was the Bollinger Bands. In consolidation, the Bollinger Bands tracked price very closely; in the late October period the distance between price and both upper and lower bands was considerable. This signaled that price was not likely to remain in the previous consolidation range. In this case, Bollinger Bands was the determining factor in coming to this conclusion. Key Point: Bollinger Bands width is a key to identifying consolidation trends and when they are likely to come to an end.

Helping in the analysis of consolidation breakout is a related indicator called the Bollinger Bands width. This is the distance between upper and lower bands. At the end of July, the band width was only 4 points. However, once the squeeze set in by the end of September, band width had cut in half to only 2 points, a strong indication that the squeeze was underway. After the morning star, a big change occurred as band width moved to 5 points in a matter of one week; and during the uptrend, it was as much as 12 points. Expressed as a percentage, a 4-point band width at average price of $75 per share is only 5 percent; and a 2-point band width with average price at $77 is 2.5 percent. The breakout band width of 5 points with average price at $76 was 6.5 percent; and finally, a 12-point band width with average price at $81 was nearly 15 percent. Another technical read on the strength of the reversal in mid-October was location of price within its trading range. With price falling to about $72, it was at its lowest point since the previous March, or seven months prior. Any time price is located at its six-month (or longer) low during consolidation, an upside breakout is likely. By the same argument, when price is at resistance and at its high for six month or longer, a bearish breakout is likely. These generalizations point to a problem with the Bollinger Squeeze. It anticipates breakout but does not provide direction. For this, you need to find confirming signals. On this chart, the upside breakout occurring after the morning star (and confirmed by the side-by-side white lines) was convincing evidence that the breakout had succeeded. The initial confirmation of the bullish reversal candlestick (widening Bollinger Bands and band width) could be enough of a signal to trade on this stock. If so, it could be bought at approximately $76. Waiting for the additional confirmation in mid-November would have meant buying at about $82, meaning the entire bullish trend would have been missed. As things turned out, price did not continue rising above the ending level between $81 and $87 and by March 2015 had begun declining in a new bearish trend. If Bollinger Bands and the Bollinger Squeeze are used as confirmation at the point of breakout, a trade can be made in a timely manner, as consolidation ends.

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 199

One potential problem in relying on breakout as a confirming signal is what has been termed a “head fake.” This occurs when price moves above the upper band (as in the first two weeks of October), but then retreats back below the band. This also occurs on the downside when the head fake takes place below the lower band only to reverse back above the zone between the bands. This bull trap or bear trap formation occurs with promising signals, but it emphasizes the importance of confirming signals. Key Point: In consolidation trends, false indicators can lead to poorly timed decisions. The solution is to act only when strong confirmation is present.

Continuation is a difficult trend to break because it represents agreement between buyers and sellers about the breadth of trading. The standoff may last a few months or a year or more, in which case consolidation becomes a primary trend. Bollinger Bands and the Bollinger Squeeze are very useful in managing price movement and in recognizing the difference between a true breakout and a head fake. The next chapter introduces one of the strongest forms of signals (whether initial or confirmation), represented by volume. Beyond the volume spike, several calculated indicators provide excellent signals of coming price trends and changes.

Chapter 9 Volume Signals: Tracking Price Trends Volume is often viewed only as an indicator to confirm price signals or to be used only in swing trends. However, volume can provide much more, including signals and divergence for longer-term trends, such as spotting the end of uptrends, downtrends, and consolidation. Divergence is one concept that applies in many volume indicators. You expect to see volume increase as price movement accelerates. But what does it mean when volume contradicts price? In many instances, divergence should not be ignored; it could reveal that the trend currently underway is likely to end soon. This is where confirmation bias plays a role. If you find a reversal pattern, for example, the tendency is to look for signals that agree. This bias may ignore divergence because it provides a contrary signal. Key Point: Volume signals tend to confirm price but may also offer divergence. This predicts the end of a current trend.

In this chapter, volume indicators are described and shown on charts, both for confirmation and divergence. Any signals accompanying price add to your confidence level and may improve your overall trend tracking abilities.

How Volume Confirms Trends The first issue to address is whether a current trend is likely to continue. One approach to trend analysis is not to take action until a signal appears forecasting reversal. However, by the time you find and confirm this reversal, it might be too late to time a trade profitably. Volume signals can be used as a confirming signal, providing confidence that the trend is not likely to end in the immediate future. With price analysis taken by itself, it often is difficult to decide whether the trend is strong or weak. Just because price is moving in one direction with strong momentum, it does not tell you whether it is due for reversal. Every investor knows that prices tend to overreact to immediate news, and that exaggerated price movement gains momentum on its own even when not justified. However, when the price pattern is viewed along with volume, the body of information is more complete. In a sense, price is only half of total trend analysis. You also need to see confirmation of trend movement in what takes place in volume. At times, volume is a better indicator than price for shifts in supply and demand. When price movement becomes extreme (meaning greed takes over near the top of an uptrend and panic dominates the bottom of the downtrend), it is not always easy to DOI 10.1515/9781547401086-009

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track the trend and find signals to identify the true price peaks. At such times, price reflects supply and demand, perhaps to an irrational degree; but volume identifies the strength or weakness of these forces and shows when one side shifts to the other (forecasting a change in direction for price as well). This solves the all too common problem of timing for fast-moving reversals. With price alone, the reversal may be spotted when it is too late to time trades. With volume, often acting as a lead indicator, the likely reversal is spotted earlier. Most technical indicators lag behind price or occur at the same time; but volume is more often a leading indicator. Volume signals also track large block trades by institutions. So smaller institutions or individuals may spot short-term volatility in price and not understand what it means. But volume reflects trading in the number of shares, so it provides an accurate tracking mechanism for most of the market, represented by institutional and high frequency traders (HFTs). This is where most of the volume occurs, with HFT accounting for at least 50 percent of all trades in the United States.1 The problem of HFT activity is not limited to volume of trades but may also include manipulation of stocks prices. In 2014, the Securities and Exchange Commission (SEC) levied a $1 million fine for rigging prices “of thousands of stocks including eBay Inc. for at least six months in 2009.”2 Key Point: High frequency trading dominates market volume, which also brings into question whether changes in volume are valid signals or merely creations of HFT.

The problem of price manipulation is a serious one and, given HFT activities, it might become worse in the future. However, as a separate issue, trend analysis is not as much concerned with why a trend develops but how long it will last, how far it will move, and when it will end. Focusing on this aspect of the question, volume reveals as much as price, notably when high levels of trades occur in short time periods, including the fast-paced HFT trades that present a problem for the modern, fast-paced algorithmic trading platform.

Confirmation Trends with Volume A stock’s price trend, when confirmed by volume, is easy to spot. Price movement, along with rising volume signals, indicates strength, and when volume falls, it indicates that the trend is weak or getting weaker. When the two disagree, trend analysis takes on a more interesting form. However, the most basic relationship between price and volume is agreement concerning price and volume of trades. Figure 9.1 demonstrates how this works. This stock was undergoing a primary bullish trend through the two years shown in the chart, and throughout, strong price surges were confirmed by volume.

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 203

prior resistance new support

Source: Chart courtesy of StockCharts.com Figure 9.1: Rising volume and rising price

The primary trend was marked clearly. The first upward surge lasted for five months and was mirrored by rising levels of volume, culminating in a two-session volume spike. The second significant event was the price breakout above resistance, also mirrored by rising volume up to a spike following the breakout. This breakout also created a flip from prior resistance to new support, a particularly strong confirmation of the uptrend’s success. Two additional surges in price were accompanied by volume surges and smaller spikes. Finally, volume settled to relatively low levels as prices continued to hold above support in the later portion of the chart. This represents a settling down of both price and volume. In other words, both price and volume proceeded without the repetitive volume spikes, so volatility was also reduced. A subtle but key attribute of these volume surges was that they acted as leading indicators. This was crucial in the surge taking place as price moved above prior support, a point where the continuation of the uptrend was by no means a certainty. The combined price and volume surge increased confidence in continuation on this chart. The same mirroring of price by volume also occurs in downtrends. When a downtrend is accompanied by rising volume, it indicates strength in the trend; however, when volume begins to decline, look for confirmation that the trend is weakening and might be due for reversal or consolidation.

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Trends with Volume-Marked Breakouts Volume often marks changes in the trend other than reversal or continuation. There are times when unusual price patterns and volume spikes together. This should draw your attention by revealing that something in the trend has changed. For example, the chart in Figure 9.2 shows specific instances of price peaks.

breakout

failed breakout

Source: Chart courtesy of StockCharts.com Figure 9.2: High volume at price peaks

Large volume spikes appeared, which signaled some type of change in the current trend. It is easy to assume that it always marks reversal, and once price gapped down and back into the previous range with another volume spike the assumption would make sense, but as this chart reveals, only the first volume spike was accompanied by a breakout; the rest were failed breakouts based on rising resistance (in October 2013 and March 2014) and support (in June 2013 and January, March, and October 2014). Key Point: Volume spikes are associated with breakouts, but this does not mean the breakouts succeed consistently.

Another repetitive pattern is a combination of high volume immediately before price dips to low levels. This activity often is accompanied by gapping price movement and may either mark a coming reversal or confirm the existing trend. To determine the meaning of high volume at price low levels, recognize the volume spike as an initial indicator and then seek other indicators. The volume spike often is one of the strongest

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 205

reversal signals, so look for breakout price movement, reversal, and the trend in both resistance and support to decide what the volume and price pattern foreshadows. An example of a chart with numerous volume spikes at the point prior to price dipping to low levels is found in Figure 9.3.

breakout below support

breakout above resistance

gap to move lower

test of resistance and gap

new resistance gap to further low

new support breakout below support

move to lower low

Source: Chart courtesy of StockCharts.com Figure 9.3: High volume before price lows

This chart in Figure 9.3 displays remarkable consistency. At each volume spike, a decline to a lower price occurred. All of these price moves were accompanied as well by gaps. This implied that volume and price gaps are related. This is not always the case, but the combination of the two does add strength to what the pattern revealed. The first instance involved price flipping from previous support to new resistance. Once new support was established after the second volume spike and price decline, it lasted for eight months, from June 2013 through January 2014. The third and fourth volume spikes moved price even lower and set up a new resistance, which held for eleven months, from December 2013 through October 2014. In September, price tested resistance but then gapped lower as the volume spike appeared. The last instance had price declining from resistance and then gapping above resistance for what appeared to be a new bullish price move. In fact, price did move to the mid-$50s by March 2015. This pattern—volume spikes with decline to low price levels—provided a clear view of how price momentum works in conjunction with volume and how the two often are found as resistance or support and confirmed and then broken. Another interaction between price and volume was found when volume spikes after a breakout above resistance or below support. This normally forecasts a failure

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in the breakout and return to established range. However, it also is found in many cases of flips from resistance to support or from support to resistance. Key Point: When volume spikes occur after breakout, it may predict a failure and later return of price into the previously establish range.

Figure 9.4 presents a chart with examples of both failed breakouts and flips from one breadth limit to the other.

resistance

support

resistance support

support

Source: Chart courtesy of StockCharts.com Figure 9.4: High volume after breakout

The chart in Figure 9.4 is yet another example of consistency in volume-related patterns. When volume spikes appear after breakout, one of two events is likely to occur next. The most frequent event is a retreat into the established range; this occurred in the first and second instances of breakout and volume spike. In March 2013, support was tested at the time of a downward gap and volume spike, but it retreated into range immediately. A second support test followed in late August. However, the pattern is not always going to occur. For example, in late May price broke out above resistance for less than two weeks and only a small bump in volume occurred, not big enough to be defined as a spike. The third breakout was interesting as it represented a flip from resistance to support. It was a strong move and support held. The fourth breakout tested support twice while volume spiked once again, but the level held. The next instance repre-

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 207

sented yet another flip from resistance to support and contained both a price gap and a volume spike with support level holding. The last spike on the chart was the strongest one. This set up an interesting new bullish move in the stock. By mid-March 2015, the price had advanced another 10 points to the mid-130s and set up support at $113 per share. This was yet another example of a long-term primary bullish trend with support rising three times in November 2013, May 2014, and December 2014. This is an example of the plateau pattern seen in many primary trends; by establishing ever higher levels of support (or in bearish trends, ever lower levels of resistance), the trend becomes stronger. In comparison, a trend that moves relentlessly in one direction without pause should cause concern because a reversal is likely to be sudden and extreme. Just as high volume following breakout indicates strength in the prevailing trend, low volume after breakout tells you the opposite, that the trend is weak or weakening. An example of this pattern is seen in the chart at Figure 9.5.

breakout

resistance

resistance

support

breakout

low volume

declin

ing vo

lume

low volume

Source: Chart courtesy of StockCharts.com Figure 9.5: Low volume after breakout

On the chart in Figure 9.5, the long-term trend began with a weak bullish move. As price moved above resistance in early May 2013, volume spiked, but it immediately retreated to a three-month low volume trend while price met resistance at approximately $36 per share (and began rising from there). A breakout above resistance lasted only about six weeks. After the retreat, volume declined strongly, revealing that a lasting bullish trend was not likely. A final breakout below support at the beginning of October was also followed by a failed attempt

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at a bearish move and price returned into range. This also marked the beginning of a consolidation period lasting into March 2015. A repetitive pattern was found after each breakout. Not only was volume low or on the decline, but big moves occurred at the same time. These breakouts all failed, but there was a common element to them. The low volume revealed overall weakness in the breakout itself, and ultimate failure of each instance forecast that consolidation was likely to continue far ahead. Given the overall weakness in the long-term primary trend, even with the small increases in trading range (from mid-$20s to mid-$30s over two years), the consolidation period that followed portrayed the company’s technical trends as weak. Key Point: Low volume indicates weakness of breakouts often seen as a symptom of weak primary trends.

When long-term technical weakness is found (e.g., long-term bullish trends that move only slightly) the problem often can be traced back to weak fundamentals. In the case of GM, this is true. Over the four years through 2014, revenues were up each year, but net profits were down, a very disturbing trend. In the same period, the debt to total capitalization ratio (long-term debt as a percentage of total capitalization) rose each year, tripling from 6.6 up to 18.4 (The long-term debt to capitalization ratio is a percentage, but is reported numerically and without percentage symbols. In this case, the conclusion was that debt represented 18.4% of total capitalization by the end of the period.) Overall, both fundamental and technical trends were weak and declining.

Trend Climax and Gap Patterns A trend climax is likely to be accompanied by volume spikes or surges, as well as by long days (broad trading range within a session), gaps, and strong reversal signals. The trend climax often sets up exceptionally strong reversal signals and confirmation. For example, the chart in Figure 9.6 covers two years and highlights several features: a six-month flip from resistance to support, then back to resistance; a volume surge; a downtrend climax with a very strong volume spike; and then a return to very low volume and rising prices. The two-year period was a primary bull trend.

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ce

resistan support ce resistan

downtrend climax reversal signal: volume surge

Source: Chart courtesy of StockCharts.com Figure 9.6: Trend climax: two year chart

Even though this was a bullish trend over two years, there were several overall weakening signals. First, the downtrend climax itself indicated bearish pressure on the trend. Second, after the volume surge, the continuing uptrend was accompanied by exceptionally low volume. This could indicate that the uptrend was exhausted. In fact, by March 2015, the trend had reversed, and price declined to under $14 per share, a fall of about 25 percent from the high on December 31. The trend climax does not always lead to strong continuation but might also be an early warning that the current trend is losing momentum. A look at the six months between April and September in Figure 9.7 shows how the downtrend climax was anticipated in reversal and confirmation signals, concluding with very low volume and the end of the uptrend with narrowing range in sessions.

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new resistance prior support

three white soldiers (reversal)

downtrend climax

trend

double bottom and bullish piercing lines

bullish thrusting lines (confirmation)

e

surg

Source: Chart courtesy of StockCharts.com Figure 9.7: Trend climax: six month chart

A closer look at the period surrounding the downtrend climax revealed a series of signals that explained what occurred and why the primary trend reversed in 2015. The downtrend climax occurred at the point of the volume surge culminating with a strong spike. This represented the bottom of a bearish secondary trend and was marked by a double bottom that also formed a bullish reversal in the form of a piercing lines signal. Even with the strong bullish signal, price did not move much after until the three white soldiers appeared, setting up a clear bullish move. This was confirmed with the bullish thrusting lines continuation signal. Key Point: Even after strong volume signals and equally strong confirmation, price reaction may take time. Delays in response are not uncommon.

However, the reversal and bullish trend did not last long. By the end of the period, volume had declined to the lowest levels on the chart, and daily price movement also narrowed. This change and growing weakness in the combined price and volume anticipated the downtrend that followed in 2015. The uptrend shown on the chart in Figure 9.7 carried prices higher through to the end of 2014, but the weakness revealed that the trend would not move any further. Volume spikes often are also marked by price gaps. At times, these consistently mark spots where resistance or support are tested or where retracement begins. A volume surge leads to a gap, then a brief retracement, and finally continuation of the trend. With the location of additional signals, a change in the slope of resistance

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or support may also mark the point of reversal. For example, the chart in Figure 9.8 contains seven volume spikes accompanied by gaps, all of which have significant meaning for the trend.

resista

nce

support

descending triangle

Source: Chart courtesy of StockCharts.com Figure 9.8: Volume spike with gap

The first two spikes represented continuation with confirmation in the form of retracement moves appearing immediately after the spike and above the gap. In early September, price began consolidating in a four-month trend, representing either a pause in the uptrend or the point where the trend has ended. The outcome turned out to be the end of the trend, with the final upward price move located in early February with a volume spike and gap. The price moved briefly above $100 marking the top of the uptrend. A new support level was set at approximately $55. This was tested in early May with a downside gap and volume spike; however, price returned into range. At the same time, resistance—starting at the peak of $100 per share—began declining through to the end of the period shown. This was tested briefly at the beginning of September. The last volume spike was the largest on the chart and it was accompanied with a price gap yet again. The combined level of support and declining resistance formed a descending triangle forecasting a new downtrend. This forecast was accurate. By late March, price had declined to about $44 per share, moving below the level of support shown on the chart. Throughout the two-year period, the signals were clear, all consisting of volume spikes and price gaps. The three retracements led to a peak in the uptrend and from

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there prices began a new primary downtrend. The chart was split between the primary uptrend and the start of the new downtrend. Each significant point was marked with visible signals. The first three consisted of volume spikes, gaps, and retracements moving above the price level that became new support and marking the top of the uptrend. Following tests of both support and resistance, price formed into a descending triangle anticipating the downtrend that followed. The chart in Figure 9.8 is an example of how volume accompanied price to first track a trend over a full year and then to lead the downtrend that followed. It is one of the ways in which volume spikes confirm what price patterns reveal.

On Balance Volume Beyond the volume spike, several calculated volume signals aid in interpreting the trend. First among these is on balance volume (OBV). This is among the most popular of volume indicators, providing the greatest value when the indicator moves opposite the direction of price. This forecasts weakness in the prevailing trend. OBV was first introduced by Joseph Granville.3 OBV calculates the daily levels of accumulation and distribution in volume. In a day when prices move upward, that day’s volume is added to the previous sum of volume; and when the day’s price declines, that day’s volume is subtracted. This is a simple equation, but it also points out a flaw in OBV. The calculation makes no distinction between a session moving slightly versus a session that moves many points. In both cases, up-day volume is added and down-day volume is subtracted. Key Point: OBV is a popular volume indicator, but it makes no distinction between big moves and small moves in either direction.

The observation analysts make about OBV is that it may confirm potential breakout moves. Rising OBV may accompany moves strong enough to break above resistance, while falling OBV warns about potential breakout below support. However, OBV is most valuable as a confirming indicator when price proximity is at the critical stage, close to resistance on the rise or close to support on the decline. This is where moves in OBV in the same direction confirm what appears to be a breakout that may be about to occur. Because OBV is based on price moves, it is not always valuable as a directional indicator, even when confirming stronger price patterns. However, OBV becomes more valuable when it represents divergence from price. A declining OBV during a period of rising prices, or a rising OBV when prices are falling, foreshadows reversal. OBV provides a signal of this, but independent confirmation is essential before accepting divergence as a certainty.

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An example of divergence in OBV is shown in the chart in Figure 9.9. In this chart, the first four months reveals a price decline while OBV rose. The change from downtrend to uptrend is marked with a peak on OBV and a price gap to the upside.

rt

po

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tance

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diverg

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rgen

ce

Source: Chart courtesy of StockCharts.com Figure 9.9: On balance volume (OBV)

The uptrend took off in July with a test in November and December. The warning signs that the trend was losing strength were found in OBV, which began declining in mid-September. At this point, it could not be known whether the end of the uptrend would lead to a downtrend or to consolidation. As it turned out, price did consolidate through March 2015, with a price range between $50 and $53. In this instance, the first example of divergence led to a strong reversal and the second instance warned of the end to the uptrend, leading to a consolidation trend.

Accumulation/Distribution The flaw in OBV is that it makes no distinction between large and small price moves. All are treated the same. Another volume indicator, accumulation/distribution (A/D) corrects this flaw.

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A/D considers the range of price for each session so that the daily change in the A/D index is adjusted to show bigger moves for bigger price changes and smaller moves when the price change is slight. This is an excellent volume indicator for the large numbers of analysts believing that volume leads price. Using A/D, it is possible to spot reversal before price signals confirm a change. The divergence between A/D and price is among the strongest early warnings of a trend ending and about to reverse. A bullish divergence occurs when the A/D index rises while prices fall. A bearish divergence is the opposite. Key Point: The flaw in OBV is corrected in A/D, which adjusts for the size of price and volume moves in each session.

A/D is calculated by comparing changes in the daily price and multiplying the result by volume. Each session’s net total is added to or subtracted from the previous A/D level: (Close – Open) ÷ (High – Low) x Volume For example, the chart in Figure 9.10 contains a primary bullish trend that ended after a large downward gap and an exceptionally big volume spike.

res

ista

gap and volume spike (bearish)

divergence

Source: Chart courtesy of StockCharts.com Figure 9.10: Accumulation/distribution (A/D)

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Divergence in the A/D index began two weeks before this strong reversal. Any time a volume spike accompanies a price gap, it should not be ignored. In this case, both the spike and the gap were very large. A/D did not reveal whether a reversal is a new primary trend or a secondary trend, but it did forecast reversal in advance of price. In this case, it turned out that the large drop was a secondary trend. The primary trend resumed in 2015, reaching a price of $19.50 by March. The conclusion here is that the long-term primary bullish trend was in effect throughout the period, but the late October decline was the start of a secondary trend, signaled well in advance by divergence in A/D.

Money Flow Index Another volume indicator, money flow index (MFI) uses daily volume to weight a popular momentum indicator, or relative strength index (see RSI in Chapter 12). This creates an index reflecting overbought or oversold conditions. MFI is interesting to analysts because it combines price-related momentum with the effects of volume. The index is set to reflect a value between 0 and 100 and assumes that any index movement above 80 shows an overbought condition and that index movement below 20 represents an oversold condition. These key reversal points can be used in trends of any length but tend to be especially useful in managing short-term volatility and movement of swing trends. Like A/D, divergence occurs in MFI. A bullish divergence is found when MFI moves up but price declines. A bearish divergence is the opposite. However, MFI is just as likely to provide a confirmation of price direction and is useful for anticipating price movement in the indicated reversal direction (upward after oversold and downward after overbought). MFI is calculated in three steps. First, the raw money flow (RMF) is the average of high price, low price, and closing price for a session, multiplied by volume: ((High price + Low price + Closing price) ÷ 3) x Volume = RMF Next, a money flow ratio (MFR) is calculated. This is the net of positive RMF in the preceding fourteen sessions divided by negative RMF in the same period. (Positive RMF sessions ÷ Negative RMF sessions) = MFR The total number of positive and negative sessions is always fourteen in the standard MFI calculation. The final step in this calculation is to arrive at the index value between 0 and 100: 100 – (100 ÷ (1 + MFR)) = MFI

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Although this index requires three steps, MFI, like most indicators, is calculated automatically on online charting services. For example, StockCharts.com calculated the MFI on the chart in Figure 9.11.

Source: Chart courtesy of StockCharts.com Figure 9.11: Money flow index (MFI)

On the chart in Figure 9.11, MFI repetitively anticipated short-term price reaction to the index moving into overbought range and, in one case, into oversold. The highlighted price declines follow every case of movement, creating a reliable form of confirmation. However, while these swing trades performed consistently, additional confirmation is invariably needed before acting on what MFI reports. Key Point: MFI is a volume indicator that highlights overbought and oversold conditions based on both price and volume moves.

For example, focusing on three months of the previous chart between July and September, the reversal points of MFI were each confirmed by a candlestick reversal signal as seen in Figure 9.12.

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 217

bearish harami bullish morning star

Source: Chart courtesy of StockCharts.com Figure 9.12: MFI—three months with confirmation

These are a series of secondary trends, two bearish reacting to overbought MFI and one bullish reacting to oversold MFI. As the first trend peak was signaled as overbought in late July, a bearish harami pattern confirmed a likely reversal, which occurred immediately. This was repeated in mid-September when the same signal appeared in conjunction with the MFI overbought signal. The offsetting bullish reversal occurred in mid-August, when MFI moved into oversold range. At the same time, a bullish morning star predicted a bullish reversal. After seven indecisive sessions, price moved strongly higher for one month. These confirming signals demonstrate how trends of all lengths (in this case, secondary trend reversals averaging one month) can be clearly anticipated by MFI and confirmed by other signals. In this example, candlestick signals served the purpose of confirming what MFI predicted. Because both volume and price reversals appeared at the same time, it is not possible to determine which was a leading indicator and which was a lagging indicator. However, observed together, they reliably pointed to the timing of the reversal, helping investors to make their trade decisions at the best possible moment in the trend.

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Chaikin Money Flow The Chaikin money flow (CMF) indicator is derived from A/D. Developed by Marc Chaikin, breakouts may be forecast in advance of the price move. This is an indicator that reflects overbought or oversold conditions based on volume accumulation. CMF establishes an index based on a zero middle line and movement above or below to a maximum of 1.0 or –1.0. If the CMF index moves above 0.20 on the upside, it indicates overbought conditions; if the index moves below –0.20 on the downside, it produces an oversold condition. However, unlike the analysis of price alone to develop these signals, CMF fails to adjust its indicator for gaps. Therefore, a large gap distorts results and leads to the wrong conclusions. This points out that CMF, like all volume indicators, must be part of a broader set of signals and confirmation. Key Point: CMF fine-tunes volume analysis, but a blind spot is in its failure to adjust its index for price gaps.

CMF is calculated by comparing the day’s high and low prices to opening and closing prices and then multiplying by volume: [((close – low) – (high – close)) ÷ (high – low)] x volume These calculations are added for twenty-one sessions and then divided by volume for the same twenty-one sessions. This sets up a range between +1.0 and –1.0. An example of how to analyze CMF is found on Figure 9.13. The areas in which CMF exceeded 0.20 or –0.20 are highlighted. While reaction was short term in this long-term primary bullish trend (representing secondary or swing trends), the last oversold indicator was a forecast that did come true in 2015. After price rose to the $53 level, it declined to under $44 per share by mid-March 2015. Although CMF indicates overbought and oversold conditions, the indicator is not always reliable as a leading indicator. At times, it lags, as in the first two overbought signals on the chart. When using CMF in conjunction with other signals, it should be recognized as only one of many possible signals, subject to confirmation from pricebased patterns and indicators.

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 219

Source: Chart courtesy of StockCharts.com Figure 9.13: Chaikin money flow (CMF)

Chaikin Oscillator Marc Chaikin also devised the Chaikin oscillator, which tracks money flow using an exponential moving average (EMA) for two time periods. EMA weighs the later entries more heavily than earlier entries, so the most recent price and volume have more influence on the outcome. Although this is calculated automatically for you through free online charting services like StockCharts.com, the formula reveals how the components of price and volume are used together to develop this indicator. The first step in the three-part calculation is to derive the money flow multiplier (MFM): [((close – low) – (high – close)) ÷ (high – low)] x volume = MFM Next, MFM is added to or subtracted from the A/D line examined earlier in this chapter: A/D +(–) MFM = Adjusted A/D

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The result is then calculated as EMA on two periods, three and ten days; and the net is the Chaikin oscillator: (3-day EMA of adjusted A/D) – (10-day EMA of adjusted A/D) = Chaikin oscillator The value of this oscillator is highest when it points out divergence. Bullish divergence is found where the oscillator rises as price declines and bearish divergence occurs when the oscillator declines as prices rise. An example of bullish divergence is found is Figure 9.14. This includes two instances in which the Chaikin oscillator anticipates a price rise even as prices fall.

resistance resistance

breakout

resistance breakout

breakout

e

genc

diver

ce

en

erg

div

Source: Chart courtesy of StockCharts.com Figure 9.14: Chaikin oscillator—bullish divergence

The first divergence took place in a consolidation trend lasting from upside breakout in February 2014 to a second breakout in November, a total of nine months. The decline in April and May was contrary to a rising oscillator starting in late March. This revealed the likely move to the upside that followed, although these were all swing trends. In the period following the charted period, this stock once again moved into a consolidation period through March 2015.

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 221

Key Point: The Chaikin oscillator is especially useful when it reflects divergence with the price direction.

These patterns contain similarities. The resistance plateaus form at breakout, and each breakout is accompanied by a volume spike. But even more important, the breakouts were anticipated by bullish divergence in the Chaikin oscillator. This points out the value on this indicator when used with confirming signals in the price patterns. An example of bearish divergence is found in Figure 9.15. In this case the oscillator points to bearish moves even as the stock price breaks through resistance and continues to rise. It is possible for the divergence to fail and for price signals to prevail.

prior resistance new support t

por

sup

div

erg

div

enc

e

erg

enc

div e

erg

en

ce

Source: Chart courtesy of StockCharts.com Figure 9.15: Chaikin oscillator—bearish divergence

As support rose in the first six months of this chart, two instances of oscillator divergence appeared. Even so, the level of resistance and rising support formed an ascending triangle indicating bullish continuation. As prices broke through resistance to form new support, yet another divergence signal appeared in the Chaikin oscillator. Despite the divergence signals, this stock demonstrated bullish strength. In fact, support held through March 2015 and a bearish reversal did not materialize. Like any indicator, the Chaikin oscillator is only one of many signals, and in this case, divergence was misleading. The three warnings of a coming downtrend were not realized.

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Interpretation of these signals also rests with proximity of the signal to the price levels of resistance or support. All these divergence signals occurred at mid-range and not at the crucial levels where reversal is most likely. The breakout above resistance to form a new support level was further evidence that price was stronger than the volume signals in this case. Key Point: With volume indicators, divergence might not always point to the direction of price contraction, it could also forecast a coming consolidation trend.

One interpretation of divergence is a signal of consolidation rather than reversal. This stock moved into a consolidation trend between November 2014 and March 2015, ranging between $60 and $52. However, when analyzing a chart and spotting divergence, it is impossible to know whether any of the three possible outcomes will occur (these are reversal, consolidation, or continuation). The Chaikin oscillator has value but mainly as a confirmation indicator of other signals. Volume spikes and indicators provide value on many levels, but like most trend analysis indicators, they must be confirmed by other related price patterns. The next chapter explores the trend significance of gaps in many forms. Although gaps occur frequently, gap patterns are useful for anticipating trend reversal or continuation.

Endnotes

1 “High-frequency trading has reshaped Wall Street in its image,” March 17, 2017. www. marketwatch.com – retrieved September 27, 2018. 2 Geiger, Keri, and San Mamudi. “HFT Firm Fined $1 Million for Manipulating Nasdaq.” Bloomberg at www.bloomberg.com (October 16, 2014). 3 Murphy, John J. The Visual Investor: How to Spot Market Trends. Hoboken, NJ: John Wiley & Sons. 1996, pp. 5153.

Chapter 10 Mind the Gap: When Price Jumps Signal Change The gap is one of the strongest price signals found on a stock chart. It often accompanies reversal or marks the beginning or end of a trend. It also will be found in many beginnings and endings of secondary trends within a longer-term primary trend. These highly visible signals often are the first attributes analysts notice on a chart. This is especially true when a large gap appears, moving price out of range and setting up an uncertain new level of resistance or support, at least temporarily. “Because technical analysis has traditionally been an extremely visual practice, it is easy to understand why early technicians noticed gaps. Gaps are visually conspicuous on a price chart.”1 Key Point: Gaps are noticed immediately; they jump out of the chart, and this explains why so much attention is paid to them. However, not all gaps are special; they occur often and may simply be price coincidences.

A gap is the result of one of two events: first, the opening price of a session is higher than the previous day’s high close or, second, when the opening price is lower than the previous day’s low close. At first, it might seem that all gaps will be visible for this reason, but it is not the case. Many gaps are “hidden” because the range of trading in the most recent session is within the range of the previous day (even with the gap between prior close and current open). This is demonstrated later in this chapter. The gap itself is only a part of the strength in gapping price action. What happens next is equally as important. If price returns into range, closing the gap, it means that the initiative of price movement was not strong enough to take hold (especially when the gap occurs in close proximity to resistance or support). However, if the gap does not close, it indicates strength in the direction of the gap, continuing the current trend or even setting up a successful breakout above resistance or below support.

The Nature of Gaps There are many “rules” in technical analysis, not all universal. For example, some analysts suggest that gaps are valid indicators only when confirmed by volume. It is true that gaps and volume spikes go together, but volume by itself is not always enough of a signal to draw conclusions about what the gap means. It could be strong retracement, breakout, or just coincidence. A more accurate rule is that when you find gaps and volume spikes together and they occur close to resistance or support, it probably means something important is about to happen. Even then, independent confirmation in at least one other signal is crucial. DOI 10.1515/9781547401086-010

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Confirmation is always required, and this “rule” is more universal. Gaps and volume are frequent companions in price charts, and interpretation is not a simple matter. The combination of independent confirmation and proximity to resistance or support add confidence to interpreting gaps and what they mean to the longer-term trend. One of the reliable tendencies is for gaps to occur as part of a secondary trend and can be observed setting up the beginning and the end of that trend. After a concluding gap, the primary trend resumes. However, at the time the secondary trend begins, you do not know whether it is a primary trend reversal; confirmation still must be the ruling force leading to decisions to trade or wait. Gaps frequently also set up retracement within a primary or secondary trend, with a gap followed by a very brief retracement in price. Gaps also are found as forms of exaggerated and short-term price movement. For example, immediately after an earnings surprise, price tends to spike up (for positive surprises) or down (for negative surprises). The same thing occurs when management adjusts its guidance for the coming year. Even when earnings are exactly in line with estimates, if management reduces its estimates of coming revenues and earnings, a price spike is likely to occur as a response to the news. Key Point: Gaps are seen along with overreaction to surprises, when earnings exceed or to not meet expectations. These are likely to self-correct and fill rapidly.

These price spikes tend to last between one and three sessions before retreating to a less volatile trading range. This is one of the keys to success in swing trading. The swing trader, acting as a contrarian, makes a rational decision to trade as soon as the exaggerated price move occurs, knowing it is most likely to reverse. In comparison, most traders overreact to the news, causing the spike and setting up the reverse. The price spike often is recognized not only by the gain or loss of several points, but also by the gap, often a large gap in the price. Swing traders recognize that the larger the gap, the more likely it is to fill quickly—meaning a price reversal. In this timing right after earnings or guidance surprises, gaps are most likely to fill. This reveals that the prevailing trend, either primary or secondary, will continue once the dust settles around market reaction to the surprise. The process of trading on exaggerated price action, especially after surprises, is known as “fading the market.” The earnings surprise is one of the few fundamental indicators that has an immediate impact on the stock’s price. Most fundamentals (revenue and earnings, working capital, and dividend announcements) tend to cause a delayed reaction on the technical side. Other fundamentals that may affect prices immediately include announcements of mergers and acquisitions, new product approval or denial (notably in pharmaceuticals, for example), or a company’s decision to buy its own shares in the open market, indicating management’s belief that the current price represents a bargain. When a company buys its own shares, those

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shares are retired permanently as “Treasury Stock” and will not be subject to dividend payments in the future. This means that the company’s quarterly dividend payments are reduced by retiring stock. Any rules for trading gaps must be observed with caution. While specific types of gaps occurring after surprises are reliable, many gaps occur as a matter of course. Gapping price action is common and with the combination of visible and hidden gaps, they occur repeatedly, in some stocks several times per week. The appearance of a gap is only significant if it is accompanied by a signal or set of signals and occurs close to resistance or support.

Gaps Filled or Unfilled The issue of “filling” a gap determines not only the strength and meaning of the gap itself, but also what will occur next. Candlestick indicators (gap filled and tasuki gap, which is unfilled) both are continuation signals. When one of these signals occurs close to resistance (in an uptrend) or support (in a downtrend), it indicates that the current trend is likely to continue. These indicators need confirmation, however. Even with strong indicators in the form of gaps filled or unfilled, the signal itself may be misleading. For example, in Figure 10.1, price breaks through below support and then evolves into a gap filled formation at the very bottom.

support

Source: Chart courtesy of StockCharts.com Figure 10.1: Filled gap

This gap at mid-October did not meet the requirements for a bearish gap filled. That would consist of a black session, a downward gap, another black session, and then a white session filling the gap. This formation consists of three white sessions. Even so,

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the gap does fill normally indicating an upward reaction. Secondly, it contained a doji with a large lower shadow (a bullish sign) and a long white session (another bullish sign). As expected, price moved to its established range. Key Point: When gaps fill, meaning the gap is later taken up with a trading range, traders are reassured, especially if directional signals are part of that pattern.

An interesting development was a second filled gap formation as price crossed back into range. This gap filled pattern met the exact criteria for a bullish candlestick: a white session, upside gap, a second white session, and a black session filling the gap. Price continued rising after this development. Confirming this continuation was yet another bullish gap filled following immediately. When you find two continuation signals in close proximity such as this, it is an exceptionally strong form of confirmation. The need for strong confirmation, especially when price has broken through support and then returned into range, is a key element of a strong gapping signal. In this case, the gap was itself part of the continuation candlestick signal, and it strongly supported the likelihood of a continuing uptrend. The unfilled gap also works as a continuation signal. Candlestick requirements indicate the upside tasuki gap should consist of a white session, upside gap, a second white session, and then a black session closing lower (but not filling the gap). A bearish version is the exact opposite, a black session, downside gap, a second black session, and then a higher-closing white session that does not close the gap. The perfect tasuki gap works as strong confirmation, but this does not mean that unfilled gaps are failures. Many unfilled gaps mark either reversal or continuation, and the larger the gap, the stronger the signal. For example, in Figure 10.2, two separate and large gaps marked changes in the secondary trends.

supp

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rt po

p

ist

su

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Source: Chart courtesy of StockCharts.com Figure 10.2: Unfilled gap

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The first gap spanned 8 points between consecutive sessions. This was a huge upside gap. It did not fill and the sessions did not meet the standards for typical continuation patterns. In addition, given the preceding downward price movement, there was not an uptrend to continue, so this form of gap just marked a change in the trend, a secondary trend development that ended up lasting three months. The second gap moved prices in the opposite direction. This gap also failed to meet the continuation requirements of the bearish tasuki gap; however, a strong signal appeared, which was a support-to-resistance flip. This is among the strongest signals that the gap breaking through support is likely to hold as the flip takes place.

Gap Up and Gap Down Gaps occur to the upside as well as to the downside. Generally, a gap up tends to occur during an uptrend and confirms that trend and a gap down confirms continuation of a downtrend. However, these observations are not always true and must be confirmed with independent signals. Key Point: Gaps tend to occur in the same direction as price movement. This is a common pattern, but it does not always occur in the manner expected. Opposite-moving gaps could signal reversal.

In candlestick analysis, a gap up is called a rising window and a gap down is called a falling window. The two sessions (before and after the gap) may be of either color, but the assumption remains the same: that gap up is bullish and gap down is bearish. The price pattern is not quite that simple in every case. Figure 10.3 includes an example of a strongly rising gap of 7 points. However, price did not react immediately with a bullish move. Instead, a two-month bearish secondary trend followed, filling the gap at the end of that downtrend.

resistance

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Source: Chart courtesy of StockCharts.com Figure 10.3: Gap up

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The two-month secondary trend is interesting because it followed such a strong upward gap, normally a bullish signal. But the bullish move finally occurred after the double bottom, marking the resumption of the uptrend—two months later. This delayed reaction emphasizes the point that gaps, even large gaps, do not set up an immediate “cause and effect” reaction in price. The signal might be correct, but price might not respond immediately. When gaps move through resistance or support, they often mark the beginning of a new trend with a modified trading range. Figure 10.4 shows a gap that sets up a secondary consolidation trend lasting three months.

resistance

resistance

Source: Chart courtesy of StockCharts.com Figure 10.4: Gap down

This consolidation trend began as the 4- gap pointing downward appeared. Resistance was set just above $72 per share. The consolidation finally broke out above resistance but failed with the appearance of another downward gap. This set up a new resistance move that immediately rose above the previous level of resistance. The price action immediately before the 5-point gap reveals a runaway gap pattern that concluded with an exhaustion gap ending consolidation and setting up a new bullish trend. Over the following three months, a new bullish trend succeeded and reached $80 per share by the end of March 2015.

Common Gaps Common gaps, also called trading gaps or area gaps, occur so often that they provide little in the way of useful signals. They normally are seen during a price move at midrange. A popular assumption is that a common gap is likely to be filled, but in fact when they are part of a fast-moving secondary trend they often are not filled at all.

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For example, Figure 10.5 provides three sets of recurring common gaps, all taking place during secondary trends. Of the ten common gaps shown, only one (second to last) filled.

prior resistance new support

Source: Chart courtesy of StockCharts.com Figure 10.5: Common gaps

The period in which these gaps occur, from August through October, was a longer-term primary consolidation trend. It appeared to end with the breakout above the $51 per share price range. However, even though prices trended higher, a new consolidation trend took over between November 2014 and March 2015, with prices remaining in a range between $59 and $51. During this period of higher price consolidation, the pattern of repetitive common gaps continued. Key Point: Common gaps are just that, common. They do not provide signaling value unless they exist within a bigger signal.

This does not mean that common gaps lack value. In fact, in situations like this, with extended consolidation patterns over time, many common gaps act as indicators that the shorter-term secondary prices are not likely to gain enough strength for a breakout. On the chart, the first two sets of common gaps occurred right before the secondary trends concluded, and in the third set, the common gaps represented a breakout above the prior consolidation resistance to form the new consolidation support. The flip indicated that new support would hold (which it did), but the momentum of this stock was not strong enough to create a dynamic trend in bullish or bearish directions. Common gaps may be viewed as symptoms rather than signals. The symptoms are of likely continuation in a consolidation trend in this example. These also may be found in long-term but very slow-moving primary uptrends or downtrends. The common gaps may signal coming change if the space of these gaps expands, so that a

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series of common gaps become runaway gaps as the momentum of a trend increases, signaling some form of change soon.

Hidden Gaps Another way in which gaps develop is through “hidden gap” formations. These meet the definition of gaps in the sense that the closing price of one session gaps to the opening price of the next session. However, due to an overlap of the day’s trading range, these are not visible. In the visible gap, space is evident between sessions. But these are only part of the gap universe. In fact, gaps are very common and an examination of just about any price chart reveals this. Hidden gaps may occur frequently. This is important because gaps often act as signals, even when they are not immediately visible. There are six forms of hidden gaps, which are summarized in Figure 10.6. Note that in each case, the real bodies of the two sessions always overlap, which shows why these are hidden.

Source: Chart prepared by the author Figure 10.6: Hidden gaps

While many hidden gaps are also common gaps and insignificant—especially given their frequency—it is also possible for a hidden gap to represent a big move. For example, in Figure 10.7, two instances of hidden gaps representing large price moves are highlighted.

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Source: Chart courtesy of StockCharts.com Figure 10.7: Hidden gaps with big moves

Putting this price pattern in perspective, the stock was in a long-term bullish primary trend. In April 2013, the price was in the $380 range. By December 2013 it had risen to $400. One year later at the end of 2014, the price was $450. By March 2015, it had risen to nearly $490. However, during the four months shown on the chart, the primary uptrend was interrupted by a bearish secondary trend. This was marked by two hidden gaps. The first was a decline of five points, followed by a price move to the downside, and then a rebound. The second was a stronger gap moving down 8 points and marking the beginning of the six-week secondary bearish trend. Key Point: Hidden gaps are not as visible as others because they are obscured by real bodies of candlesticks. The danger in ignoring hidden gaps is missing the signal values they provide.

The hidden gaps were initial signals. They were confirmed by the bearish harami formed by the two sessions involved with the second hidden gap—a long white followed by a smaller black session. The long white extended far beyond the range of the second day, making this an exceptionally strong bearish signal. After six weeks, the secondary trend concluded and the primary bullish trend resumed. The point to this is that the large downward-moving hidden gaps were important signals. These are easily missed, however, if an analyst focused only on the visible forms of a gapping price pattern. This secondary bearish trend was volatile and the big gaps set up the strength of the downtrend, even though it lasted only six weeks.

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Breakaway Gaps The breakaway gap occurs as price moves above resistance or below support. This is the price area where reversal is most likely to occur. The breakout from a trading range is half of the likely pattern; the other half is the breakaway gap itself. This extreme move is likely to reverse and fill, although this does not always happen immediately. An example of two secondary trends concluding with breakaway gaps is shown in Figure 10.8. In both instances, the gap marked the beginning of reversal.

resista

ce

resistan

nce

support ort

pp

su

Source: Chart courtesy of StockCharts.com Figure 10.8: Breakaway gaps

From July 1 through mid-September, a gradual uptrend was underway. As price moved through resistance, the breakaway gap also formed. After this, price retreated into range and then broke through below support, falling from $28.50 down to about $23 per share before a new uptrend began. A second breakaway gap was found toward the end of the chart as an uncertain resistance level was clearly violated. After the period shown, the price dipped in late January to a range between $27.50 and $25. After this, the February to March 2015 period moved into consolidation between $31 and $28.50. None of the trends for this company were particularly strong or long-lasting. In fact, the price range at the beginning of the chart (between $28 and $26) was similar to the consolidation range by March 2015, eight months later. This suggests that the stock was in a long-term primary consolidation trend with secondary trends moving both above and below, but with no success in breaking out. These moves, marked clearly by breakaway gaps, demonstrated that when the breakaway occurred in close proximity to resistance or support, reversal was most likely—especially when the trend in effect was a secondary trend, meaning the reversal returned price to its established trading range.

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Runaway Gaps Another form of gap is the runaway gap, also called the measuring gap. This gap normally will be found during trending movement, often as part of a secondary trend working against a primary trend. When runaway gaps appear, it might indicate a short-term move in the indicated direction, which is likely to revert to the previous or primary trend direction. Key Point: A runaway gap may be part of a strong evolving trend, often found in a secondary trend of great momentum but short duration.

Another type of runaway gap occurs right after price makes a move and is supported by a strong gapping action, providing confirmation of a continuation in the new trend. In other words, runaway gaps can mean many different things and should be considered based on where they appear and how strongly they are confirmed. A sequence of runaway gaps could be caused when several traders decide to get in on the trend action by buying shares (in an uptrend) or cutting losses (in a downtrend). The sequence may also be a correction of a preceding excessive price move. For example, Figure 10.9 contains a chart with two distinct areas of runaway gaps, which look different from one another.

resistance

support

Source: Chart courtesy of StockCharts.com Figure 10.9: Runaway gaps

The first set of runaway gaps takes price above support. The breakout came after a set of narrow breadth days and not much of a trend at all. That indicates the breakout was weak. In fact, after a 6-point decline, prices rebounded and jumped back into range. This fast upward movement included a series of strong runaway gaps moving up.

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The first series broke through support and the second series proved the breakout had failed. The longer-term trend was a consolidation trend, with resistance set firmly at $69 and support at $60. In 2015, the resistance level fell gradually until it rested at about $61 by the end of March, with support holding at $60. So other than the brief breakout below support, this primary consolidation trend held with the short-lived breakout characterized by two series of runaway gaps.

Exhaustion Gaps The exhaustion gap signals that the current trend or price pattern has lost momentum and is likely to soon reverse. This pattern is seen repeatedly in charts. Generally, exhaustion gaps showing up at the end of a strong trend tend to lead to equally strong reversals; and the larger the gap, the more likely the reversal will occur soon in a filling action. Figure 10.10 contains four examples of exhaustion gaps. This chart is similar to the one in Figure 10.9 in overall shape and price pattern; however, the exhaustion gaps clearly defined turning points in secondary trends. exhaustion gaps resistance

support

Source: Chart courtesy of StockCharts.com Figure 10.10: Exhaustion gaps

As in the previous chart, this one exhibited a long-term consolidation primary trend that ranged between resistance of $56 and support close to $50. The first exhaustion gap led to a test of support, which failed and kept price levels within range. However, after a strong secondary downtrend in September and October, prices broke through support. However, that trend was concluded with another exhaustion gap. The reversal was confirmed by the session immediately following the gap, which was a

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hammer with an exceptionally long lower shadow. The hammer is a strong single-session reversal. The combination of the exhaustion gap and the hammer, occurring immediately after a breakout, raised confidence in the likelihood of reversal. Key Point: The exhaustion gap forecasts reversal of the current trend. Once confirmed, this signal should raise confidence to high levels that a reversal is about to occur.

The next two exhaustion gaps strongly confirmed the likelihood of continuation in the established consolidation trend. The first one, in late November, led to a test of resistance; the second one, in mid-December, led to a test of support. All the secondary trends on this chart demonstrated the failure of breakouts; and all these tests were associated with fast and quick secondary trends and exhaustion gaps.

Island Cluster A final oddity involving gaps in price patterns is the island cluster (also called island reversal or archipelago). This is a very brief set of consecutive sessions with strong gaps on either side. It is like candlestick patterns such as the abandoned baby, morning star, evening star, and doji star. In all these signals, a single session is separated from the sessions before and after by a gap. However, while all these signals involve an island of one session, the island cluster contains several, often with a compressed trading range. For example, Figure 10.11 revealed a visible island cluster in July 2014. Price jumped above prior resistance but quickly returned to the established trading range.

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island cluster ce

resistan

volume spikes

Source: Chart courtesy of StockCharts.com Figure 10.11: Island cluster

The cluster could predict a strong reversal in which case you would expect to see prices beginning to move downward. This did not occur. In this case, the island cluster set up a new resistance level at $85 per share. Prices settled into a new consolidation trend lasting until March 2015 with support at $78. This 7-point range was narrow, considering the range of the years 2013 and 2014, which was a primary bullish trend moving prices from $45 up to $85. Another accompanying signal at the beginning and end of the island cluster was a set of volume spikes. The first, and longer one, occurred as prices gapped higher and broke out above resistance. The second, smaller spike marked the failure of the breakout and a return into range. However, that rising bullish range did not endure the preceding breadth of as much as 10 points. Once the new consolidation trend replaced the bullish trend, the breadth narrowed to 7 points, with the change marked by the island cluster and volume spikes.

Ex-Dividend Gaps Many gaps are mere coincidence. These common gaps are found often in charts and can easily be misinterpreted. Only when proximity and price action justify defining a gap as runaway, breakaway, or exhaustion does the gap matter. Because gaps are common, they should be analyzed and interpreted cautiously. Even the appearance of strong gaps providing signals can be difficult to interpret.

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Therefore, confirmation of gaps patterns is just as important for other forms of price signals. However, some gaps are associated with specific events and should be analyzed in context. Key Point: The ex-dividend gap is caused by price adjustment as dividends are earned. These are non-recurring gaps.

An ex-dividend gap may be found the day before ex-dividend date or on ex-dividend date itself. This is the date on which an owner of stock no longer is entitled to earn the current dividend. The gap is associated with the obligation of the company to pay the dividend on a specified date soon, usually within one month. However, because the day before ex-dividend date is acknowledged as the day the dividend is an obligation, price of stock may decline to offset the cost of paying the dividend. The ex-dividend gap may fill or simply work as an adjustment to a range-bound stock. This gap does not always occur either, when offsetting supply and demand interests erase the effects of paying the quarterly dividend. The danger of the ex-dividend gap is that it may be misinterpreted by analysts. With awareness that ex-dividend is arriving, an analyst will discount the downward-moving gap occurring at or right before that date. It is a mistake to assign other properties to a gap, such as breakout signal, failing to fill, or exhaustion. The ex-dividend event distorts price temporarily and when that includes a gap, even a developing candlestick signal should be largely ignored. The reversal or continuation properties of a signal do not necessarily apply when the gap is a feature of ex-dividend and not of an actual independent price pattern.

Gaps as Part of Other Signals Gaps may be located free of other signals. When these signals occur as breakaway, runaway, or exhaustion signals, they are powerful initial indicators. Once confirmed, confidence in the expected outcome will be quite high. However, gaps do not always exist on their own but may be parts of other signals as well. Some examples are: –– The engulfing pattern is one of the strongest of two-session candlesticks. It always sets up with a hidden gap between the two sessions, with the opening price of the second session lower (bullish) or higher (bearish) than the previous day’s close. –– A harami is the opposite of an engulfing, with a long session followed by a shorter one. It, too, contains a hidden gap between the two days. A bullish harami gaps up and a bearish harami gaps down. The same is true of a harami cross. With a doji in the second day, an upward gap (bullish) or downward gap (bearish) is part of the formation. –– The morning star and doji star also involve gaps moving down in a bullish version or up in the bearish version.

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–– An abandoned baby contains two gaps. In the bullish version, a downward gap leads to the middle session followed by an upward gap. In the bearish version the same pattern emerges but in the opposite direction. –– Side-by-side continuation patterns come in four varieties but all involve a gap between the first and second day but little or no gap between days two and three. –– Tasuki gaps and gap filled patterns also act as continuation patterns. The gap is the essential element in each. In the bullish continuation, the gap occurs between the first two days and moves to the upside. In the bearish version, the gap takes price lower. Many candlestick signals involve no gaps whatsoever (three white soldiers and three black crows, for example). However, the patterns involving one or more gaps provide the strongest reversal or confirmation signals. When finding gaps on a price chart, you need to decide whether it is a stand-alone signal of value in predicting price action or part of a candlestick reversal or continuation signal relying on the gap as part of its formation. Key Point: Candlestick signals containing gaps are notable but the gap does not always add to the strength of the signal. It is only one attribute worth observing.

Gap Proximity to Resistance or Support Most price signals contain the strongest predictive value when they occur at or close to resistance or support. This proximity factor is the strongest factor in determining the reliability of the signal itself. This is especially true in the case of breakaway and exhaustion gaps. When price gaps through resistance or support, a reversal is most likely. The tendency for gaps to fill should not be overlooked in any case, but when the gap takes price over the trading range border, it has extra meaning. A breakaway gap, if confirmed by a strong signal indicating continuation, is strongest when it breaks through. However, if a reversal signal or set of signals occurs immediately, then expect price to retreat into range. Exhaustion gaps occur at or near the end of a current trend, especially in secondary or swing trends. If the exhaustion gap takes price through resistance or support, it means a reversal is highly possible and that price is expected to fill the gap and return to the established range. Gaps may also signal the end of a trend with one of two results: reversal to a trend going in the opposite direction or replacement of the prior trend with a new consolidation trend. In both cases, duration can not be known based on the strength of the gap, but the gap itself reveals that exhaustion (another name for lost momentum) is the clear signal that the trend will not continue.

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These unknown factors related to how price acts after a gap is found define the technical “gap risk” of chart analysis. However, this risk is more closely associated with swing trends than with secondary or primary trends. In a swing trend, expect rapid movement of price and with exhaustion gaps anticipate volume spikes. This pattern often recurs within the swing trend movement of price patterns and provides reliable signals of short-term changes. However, gap risk applies to all forms of gaps. Gaps, in general, represent a form of chaotic price change. In a completely orderly market you would expect a session’s price to start where the previous session ended. This is unrealistic, however, as virtually every chart reveals. Instances of prices opening where the prior session closed are rare. For example, Figure 10.12 reveals the likely occurrence of sessions opening where a prior session closed. Out of sixty-four sessions, price opened where the previous session ended only four times. This is typical of how price changes between consecutive daily sessions.

Source: Chart courtesy of StockCharts.com Figure 10.12: Inter-session gaps

This is not a volatile chart. In fact, it represents a three-month primary uptrend that moves only modestly with daily breadth of trading never exceeding three points. Even so, the likelihood of prices opening and closing at the same level is small. This makes an important point: most gaps, both hidden and visible, do not contain meaning on their own. It is the gap forming as part of a strong candlestick signal, or a notable breakaway or exhaustion gap, that forecasts price changes. When it comes to gaps, look for the exceptions: gaps moving through resistance or support (breakaway) or those forming near the end of a trend (exhaustion). Key Point: Among the strongest of signals, both reversal and continuation, are those occurring as price gaps through resistance or support.

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Gap risk is constant. If defined as the risk that price level will change between sessions, it is found on almost every stock chart and with great frequency. When gaps are extreme, however, it invariably signals a strong adjustment to follow that either indicates a new trend is beginning, or that the gap itself will be filled by a reversing price move and price will then return to the previous breadth of trading. This occurs in cases of earnings surprises, changes in announced guidance, product news, mergers and acquisitions, and other information, either positive or negative, that comes as an unexpected event. Gaps are so frequent that the biggest challenge in interpretation is not deciding whether the gap has occurred but distinguishing between normal patterns and exceptions. The study of gaps demands judgment, an understanding of their proximity, and how they act as part of two- or three-session candlestick signals. The next chapter takes a look at another type of indicator that is always present, but which provides numerous signals based on how price moves. The moving average by itself is not always significant, but when two moving averages of different duration are studied together, the chart takes on a stronger forecasting characteristic.

Endnotes

1 Dahlquist, Julie, and Richard J. Bauer. Technical Analysis of Gaps: Identifying Profitable Gaps for Trading. Upper Saddle River, NJ: FT Press, 2012. p. 1.

Chapter 11 Moving Averages: Order in the Change The moving average (MA) is a statistical tool that evens out a set of values. On a stock chart, those values are based on closing prices over a range of sessions. In reviewing a chart for a volatile stock, it often is difficult to determine the general trend of price; with moving averages it becomes possible to tell not only the direction, but the level of volatility as well. A “moving” average is just that: with the close of each new session, the oldest session is dropped off and replaced with the newest session’s closing price. With price data smoothing through MA, charting is given a specific structure not always available otherwise. The longer the period in the MA, the less responsive it is to change. Newer information that departs from the average will not change the MA line as much as it does in a shorter time frame MA. For example, a fifty-day MA will be more responsive to new information than a two hundred-day MA. This observation explains the technical value of MA analysis: by comparing two different MA lines over a price chart, conclusions can be reached based on how the two MA lines interact, converge, or cross, providing signals or confirmation about direction and potential reversal. Key Point: The longer the period of the MA, the less responsive it is to changing prices. This points out the value of two MAs used together.

The most popular MA system is the fifty-session and two hundred-session combined analysis. This is based on a simple moving average (SMA) as the default position, meaning the calculation is straightforward and not adjusted. The formula for SMA is: (v1 + v2 + v3 + ….. vn) ÷ n = SMA In this formula, v represents each value (closing price), and n represents the total number of closing prices studied in the MA. For fifty sessions, a combination of fifty most recent closing prices are added together and divided by 50. For two hundred sessions, a total of two hundred closing prices are added and then divided by 200. Fortunately for the trader, online charting services like StockCharts.com calculate MA automatically as part of the chart. Other MA systems weigh the latest information in the belief that it is more relevant to the current price than older information. The most popular of these weighted average systems is the exponential moving average (EMA). While EMA is used in many technical calculations, especially momentum oscillators, the system for MA analysis normally is SMA.

DOI 10.1515/9781547401086-011

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Averages can be weighted in other ways as well. For example, double weight can be given to the latest entry in the field. For example, a ten-session study adds the latest value twice, and the added total is divided by 11. MA in trend analysis provides several benefits. Beyond reversal signals and confirmation, MA provides examples of divergence that anticipate a secondary trend moving in opposite direction from the primary trend and MA also confirms dynamic resistance and support on many charts, adding strength to the tracking of a trend and revealing the moment when the trend begins to weaken (as MA crosses into the price range, for example). Considering that MA merely represents the averaging of price, it is a form of price confirmation itself. However, the properties of MA have succeeded and have been critically studied for reliability: “MA rules are very widely used by practitioners and . . . are one of the few technical trading rules that are statistically well defined.”1 The skepticism toward MA as a reliable signal for confirmation is understandable. However, the studies point to consistent levels of predictability. One study examined: prices for the Financial Times Industrial Ordinary Index (FTI) over a 59.5-year period from 1935 to 1994 . . . [and employed] two of the simplest and most popular classes of technical trading rules—moving average and trading range breakout rules . . . these technical trading rules have predictive ability if sufficiently long series of data are considered.2

Given the conclusions of this and other studies, it makes sense to put aside skepticism and to treat MA analysis as one of the many worthwhile forms of signal and confirmation. A related use of MA based on price and price averages involves the study of momentum oscillators (see Chapter 12). MAs have one significant drawback. Because they summarize past information, they are lagging indicators. Statistically, lagging indicators tend to lack predictive properties because past price performance can not accurately predict what the future holds. However, by combining two separate MA lines and comparing these to price, predictive signals do evolve and provide value. Crossover and convergence work even when using these lagging indicators.

Two Moving Averages The use of a fifty-day and two hundred-day moving average provides many signals of value in trend analysis; even as a combination of lagging indicators, using this two-part analytical tool has widespread acceptance for confirmation. In fact, “moving averages are considered as more profitable technical trading rules by analysts. . . . The 50- and 200-day ones provide the most reliable signals.”3

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Key Point: The MA analysis consists of observed lagging indicators; thus, as confirmation for other signals, MA is a strong signal for trend analysis.

The aspects of MA in analysis, specifically the significance of crossover, makes this is strong set of signals. MA crossover occurs whenever the fast MA (fifty-day) crosses over the slow MA (two hundred-day). An example of the two-MA chart is shown in Figure 11.1.

MA crossover

50-day MA

200-day MA

Source: Chart courtesy of StockCharts.com Figure 11.1: Two moving averages

The fast MA line on the chart in Figure 11.1 was lighter and the slow MA line was darker. Crossover occurred so frequently that by itself, it did not provide enough information to generate a trade. Confirmation is required, and MA often acts as a confirming signal to other indicators. On this chart, the price pattern moved rapidly, so MA crossover would most likely be used for secondary trend identification. Following the strong uptrend in the first eight months of 2013, the remaining fourteen months of the chart developed into a primary consolidation trend between $110 and $90. Crossover did not take the price permanently above or below this level, but it did mark the start of a secondary trend from the downward gap in November 2013 through mid-February 2014. The bearish crossover confirmed what the gap predicted. The second example of crossover was late June 2014 and it did not lead to a big price move even though the crossover was bullish. This indicator lagged behind the fast price pattern during most of June. Even though the two-MA system provides useful information about price direction or, in some cases, divergence between price and MA, it is only one part of the broader price pattern. Its overall weakness (due to its tendency to lag behind price) is one reason additional signals are needed to time trades accurately. As a price indicator, how reliable can an MA be? Stronger signals involve developing price patterns

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or momentum or interaction between price and other signals such as volume. MA is a pattern indicator confirming other signals, but it is best used with skepticism and only when strongly confirmed by other independent signals. The chart in Figure 11.1 reveals the basic “rule” about crossover. When the slow MA crosses above the fast MA, the tendency is bullish; this is called a “golden cross.” When the slow MA crosses below the fast MA, it is a bearish sign. This has the dramatic name, “death cross.” However, assuming confirmation is located, MA provides confidence with this “rule” about crossover direction: “Under [the moving average rule], technical analysts initiate buy and sell decisions after comparing the short-run moving average of the share price with its long-run moving counterpart.”4 The lag impact varies for each MA. The longer the period studied, the greater the lag. Therefore the two hundred-MA is referred to as the “slow” MA. However, the value in comparison is based on crossover itself. The crossover between the two MA lines is part of the story; price crossover of trading above or below both MA lines is equally important, predicting price reaction to follow quickly. Key Point: The trend analysis value in MA is not in the duration of the average itself but in how and when crossover takes place.

Bollinger Bands Although the two hundred-MA and fifty-MA represent a strong signal methodology, it is not the only way that MA is used in trend analysis. Bollinger Bands is one effective use of multiple moving average analysis, based on the SMA method. Bollinger Bands sets up a statistical summary of price range and movement. The middle band is a twenty-day SMA. The upper and lower bands are two standard deviations removed from this middle band. Therefore, the distance between the middle band and the outer bands is always identical on each side. This three-band system sets up several potential reversal signals while tracking trends over time. Testing price volatility is only one aspect of the band system. This also indicates movement above and below expected breadth, which signals likely reversal points. However, like most indicators, strong confirmation is essential: Bollinger Bands (BB) are not standalone indicators as they do not generate explicit buy or sell signals and are generally used to provide a form of guideline, indicating possible trend reversals. In this case, if the current price breaks through the lower Bollinger Band it is considered a buy signal, while if it breaks through the upper band it is considered a sell signal.5

When price volatility increases, reversal becomes likely. This tendency is made visual with Bollinger Bands. The bands increase as volatility increases and con-

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tracts as it decreases. Well-known signal effects are the M tops and W bottoms (see Chapter 2), which strongly mark reversal points. Closely associated with double tops and bottoms, the M top and W bottom are given additional strength when occurring as part of Bollinger Bands. When occurring within the band pattern, the double tops and bottoms extend over a greater time, but the reversal signal may also be much stronger than upper or lower shadow spikes taking place over two consecutive sessions. Key Point: As prices spike above or below Bollinger Bands, the MA significance for reversal is exceptionally strong.

Another important signal obtained from analysis of Bollinger Bands is the timing of price spikes above the upper band or below the lower band. These take on two characteristics. The most common is a price spike outside the band zone that occurs right before short-term price reversal. This is a useful confirmation signal for swing trends. The second, less frequent type is the price spike occurring in conjunction with a price gap, often signaling continuation over the short term and a second band move after the gap occurred. For example, Figure 11.2 contains examples of both types of Bollinger Band moves.

gap

gap

reversal signal

gap

reversal signal

reversal signal

Source: Chart courtesy of StockCharts.com Figure 11.2: Bollinger Band moves

The highlighted areas in Figure 11.2 reveal fourteen instances in which the price spiked above or below the band ranges. Three of these followed the pattern of movegap-move, or price moves along with gaps, after which price continued in the same direction as the price move (above Bollinger Bands) and gap and then a second move of price above the upper band. Eight moves were reversals pointed to a coming bullish or bearish move taking the price back into range within the upper and lower bands.

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Convergence A phenomenon of MA is the trend-related convergence pattern. This occurs when the two MA lines narrow and become closely aligned. It generates a reversal signal and, if confirmed by related patterns, may be among the strongest applications of MA. Convergence as part of a different set of indicators is aligned with the opposite of divergence and studied as part of EMA analysis of momentum. This is explored in Chapter 12. For the purposes of MA analysis, convergence is based on movement in the two SMA trends, fast and slow. The chart in Figure 11.3 shows how this works. Convergence is strong in this example because it is confirmed by two other reversal signals.

symmetrical wedge (bullish)

MA convergence

bullish engulfing

Source: Chart courtesy of StockCharts.com Figure 11.3: Convergence

The two lines began converging in April and became closest to one another in late May. When this occurs, it often is accompanied by wedge formations. The symmetrical wedge was marked on the chart. At the end of the wedge—the point where the two MA lines converged as well—the reversal was signaled strongly by the bullish engulfing indicator. By itself, this small engulfing indicator was not especially strong, but coming at the end of the wedge and at the point of narrowest convergence of the two MA lines, it forecasted the reversal that followed.

Divergence In the case of MA trend analysis, divergence is not the opposite of convergence. Chapter 12 examines convergence and divergence relating to momentum; divergence

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when analyzing MA is defined as opposite price movement compared to what MA forecasts. Key Point: Convergence of the two MA lines anticipates crossover and possible reversal.

A price crossover (movement of price above or below both MA lines) is considered a strong signal. For example, in Figure 11.4 a move in price below both MA lines implied a bearish price move. However, as soon as this occurred, price began moving in a bullish trend direction.

price moves below MA (bearish sign)

price begins bullish trend

Source: Chart courtesy of StockCharts.com Figure 11.4: Divergence

Price crossover is not the same as crossover between the two MA lines. Once price moves below both lines, as it did on the chart in Figure 11.4, it is thought to lead MA in the same direction. What started out as a downtrend was expected to continue, but it did not. This divergence between price and proximity (of price to MA) may be a confusing matter for analysts. However, the conclusive sign of lost bearish momentum was seen in the mid-May doji session with an exceptionally long lower shadow. This indicated a likely bullish reversal, notably as price levels moved back into the MA range and then moved strongly above both MA lines.

Price Crossover The value of MA is that it establishes a recognizable trading range over time. This range—the current trend—is not only easily identified, but once price evolves above or below, it creates a specific signal moving away from the established trend.

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A bullish signal results from current price crossing above both MA lines, and a bearish signal is found when price crosses below both MA lines. The rationale makes sense for secondary and swing trades; but for primary trends, price crossover may mark the beginning and end of a secondary trend as well. Thus, MA tracked over a long period is useful in determining the longevity of the trend, whereas short-term crossover can be used to spot and time shorter-term trends, notably swing trends. The crossover “rule” is worth acknowledging, given the ability to find confirmation as well: In the simplest form, a MA crossover rule operates on the assumption that buy signals are generated when the current stock price crosses its moving average from below while sell signals are generated when the stock price crosses its moving average from above. The rationale for this interpretation is that a trend is said to have emerged when the stock price penetrates the moving average. Specifically, an upward (bullish) trend emerges when the price rises above its moving average, while a downward (bearish) trend emerges when the price falls below its moving average.6

The price crossover is especially interesting to observe when it moves from the extreme of one side and then to the other—trending first above and then below the two MA lines (or vice versa). This price pattern volatility represents a momentum shift, helping with short-term trade timing and potentially marking the start and stop times of secondary trends. When a secondary trend first appears, it is impossible to know what will occur next. Will the new trend emerge as a reversal and the start of a new primary trend? Or will it truly be restricted to a secondary move, with a return to the previous primary trend? Key Point: Price crossover moving from one side of MA to the other may indicate a momentum shift but could also represent a confusing set of signals.

This is where price crossover provides insight. Once the crossover emerges, it becomes a new primary trend only if it can hold onto its new direction. However, if price reverses again and moves across the MA lines in the opposite direction, it is most likely that the prior primary trend will then continue. This pattern is seen in the chart in Figure 11.5. It begins with a seventeen-month primary trend, during which price remains above both MA lines for the first twelve months before it begins moving below the fast MA.

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primary bullish trend secondary bearish trend

bullish crossover

Source: Chart courtesy of StockCharts.com Figure 11.5: Price crossover, bullish

The primary bull trend dominated the chart until the downtrend began in early June 2014. At this point, price first moved between the two MA lines and then gapped below at the point of a bearish MA crossover (fast MA crossed below slow MA). The resulting downtrend continued at that point, concluding in October; this trend lasted only five months. The reversal point moved from below both MA lines to gap above in December. This identified the secondary trend with high confidence that the primary trend would continue. In fact, a bullish MA crossover occurred in mid-January and price continued rising to nearly $9 per share by March 2015. This signaled that the previously established primary bullish trend was continuing. The five-month downtrend was a secondary trend and analysis of the price crossover patterns confirmed this. A bearish crossover works in the same manner. The switch from price movement above both MA lines (as a signal of a bearish move to follow) is likely to be followed by a bearish trend. The next chart in Figure 11.6 provides one example of this type of signal.

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price crossover, bearish

bearish signal

primary downtrend

Source: Chart courtesy of StockCharts.com Figure 11.6: Price crossover, bearish

The first signal of a bear trend to come was located between late April and late May, when price moved strongly above both MA lines. Price immediately fell below both lines by June and then consolidated until late August. After this, a strong downtrend began. Price fell rapidly and reached as low as nearly $5 per share by March 2015. Key Point: Although price crossover is a strong signal, it remains a lagging indicator and therefore should be used not as an initial signal but as confirmation.

It could be argued that the fall in price below both MA lines was a bullish signal, but there is a subtle difference. In the initial bearish signal, price exceeded range while MA lines had converged. The bearish signal was strong. However, once a strong downtrend began and took off strongly in September, prices fell so rapidly that MA lagged behind, with the space between MA and price widening. This was not a momentary move of price away from MA but an indication of the momentum of the downtrend. An analysis of the April–May price crossover above MA, and the price levels below MA lines from September onward, revealed the difference. One was clearly a signal while the other augmented MA’s tendency to lag behind price (especially the slow MA).

MA Double Crossover Whenever one MA line crosses another, it is referred to as a double crossover. This signals the beginning of a new trend or confirms a reversal signal occurring at the same time or immediately before. A bullish crossover is created when the fast MA crosses above the slow MA. A bearish crossover occurs when the fast MA crosses below the slow MA. Both forms of

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the double crossover are lagging indicators, so they will work as confirming signals rather than as initial reversal signals. An example of the double crossover forming as a bullish signal is seen in the chart in Figure 11.7. Although the downtrend preceding this was not long in duration or very strong, three things occurred at the same time. First was a convergence of the MA lines between late January and late March. Second was a whipsaw consisting of a bearish double crossover followed immediately by a bullish crossover. Third was the movement of price from above both MA lines, to below, and then back to above; a strong bullish move leading to continued uptrend for the next three months. The strength of the uptrend appeared in the fact that price remained above both MA lines throughout the period.

bullish crossover

Source: Chart courtesy of StockCharts.com Figure 11.7: Double crossover, bullish

In this case, the bullish crossover was especially strong, consisting of ten consecutive white candlestick sessions at the point of final crossover. If resistance was marked at the $54 level, prices went through a breakout in late April. If resistance was marked earlier at $56.50, the bullish breakout occurred in mid-June. In either case, the primary trend clearly was bullish, with the double crossover signals confirmed by the breakout above resistance. The bearish double crossover is the opposite of a bullish one, with the fast MA crossing below the slow MA. For example, in Figure 11.8, the fast MA declined rapidly from January through mid-March when it crossed below the slow MA. This signaled a bearish sentiment and the crossover point marked the beginning of that new primary bear trend.

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bearish crossover

Source: Chart courtesy of StockCharts.com Figure 11.8: Double crossover, bearish

The chart in Figure 11.8 was also marked by a set of repetitive price gaps. The January gap preceded the double crossover; the March gap occurred immediately after. In early August, the gap was an exhaustion gap signaling the end of the downtrend and the start of a new consolidation trend. The early November gap moved price below the fast MA but did not move much lower. The consolidation trend lasted until the end of January 2015, after which a new uptrend began, moving price from $42 to $60 in two months. Key Point: MA crossover may occur as part of the immediate trend, but when excessive price gapping is also present, it might indicate increased volatility and less certainty.

On the chart in Figure 11.8, the double crossover was framed by price gaps, first downward and then upward, and identified a point where the six-month downtrend began. The consolidation at the end of the chart spanned only 4 points, and this narrow breadth held until the strong bullish breakout in February 2015.

Resistance and Support An added benefit to MA is that it often strengthens the analysis of trends by providing additional confirmation of resistance or support. These levels are normally associated with price alone, but when price and MA track the same level, it indicates continuation of the trend. Until price crosses below both MA lines (in an uptrend) or above both MA lines (in a downtrend), the trend remains in effect. This does not mean that MA becomes resistance or support. Those levels are strictly marked by current prices. However, the fact that MA might track resistance

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or support closely confirms the strength in the current breadth of trading and makes continuation of the trend more likely than in a situation in which MA does not track resistance or support as closely. An example of MA tracking resistance is shown in Figure 11.9. Price moved downward strongly enough to maintain its position below both MA lines for the entire six months, with only brief moves above the fast MA line, followed by immediate retreat.

Source: Chart courtesy of StockCharts.com Figure 11.9: MA as resistance

The large downward gap in mid-June could be a reversal signal; however, it is important to acknowledge that the entire chart reflects a primary downtrend. Before identifying any signal as a change in a primary trend, significant confirmation was a requirement. This development at the conclusion of the chart was uncertain, and this pattern should be watched to discover whether the downtrend would continue, move into consolidation or reverse. MA also tracks support during uptrends. The fast MA is the most likely tracking average in most instances. However, in the chart in Figure 11.10, both MA lines provided a tracking feature—the fast MA remained close to price range while the slow MA remained lower but evolved in a pattern of consistent movement, looking very much like a trendline.

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Source: Chart courtesy of StockCharts.com Figure 11.10: MA as support

The closeness of the fast MA to price was the strongest attribute of this chart. The minor retreats below fast MA returned to range quickly. One reason for the close tracking of both MA lines was the exceptionally narrow breadth of trading throughout these two years. The range remained in a 2-point range most of the time during these two years, accounting for the close tracking of the fast MA and price and for the consistent rise of the slow MA and close tracking between the two. The price space between the two MA lines remained below 4 points for the entire two years, making this a bullish primary trend with low volatility. Key Point: When both MA lines remain close to other another, it confirms that the narrow breadth of price will continue—at least until the MA lines begin to diverge.

MA analysis must be undertaken with caution because these are lagging indicators. Even instances of divergence occur mainly as a lagging confirmation signal for other signals. A second use of MA is applied in momentum oscillators. The next chapter demonstrates how trend analysis is strengthened by comparing price with momentum.

Endnotes

1 Neftçi, S. “Naïve Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of Technical Analysis.” Journal of Business, 64 (1991): 549–71. 2 Hudson, R., M. Dempsey, and K. Keasey. “A Note on the Weak Form Efficiency of Capital Markets: The Application of Simple Technical Trading Rules to UK Stock Prices - 1935 to 1994.” Journal of Banking and Finance, 20 (1996): 1121–32. 3 Bigalow, Stephen W. and David Elliot. “Day-Trading with Candlesticks and Moving Averages.” Futures (2004): 40–42. 4 Gunasekarage, Abeyratna, and David M. Power. “The Profitability of Moving Average Trading Rules in South Asian Stock Markets.” Emerging Markets Review, 2, issue 1 (March, 2001): 17–33.

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5 Senthamarai Kannan, P., M. Sailapathi Sekar, M. Sathik, and P. Arumugam. “Financial Stock Market Forecast Using Data Mining Techniques” (Proceedings of the International MultiConference of Engineers and Computer Scientists, 2010, Vol. I). 6 Fong, Wai Mun, and Lawrence H. M. Yong. “Chasing Trends: Recursive Moving Average Trading Rules and Internet Stocks.” Journal of Empirical Finance, 12, issue 1 (January 2005): 43–76.

Chapter 12 Momentum Oscillators: Duration and Speed of a Trend Momentum reveals the character of a trend. It is not an indicator about price or direction of price movement, but a measurement of strength and of how that strength increases or decreases during the trend’s life. In all statistical analysis, the concept of exhaustion applies. This means that no trend continues indefinitely. It eventually will slow down, stop, or reverse. An analysis of price reveals direction and movement, but momentum is a separate attribute of price. It defines trends in terms of when or if those trends move into a range of overbought or oversold. These areas are measurable and occur when reversal is most likely. An overbought condition simply means that the price has been moved too high, too fast and that buying momentum has become excessive. As a result, the most likely next step will be for price to reverse and move back within the middle range measured by momentum. Oversold is the same attribute on the opposite side. Once a momentum oscillator moves down into the oversold zone, the next and most likely step is reversal and a price increase back into the middle zone. Key Point: Every trend eventually slows down, stops, or reverses. These changes are measured by momentum oscillators.

This distinction by zone—overbought or oversold versus a middle zone—is what gives momentum oscillators great value. In a normal balance between buyers and sellers, the calculated oscillator will reside in between overbought and oversold. There will be occasional moves into overbought or oversold, but these will not last long. The index created through oscillators is a measurement of momentum; the oscillator may perform as either a leading or a lagging indicator. In either case, the three major oscillators analyzed in this chapter add great value to trend analysis and, as confirming signals, increase confidence in the conclusions drawn about the health of the trend.

The Nature of Momentum Those studying trends realize that every trend has its own distinct character. Some are very fast and steep, lasting only a matter of days or weeks. These are swing trends and are the most common form of trend. Therefore, a part of trend analysis is the requirement that momentum be identified without difficulty. In a short-term trend, movement into overbought or oversold is a valuable signal that it is a swing trend and not a new secondary or primary trend. DOI 10.1515/9781547401086-012

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In the moment, it is a challenge deciding whether reversal is only a retraction to last a few sessions, a swing trend, reversal of a secondary trend, or the beginning of a new primary trend. A key to determining the nature of reversal is to track momentum along with price and volume signals. When the new direction continues with strength in all the indicators, including momentum, it is likely that the reversal represented more than one of those fast retracements or swing trends. This is especially applicable when proximity of reversal is at the proper point for a new and strong trend. This means that prices have moved through resistance or support and then reversed strongly; and this likely reversal is at its strongest with price gaps and volume spikes occurring at the same time. One of the basic principles of technical analysis is that failed breakout is likely to create a new trend moving in the opposite direction. This can include the potential for movement with enough momentum to break through the other side of the trading range. A failed move above resistance might easily signal the beginning of a new primary or secondary bear trend; and the same type of move below support often marks the beginning of a new primary or secondary bull trend. Key Point: The measurement of failure in a breakout is also a signal of lost momentum—and reversal.

The failed breakout is not a cause of the new trend, and it is not always a strong signal of a new trend in the opposite direction. Following breakout, price might only return into range as part of the existing trend. However, the breakout is significant when price is analyzed in conjunction with momentum. It is unlikely that a new trend begins from mid-range with low volume and the lack of any specific reversal signals. In reviewing past reversals at the beginning of primary trends, it is most likely that the signals will be found. Strong primary trends tend to be predicted with strong reversal signals and, quite often, by many signals. In many cases, these include a strong move in an oscillator into the overbought or the oversold range before or during the formation of a reversal. This reveals a key principle about momentum. It is not the same as a price pattern but a summary of the trend’s strength or weakness. Strong reversals tend to lead to strong trends, and when momentum indicators report a strong move, this only adds to the strength of reversal. An analysis of strength or weakness in price patterns and corresponding momentum is part of a larger picture within the science of trend analysis. Prices do not evolve in a vacuum, and technical moves—price patterns, volume, moving averages and of course, momentum—are not the cause of trends but symptoms of a larger reality reflecting supply and demand over the long term. Trends do not reverse because a technical signal predicts reversal; those signals are the visual representations of reversals collectively due to the supply and demand for a company’s stock, fundamental strength or weakness, news about a company, earnings predictions and final reports, mergers and acquisitions, dividend declarations, decisions by institutional traders

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to buy or sell large numbers of shares, and the intangible factors—rumors, hopes, or fears about a company’s future, its products, competitive position, economic impact in domestic and geopolitical changes, and other (often unknown) influences. All these collective influences on price and on trends represent what takes place over time. Anticipation of a trend’s strength and, equally important, of a coming weakened state and end, are reflected in momentum oscillators. These include relative strength index (RSI), moving average convergence divergence (MACD), and the stochastic oscillator.

Relative Strength Index The relative strength index (RSI) is a momentum oscillator based on a created index value between 0 and 100. If the oscillator calculates out to the mid-range, the current trend is not in danger, but if it moves above 70 the stock is overbought and if it moves below 30 it is oversold. This applies to trends of all durations. Swing traders rely on RSI to track the daily trend and to look for confirmation of reversal found in price and volume signals. When RSI moves above 70 or below 30, it tells a trader that the short-term trend is likely to reverse. For secondary trends, the tracking mechanism is the same and may signal a return to a primary trend. However, in using RSI to track primary trends, a move into overbought or oversold range does not necessarily generate a trade. Primary trend observers understand that RSI often moves above 70 or below 30, only to immediately retreat into the oscillator’s midrange. Key Point: Moves into overbought or oversold territory signal potential reversal but do not always require an immediate trade.

RSI becomes significant—notably in tracking of primary trends—when the oscillator moves into overbought or oversold range and remains there longer than just a few sessions. It is even more significant when the oscillator moves further into overbought or oversold range. The farther it moves, the stronger the likelihood of a reversal. The range levels of 70 and 30 are the normal settings for RSI. These can be adjusted to suit a trading strategy. By moving them to 80 and 20, for example, occurrences of overbought or oversold will be reduced; by moving the lines to 60 and 40, RSI will move into overbought and oversold far more often; but reliability of the oscillator is also reduced when frequent signals are located. Therefore, 70 and 30 are applied in most cases to decide when a stock becomes overbought or oversold. In trend analysis, movement into overbought or oversold is only one way that momentum can be studied. Another involves the speed of change. If the oscillator is trending rapidly toward the 70 or 30 lines, it indicates growing momentum and a likely move into the overbought or oversold area of the index. This is especially true

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when price is close to resistance (and RSI is moving strongly toward 70) or support (and RSI is moving strongly toward 30). This “momentum of momentum” is significant because it reveals growing strength in a specific direction. Contrarian investors acknowledge that markets tend to overreact to news. This overreaction is reflected if RSI changes rapidly while moving in a specific direction with price proximity to resistance or support also evolving toward potential breakout. A considerable difference should be acknowledged between momentum barely moving above 70 or below 30 versus an extreme move into those zones. The further above 70 or below 30 the indicator moves, the stronger the chances for a corrective reversal. Finally, the true deciding point is not whether RSI shows a move into overbought or oversold, but how long it remains there. A tendency seen on most stock charts is for RSI to remain in the middle zone most of the time, with moves above 70 or below 30 very brief and that correct rapidly. When the RSI oscillator remains in overbought or oversold status for an extended period, the signal is that the trend is weak and likely to stop moving or to reverse. The best way to appreciate what RSI reveals is to understand how it is calculated. Even though free charting services calculate the oscillator as part of a chart, this awareness of what RSI reflects is likely to improve the skill of trend analysis. RSI is calculated over fourteen consecutive sessions. First, all upward-moving closing prices are added together. The exponential moving average (EMA) is then calculated. Next, all downward-moving sessions are added together. The EMA for this group is then calculated. The upward-closing EMA is divided by the downward-closing EMA to determine relative strength: EMA (upward) ÷ EMA (downward) = RS The index value is derived from RS as a final step: 100 – (100 ÷ (1 + RS)) = RSI This creates a value between 100 and 0. With the formula in mind, it makes sense that RSI will normally reside between 70 and 30. Over the most recent fourteen sessions, the net effect of rising and falling days will tend to revert to the mean so that moves above 70 or below 30 are the exceptions. Once the index moves above 70, conditions are overbought and a bearish signal is given; and once it moves below 30, the oversold condition produces a bullish signal. Key Point: Moves above 70 and below 30 in the RSI index are exceptions; based on how the index is calculated, value is normally found at midrange.

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Given the method for calculating RSI, it makes sense to view overbought and oversold moves as exceptions. An analysis of a primary trend over many months reveals that RSI moving into overbought or oversold is the exception and that most of the time, RSI will reside between 70 and 30. The chart in Figure 12.1 makes this point.

bullish thrusting lines (continuation)

bearish abandoned baby falling wedge (bullish)

overbought

oversold

hammer

Source: Chart courtesy of StockCharts.com Figure 12.1: Relative strength index (RSI), primary trend

The stock in Figure 12.1 was undergoing a gradual bearish primary trend, which continued beyond the period charted. With the usual movement quite mild and with small breadth of trading, RSI did not give out much of a signal in the first two months. During this period, breadth of trading was approximately 1 point. Once price levels began falling, however, the RSI line also trended from a midrange of 50 all the way down to 30. As a lagging indicator, RSI reflected the changing sentiment among buyers and sellers; however, the rapid price decline, even in a primary bear trend, was disturbing because of its momentum. Once RSI moved below 30 in late September, a reversal to the upside was expected. This secondary bullish trend was further predicted by the bullish signal in the form of a falling wedge between August and September. The reversal point was located at the point that RSI moved well below 30 and a hammer formed. This candlestick reversal was confirmed by the confirmation signal in the form of a thrusting lines indicator. As it often occurs, the reversal moved beyond the established trading range and trended above the long-term resistance level. RSI went into overbought and remained there for most of November. This duration was unusual and served as a leading indicator for a likely return to the primary bear trend.

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This was confirmed by the abandoned baby signal in early December. At this exact point, RSI had also declined back into midrange. In this example, RSI confirmed what price movement revealed and identified the extremes of oversold and overbought. In the short term, these secondary trend movements (first a bearish move from September to mid-October and then a bullish move from mid-October to early December) were clearly identified and confirmed by RSI. For the rest of the period charted, RSI resided between 70 and 30. Another example of RSI involves analysis of secondary trends. In the chart in Figure 12.2, RSI also marked the start and end of secondary trends in a long-term consolidation primary trend.

bullish harami

overbought oversold

Source: Chart courtesy of StockCharts.com Figure 12.2: Relative strength index (RSI), secondary trends

It appeared that the consolidation trend moved from a range of $104 to $100 and then to a lower range of $98 to $94. However, an analysis of what occurred over the period beyond this chart revealed the true consolidation range was between $104 and $94, the high of the earlier consolidation and the low of the later one. This might be difficult to track without the addition of RSI. Note that the initial move breaking out below support was marked by a decline in RSI into oversold. This predicted that the breakout would not succeed. However, the upward breakout did succeed after the appearance of the bullish harami and subsequent upward price gaps. Key Point: The value in RSI is how its signal is combined with other reversal signals in gaps, candlesticks, and volume, for example.

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The price breakout quickly moved into overbought. Even though price levels had moved much higher than previous trading range, the overbought conditions were accompanied by sideways price movement with very narrow range of two points or less. This predicted weakness in the bullish trend and in fact, three months beyond the period charted, price levels had returned to the consolidation range between $104 and $94. Even with secondary trend movement as high at $112, the primary consolidation trend held. This chart demonstrated another characteristic of momentum. Trends often become exhausted and stop with an expectation of a reversal, but this does not always occur. At times, momentum reaches a plateau and stops for a period. This plateau may be brief or extended. After the plateau, often forming a consolidation trend, the previous dynamic trend may continue or it may break out and move in the opposite direction. On this chart, the initial plateau declined to a lower plateau. This lasted for ten weeks, from August to mid-October. At the point of breakout, a new uptrend started and moved from $94 to $112 over the next two months. The plateau appears to be a pause in momentum, but this is not the only change in a trend’s behavior. No trend is likely to continue moving in the same direction without reversal, retracement, or plateau. In this sense, the plateau marks a period of settling down when previous momentum stops only to resume and for the trend to resume or reverse. The plateau is a critical momentum signal because invariably it, like all consolidation trends, is going to end. Knowing exactly when is the difficult part.

Moving Average Convergence Divergence Whereas RSI provides a readily recognizable single index value, moving average convergence divergence (MACD) involves three different moving averages. Its value is in its tracking of an ongoing trend, in the way it signals that a current trend has weakened and is coming to an end. Developed by Gerald Appel in the 1970s, MACD uses its three “time series” calculations based on the closing price. The first two are a fast EMA (twelve days of closing prices) and a slow EMA (twenty-six days of closing prices). Third is a signal line EMA of the last nine sessions. Several values of MACD include the divergence between the two EMA lines, the movement of both EMA signals above or below the signal line, and the degree of change in the signal line itself, above or below zero. The overall index value of MACD ranges from +1.00 to –1.00.1 The signals derived from MACD include crossover (when both averages cross over the signal line and move above (bullish) or below (bearish)); and divergence (developing and widening gaps between the two EMA lines). An upward swing is divergence of a bullish nature and a downward swing or expansion of the gap is bearish.

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An example of MACD in analysis of a primary trend is found in the chart in Figure 12.3. The steady price movement in this bullish primary trend explains why the signal line was above 0 for most of the period, but with very little change.

upside tasuki gap (continuation) rt

po

sup

retracement

bullish side-by-side white lines (continuation)

retracement bullish crossover

26 12

Source: Chart courtesy of StockCharts.com Figure 12.3: Moving average convergence divergence (MACD), primary trend

A more interesting observation is that the two EMA signals remained far above the signal line through most of the chart. In fact, the initial crossover in August marked the beginning of the primary bull trend, continuing until early December. At that point, both MACD lines started to decline. Although they did cross into bearish range by moving below the signal line, the signal was clear. The trend had either paused or ended. The dip in price and MACD turned out to be a retracement move only. The bullish side-by-side lines promised continuation. The fact that the MACD averages remained above the signal line by the end of the charted period indicated continuation as well. In fact, three months after the period charted, the primary bull trend was still in effect. In this case, MACD tracked the primary trend with strong consistency. If both EMA lines remained strong above the signal line, there was no immediate reason to believe the trend was in any danger. The first retracement (in late September) was followed quickly by a continuation signal in the form of an upside tasuki gap. The second retracement (in December) was more difficult to interpret. Both the twelveand twenty-six-day EMA lines declined rapidly. The only assurance of continuation was the failure of EMA lines to both fall below the signal line, confirmed by the bullish side-by-side continuation signal at the end of the chart.

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Key Point: One of the strengths in MACD is being able to rely on trend continuation if both MA lines remain on the same side of the signal line.

Tracking MACD over a series of faster-moving secondary trends involves greater volatility in momentum, as you would expect. The next chart, in Figure 12.4, is a good example of how MACD is used to identify the all-important turning points in the form of crossover.

bullish harami

bullish crossover

bullish harami

bearish harami cross

bearish harami

bearish crossover

bullish tasuki gap (continuation)

bullish side-by-side white lines (continuation)

bullish crossover

Source: Chart courtesy of StockCharts.com Figure 12.4: Moving average convergence divergence (MACD), secondary trends

The chart in Figure 12.4 is a busy one. On the momentum side, crossovers were prominent. The first bullish crossover lagged after the bullish harami at the bottom of the secondary trend. The subsequent reversal and new secondary bearish trend was marked by the bearish harami cross; as MACD lines crossed below the signal line, a bearish harami confirmed further bearish movement. However, another bullish trend began with the bullish harami at mid-October. The bullish tasuki gap continuation signal confirmed this trend at the same time as the bullish NACD crossover. In December, declining MACD lines failed to move below the signal line. At the same time, a bullish side-by-side white lines continuation signal indicated that the bullish trend was likely to continue. The fast-moving secondary trends dominated this chart. The confirmation from MACD crossover added a sense of order beyond the recurring candlestick signals.

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Stochastic Oscillator The stochastic oscillator combines two moving averages calculated with high and low prices as well as closing prices over fourteen consecutive sessions. The term “stochastic” refers to random probability, appropriately named with the use of two separate calculations to create an oscillator. The stochastic oscillator creates value between 0 and 100, with overbought conditions found above 80 and oversold below 20. In this regard, the stochastic oscillator is like RSI. It usually is a leading indicator since it is based partly on high and low price levels. Thus, for the analysis of some trends (especially primary trends), it often provides more useful and timely information than RSI. The difference between RSI and the stochastic oscillator is in the method used to find turning points. Stochastic calculation is a comparison between closing prices and price range. This takes advantage of a tendency of price itself. Prices tend to close near the extremes of the recent range just before turning points. In the case of an uptrend, prices tend to make higher highs, and the settlement price usually tends to be in the upper end of that time period’s trading range. When the momentum starts to slow, the settlement prices will start to retreat from the upper boundaries of the range, causing the stochastic indicator to turn down at or before the final price high.2 The calculation, combining price closings with price ranges, makes this oscillator more accurate than RSI, especially when price moves with increasing volatility. The first of two moving averages is based on fourteen sessions. This is also called the %k line. It is calculated as: 100 [( cc – lc) ÷ (hh – ll)] = %k In this formula, cc is the current closing price; lc is the lowest close of the past fourteen sessions; hh is the highest high; and ll is the lowest low. The second moving average is the average of the last three %k outcomes and is called the %d line: %k (three most recent sessions) ÷ 3 = %d The oscillator resulting from these calculations identifies overbought (above 80) and oversold (below 20) conditions. For example, the chart in Figure 12.5 represents six months of a primary bullish trend. However, during this period, secondary trend movement was marked clearly by the stochastic oscillator and its overbought and oversold conditions.

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stochastic oscillator, primary trend

double top

bullish harami

bearish piercing lines

bearish engulfing

overbought

oversold

%d

%k

double bottom

overbought

oversold

Source: Chart courtesy of StockCharts.com Figure 12.5: Stochastic oscillator, primary trend

The first secondary trend was identified by the double top, confirming the overbought signal in the stochastic oscillator. The two-week price decline concluded as the oscillator fell rapidly and moved into oversold. At that point, a bullish harami confirmed a likely reversal and resumption of the primary bull trend. Key Point: The stochastic oscillator, like RSI, is based on identification of overbought and oversold, but it also needs strong confirmation to generate a trade.

The oscillator remained in overbought from mid-August through late September, a period of exceptional length. The longer it remained there, the greater the chances for a bearish reversal. The piercing lines signaled this as the stochastic oscillator once again declined. Like the previous decline, this drop was also rapid and moved into oversold as a double bottom signal appeared. The stock was once again marked as overbought from late October to late November and during the first half of December. The lagging bearish engulfing confirmed a secondary bearish trend. However, even with consolidation resulting through midMarch 2015, the direction of this trend eventually resumed its bullish movement. The stochastic oscillator is equally effective at identifying turning points in secondary trends. Figure 12.6 provides an example of this.

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three white soldiers

three black crows

bullish doji star

bearish harami

evening star overbought

overbought

oversold oversold

Source: Chart courtesy of StockCharts.com Figure 12.6: Stochastic oscillator, secondary trends

In Figure 12.6, the initial three black crows lagged the stochastic overbought condition. This was followed quickly by three white crows and then a bearish harami, defining a very fast secondary bull trend. The resulting bear trend continued for more than a month, and during this time the oscillator moved into oversold until the bullish doji star confirmed a likely bullish reversal. However, the duration of the resulting overbought status, from late October through late November, was confirmed by the bearish evening star. This bearish warning predicted a decline in price. In January, a large one-session gap of 10 points set up a consolidation range between $91 and $85, remaining in effect through the end of March 2015. The stochastic oscillator, like RSI and MACD, provides confirmation value and in some instances, leading indication of coming change. However, while the consistency of momentum trends is consistent, it cannot reveal the extent of the response likely to occur. Momentum is the most reliable of timing signals for trends of all lengths. The next chapter expands on the observation about momentum by examining technical volatility of stocks. If volatility is another word for “risk,” stock charts make risk highly visible, especially in the extremes of high volatility.

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1 Appel, Gerald. Technical Analysis Power Tools for Active Investors. Upper Saddle River, NJ: FT Press, 2005, p. 166. 2 Person, John L. A Complete Guide to Technical Trading Tactics: How to Profit Using Pivot Points, Candlesticks & Other Indicators. Hoboken, NJ: John Wiley & Sons, 2004, pp. 144–45.

Chapter 13 Volatility: Marking Risk within the Trend The term “volatility” describes unpredictable price movement, fast directional swings, and overall risk involved with investing. Volatility is price uncertainty. Prices can and do move even when volatility is low, and volatility does not forecast or predict price movement in either direction. It is a mistake to equate volatility (market risk) with price movement or its symptoms. In times of high volatility, risks are greater but so is profit potential. Depending on whether you are tracking a primary or a secondary trend, volatility in the trend itself reveals a lot. For a primary trend, increasing volatility could forecast the end of the trend and for a secondary trend, volatility often forecasts a quick return to the primary trend. In swing trends, volatility offers great opportunity for fast profits if trade timing is made skillfully and based on strong signals and confirmation. Key Point: Volatility signals the end or reversal of a trend but not price direction, or it may reveal uncertainty within the trading range.

In a consolidation trend of any duration, interim volatility reveals the inability among both buyers and sellers to move price beyond the range-bound breadth of trading. However, when volatility increases within the consolidation trend, it often signals that a breakout is becoming more likely. Typical of this condition is seesaw swings between resistance and support even as the consolidation continues, at times for several months or even years. Consolidation is a frustrating trend for those traders looking for price action or for investors seeking capital gains. However, if the trading range is wide enough during consolidation, short-term profits are possible. The predictability of the trading range adds to the certainty of trades. In comparison, in a high-momentum bullish or bearish trend, reversal is less certain and timing of trades may offer lower degrees of certainty. These are generalizations about volatility and the entire matter is uncertain. Any attempt to quantify volatility is going to be an estimate and cannot clearly define the next price direction. The best you can hope for is an indication that, once confirmed, points to dynamic price continuation or change.

Calculating Volatility A few methods for defining and calculating volatility help manage trends and spot possible changes in the future. However, the number of points of a stock’s movement is not a reliable volatility test. The scaling of a chart determines volatility as a relative matter. For example, a chart scaled in 1-point increments and experiencing a 3-point DOI 10.1515/9781547401086-013

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move might be extremely volatile (based on typical daily price changes). However, another stock scaled with 10-point increments and experiencing the same 3-point move might not reflect high volatility. It could point to low or declining volatility due to the relative point change in a typical session versus the 3-point move itself. Another way to define volatility is to calculate a “breadth test.” This is a comparison of the fifty-two-week breadth of trading to the current breadth. For example, if the current breadth is 6 points and the fifty-two-week high/low is $67 to $52, the breadth test is: 6 ÷ (67 – 52) = 40% A big problem with this method is that the fifty-two-week breadth is not the last word in breadth of trading. Several problems arise, including: 1. Spikes distort the analysis. For example, in a 15-point range over fifty-two weeks, the “typical” range could be closer to 4 points, with one 11-point price spike. A spike is exceptional and non-repetitive, and as soon as it appears, price levels will immediately return to the established breadth. In removing the spike, the relative impact of a price move is not the same as when the spike is included. With a smaller fifty-two-week high/low range, that 6 points of current breadth of trading is more volatile than with the spike left in the calculation. Key Point: The breadth test measures price volatility in one respect, but it is reliable only if spikes are removed.

2. Trend during the fifty-two weeks will also distort the conclusion but not the outcome. Whether the breadth test results in 50.0 percent or 27.3 percent, what does it mean? Did the high price during the fifty-two weeks occur closer to the beginning of the year (meaning a primary bearish trend is in effect)? Or did it occur at the end of the fifty-two weeks (meaning a primary bullish trend is in effect)? Did the price at the end of the year approximate price at the beginning, with the price level advancing and retreating during the year? All these patterns contain different meanings and require different interpretations. The conclusion you reach based of where high and low prices occurred is crucially important in defining the volatility expressed in the current range. This is even more difficult to quantify if the fifty-two-week breadth involved numerous swings between high and low, in which case the current breadth of trading does not indicate the strength or weakness of the trend, nor a likely direction in the case of breakout. You might understand the breadth test without knowing very much about the health of the current or the next trend. 3. Proximity of current prices in relation to the high/low range also carries great weight in interpreting breadth as a form of volatility. Successful reversal is most likely to occur when price levels are close to resistance or support (successful

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breakout is also most likely if confirmed at the same proximity). The true definition of volatility may need to rely on the significance of proximity more than on the breadth of trading. 4. Changes in breadth in recent weeks is revealing in trend analysis. The trend’s health may be more readily understood if the breadth of trading has been broadening or narrowing in recent weeks. In practice, trend analysis relies on changes or lack of changes in the breadth of trading and not so much on the breadth test as a definition of the trend’s health.

Volatility Indicator A statistical test of volatility attempts to quantify volatility by comparing the latest closing price to the average closing price based on standard deviation. This will be influenced by the number of days selected in the test. This indicator is calculated by finding standard deviation and dividing it by the average closing price for the same number of periods: V = (σ cpn) ÷ (cp ÷ n) where: V = volatility σ = standard deviation cp = closing prices n = number of periods This calculation may be performed against n periods of several days or over several years. It produces a version of volatility based on one standard deviation; in comparison, Bollinger Bands accomplishes the same comparison basis but uses two standard deviations, one above and one below the middle average. This enables an analyst to spot widening or narrowing breadth of trading and to anticipate coming changes. For example, as Bollinger Bands width and price breadth both narrow within a consolidation trend, it signals a likelihood of a breakout in the near future. Key Point: Calculated volatility is a result of applying standard deviation, but Bollinger Bands is a more accurate test of the same tendencies within a trend.

The more stringent statistical application of Bollinger Bands compared to this volatility indicator make the bands approach a more reliable indicator of trend health and, as a result, of volatility. The purpose of volatility testing is to spot evolving risk levels within trends (bullish, bearish, and consolidation) and to use the technical price patterns developed from Bollinger Bands to identify volatility and trend strength.

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Evolving Volatility Levels Beyond statistical analysis of volatility and development of indicators like Bollinger Bands, specific patterns evolve that reflect growing or shrinking volatility. Whereas Bollinger Bands may be thought of as a trend-based form of probability matrix, these changing trend characteristics are more reliable for anticipating changing volatility. A broadening price formation signals increasing volatility. As the breadth of trading expands, so does the likelihood of other volatile signals, such as price gaps. For example, Figure 13.1 shows a breadth of trading broadening over nine months, from June 2013 through February 2014.

Source: Chart courtesy of StockCharts.com Figure 13.1: Broadening breadth of trading

In this example, breadth moved from only 2 points up to as much as 20 points, a strong expansion of breadth, and of volatility. It is particularly interesting to note that the period between the end of this broadening formation and the gap near the end of July, was followed by a return to a narrow breadth. By the end of March 2015, prices settled into a range between $82 and $74 as a further phase in this long-term primary bull trend. Decreasing breadth takes the form of either a wedge or a triangle. For determining the significance of each, caution must be exercised. The difference between wedges and triangles often is only slight, but the interpretation is opposite. A rising wedge signals bearish reversal, but an ascending triangle points to bullish continuation; and a falling wedge is a bullish reversal signal while a descending triangle indicates bearish continuation. In both instances, the decrease in the breadth of trading signals falling volatility. For example, Figure 13.2 reveals a chart with a rising wedge over four months, a six-

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month consolidation, and a falling wedge lasting nearly three months. The falling wedge was bullish and was followed by a strong upward surge in late November.

Source: Chart courtesy of StockCharts.com Figure 13.2: Narrowing breadth of trading—wedge

The problem with these wedges is that they can be interpreted in several ways. For example, the falling wedge could be interpreted as a descending triangle (bearish) by moving the support line down to $70 per share. That would have been a misleading signal, as price settled at a support level of $80 through the three months following the period shown. Key Point: The similarity between wedges and triangles—and their opposite interpretation—makes them questionable signals for reversal timing.

With this uncertainty in mind, wedges are best used to confirm strong reversal or continuation signals found at the same time, but not relied upon as particularly strong signals on their own. However, whether bullish or bearish, the narrowing breadth of trading reveals a reduction in volatility. In the perspective of a primary trend, this is valuable information forecasting that big price moves are not likely soon. The triangle is stronger than the wedge because it relies on a flat resistance (ascending) or a flat support (descending). The longer this flat period, the more reliable the triangle is as a directional signal and a sign of declining volatility. For example, Figure 13.3 contains several triangles over two years. This displays a narrowing of volatility. In the first triangle, breadth of trading went from approximately 15 points down to about 6. This breadth held through to the end of the period charted. However, from October to December volatility appeared to be increasing.

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Source: Chart courtesy of StockCharts.com Figure 13.3: Narrowing breadth of trading—triangle

After the first two ascending triangles, a descending triangle (bearish) appeared between August and October. This forecast a price decline to follow. By the end of March, prices did fall to settle at under $80 per share. Given the overall breadth of trading in the last portion of the chart, the price decline appeared to accompany a secondary trend with low volatility. Volatility also evolves by changes in the frequency of price gaps. As gaps begin showing up more often, volatility increases, and as gaps decline, so does volatility. For example, in Figure 13.4 a consolidation trend extended from May to the end of the chart (and beyond to the following March). Within this primary consolidation trend, numerous secondary trends were characterized by a growing number of gaps.

Source: Chart courtesy of StockCharts.com Figure 13.4: Increasing gaps

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The gaps appeared in various configurations. The first two marked an island cluster in October. The third preceded a price swing. The fourth, fifth, and sixth gaps were small but marked the approach to resistance without breakout. The final gap was much larger and approached support before reversing. All these price swings revealed the strength of the consolidation trend. None of the swings were able to break through resistance or support. This demonstrates that even with high volatility like the kind found on this chart, breakout is not guaranteed. The volatility affects the secondary trends without affecting the overall strength of the primary consolidation trend. Volatility declines as the frequency of price gaps declines. In Figure 13.5, an example of this pattern is summarized.

resistance

Source: Chart courtesy of StockCharts.com Figure 13.5: Decreasing gaps

Over a six-month period, only three visible gaps worth noting were identified. Several hidden and smaller gaps were not highlighted as they were common gaps and had no specific signal value. The pattern involved 5 points of breadth over the period, but the key observation is that throughout the period, resistance held—until it broke in late December. Although price retreated temporarily, the breakout forecast a successful breakout and a bullish move in price by March to approximately $57 per share. This marked two important changes: volatility declined through the period and the breakout marked a new bull trend. Whether it was primary or secondary was not established until March, but the direction and decrease in volatility were clear. Key Point: Declining volatility associated with post-breakout periods confirms the likelihood of success in the newly-established trading range.

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A third way in which volatility is labeled as increasing or decreasing is in the volume trend. While volume may spike or move according to specific volume indicators, increases or decreases in typical volume mark changes in volatility. Increasing volume equals greater price volatility, and decreasing volume indicates reduced volatility. As the volume level evolves, it is likely that changes in breadth of trading will be found as well. An example of increasing volume is shown in Figure 13.6.

Source: Chart courtesy of StockCharts.com Figure 13.6: Increasing volume

Before the price decline starting in October, the breadth of trading was quite narrow at about 1 point. However, volume levels had been increasing since early July, culminating at the first price decline through mid-October. At that point, breadth of trading grew to approximately 4 points. A second decline between late November and mid-December saw a continuation of increasing volume and expansion in breadth of trading to 10 points. The chart in Figure 13.6 reveals the close relationship between increasing volume and growing breadth of trading. Together, these provide a picture of growing volatility that continued beyond the period shown. This major oil company was in a primary bearish trend during a period when oil prices fell from over $100 per barrel to under $50. This made the bearish primary trend not surprising, but the condition of the decline was laid out in the combined pattern of increasing volume and broadening breadth of trading. Decreasing volume reveals reduced volatility and may not reveal as clear a change in the breadth of trading as the opposite, increasing volume pattern. This is so

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because decreasing volume tends to hold breadth of trading to a very narrow span. If the period starts out with a narrow range, the span is less likely to become narrower and more likely to remain consistent even if price moves substantially higher or lower. For example, in Figure 13.7, the price doubled over two years, but over the last fourteen months volume levels decline. At the same time, breadth of trading maintained an average of 5 points, increasing at times to as much as 10 points due to retracements or secondary trends. However, the primary bullish trend was consistent throughout the two years.

Source: Chart courtesy of StockCharts.com Figure 13.7: Decreasing volume

A recurring set of retracements is reassuring in a chart like this. No one expects a primary trend to move in the same direction without pause over two years. Retracements reflect both profit taking and testing of momentum. However, in this example, the pattern of bullish price movement with decreasing volume revealed falling volatility.

Average True Range The use of average true range (ATR) does identify volatility. However, it can be adjusted so that selection of ranges and dates may easily create a desired result. ATR should be used as a comparative indicator to confirm other signals. ATR was developed in the late 1970s by J. Welles Wilder to demonstrate how growing and shrinking breadth of trading is reflected in volatility.1

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Key Point: ATR can be modified to create a desired result. Confirmation bias should be kept in mind when using this indicator.

The indicator points to a high likelihood of volatility at price tops and bottoms in a manner like momentum indicators such as RSI. The assumption with ATR is that when the index is mid-range, volatility is low. The analysis is usually performed over fourteen consecutive days. There are many ways to define true range, which is the starting point for calculating the index. Three examples of true range—high minus low, prior close minus low, and current high minus previous close—are summarized in Figure 13.8. ---------------

---------------------------

-------high minus low

-------prior close minus low

--------------current high minus previous close

Source: Prepared by the author Figure 13.8: Types of true range

Because true range is the result of the greater of these three choices or selection of others, it reflects a range of trading breadth for a specified period. By itself, true range may give off an artificial perception of volatility; however, when studied as an index of fourteen periods, it reports the trend toward increasing or decreasing volatility and a comparison to proximity of price. An example of ATR compared with ranging price versus peaks and how these are reflected on ATR, is shown in Figure 13.9.

Average True Range 

low while price is ranging

 281

peaks at price bottom

Source: Chart courtesy of StockCharts.com Figure 13.9: Average true range (ATR)

When price was ranging (adhering to established breadth of trading), volatility was expected to be low, and this clearly was established by comparing the price pattern to ATR. However, once price became dynamic in either a bullish or bearish move, volatility was expected to increase dramatically. In this example, price bottomed out in mid-October after a three-week decline and bottomed once again in mid-December following a two-week decline. In both instances, volatility as measured by ATR peaked as well. ATR is a relative indicator, meaning its strength as a test of volatility is based on behavior of the index next to price behavior. Notice, for example, the extreme rise in the ATR index in the last week of October, corresponding to the large black candle session at the same time. This reflected the corresponding price to calculated ATR as a factor of the change, but it also demonstrated a characteristic of volatility: it moved based on the degree of change in price, regardless of price direction. For example, at the end of the chart, price breadth narrowed in the last two weeks, but ATR had not returned to the low levels established in the first two months of the chart. This indicated that while volatility had declined, it was not as low as it was at the beginning of the period.

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Volatility According to the VIX A final measurement of volatility worth mentioning is the Chicago Boards Option Exchange (CBOE) volatility index, or VIX. The VIX tracks the speed of index option change among the S&P 500 index of stocks. It produces a weighted average of estimated volatility. It is also called the “fear index” as it reflects investor nervousness about price levels in the S&P 100, meaning movement in the VIX reflects overall volatility. However, VIX is removed from direct volatility in stocks. It measures the implied volatility of options rather than directly tracking stocks. The concept of a financial index measuring stock index volatility was first proposed in 1989.2 Key Point: The VIX measures volatility in the moment, but because volatility moves quickly, it is only one of several volatility indicators worth tracking.

Based on the introduction of an index-based measurement of market volatility, CBOE hired Vanderbilt University professor Robert Whaley to develop a practical volatility index based on options implied volatility. The result was the VIX, which is used by many investors to time trades, especially trades within swing trends.3 Trend analysis must consider the volatility in price to judge the trend itself. Recognizing that volatility increases and decreases over time defines the finite life of every trend. However, volatility does not imply reversal or price direction; and prices may move, even strongly, in a bullish or bearish direction or as a consolidation trend, in times of both high and low volatility. This demonstrates the point that price movement, momentum and volatility are all attributes of trends, but lacking price patterns and specific reversal indicators, changes in volatility do not forecast changes in the trend. Volatility (risk) is a component of investing, and as it changes, so do the risks and opportunities of holding positions in a stock. The next chapter moves trend analysis out of the realm of the technical and shows how fundamental volatility ultimately affects stock trends. This does not always occur immediately, but fundamental volatility is one of many aspects that technical analysts should track. By being aware of how fundamental trends behave, some assumptions concerning future price movement can be made with a reasonable expectation of accuracy.

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1 Wilder, J. Welles Jr. New Concepts in Technical Trading Systems. Greensboro, NC: Trend Research, 1978, pp. 22–24. 2 Brenner, Menachem, and Dan Fand Galai. “New Financial Instruments for Hedging Changes in Volatility.” Financial Analysts Journal (July/August 1989) http://people.stern.nyu.edu/mbrenner/ research/FAJ_articleon_Volatility_Der.pdf. 3 Whaley, Robert E. “Derivatives on Market Volatility: Hedging Tools Long Overdue.” Journal of Derivatives 1 (Fall, 1993): 71–84.

Chapter 14 Fundamentals: Connecting the Two Sides Some investors favor the technical approach for selecting stocks and timing trades, while others rely solely on the fundamental approach. Both contain merits as well as setbacks. However, using both in combination improves overall information, reduces market risks, and adds to the chances for profits from well-selected and welltimed trades. Another point is worth mentioning: companies with strong fundamentals tend to also experience equally strong growth in stock value. This makes sense. The more profitable a company becomes and the more it increases the value of equity, the more valuable its share price. Although this might become apparent only over the long term and not immediately, it is also true for analysis of secondary trends within the longer-term primary trend. Consistent fundamental trends are more likely to be reflected in equally strong price trends, lower stock price volatility, and reduced market risk. Key Point: The connection between strong fundamentals and strong stock performance points to the advantage of using both types of indicators to pick stocks and for tracking long-term trends.

This chapter examines a few select fundamentals for four different companies. The fundamentals are dividend per share and payout ratio, P/E ratio, revenue and earnings, and debt to total capitalization ratio.

Value Versus Growth Most trend analysts focus closely on price trends as if they occur in a vacuum. Assigning momentum to supply and demand is legitimate, but that supply and demand interaction results not only from perceptions of market value in a stock, but also in the fundamental success (profitability) of a company, changes in dividends paid and payout ratio, and effective management of working capital. These collectively form the essence of fundamental analysis and define companies as value investments or growth investments. For technical investors deciding between value or growth, a problem becomes evident upon historical analysis. In some years, value investments outperform and in others the dominant force is growth. Neither side consistently outperforms the other. In selecting companies as investment candidates, a starting point is to examine fundamental indicators and trends over time, look for consistent growth and profits, and apply wise selection criteria to pick stocks whose fundamental trends support the resulting technical trends.

DOI 10.1515/9781547401086-014

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The concept of value investing, developed by Graham and Dodd, points to undervalued securities as potential bargains, or “value investments.” These value investments often are traded at levels well below market value of similar securities, and in extreme cases may approach or even move below tangible book value per share.1 A “growth” investment must be defined as one perceived to report higher success in terms of profits and market share over a period of years. Thus, investors in growth stocks expect to earn higher returns but also must accept higher market risks. A value investment is believed to be set at a bargain price, often measured by the price/earnings (P/E) ratio. Since the single number called the P/E is the result of a technical value (price) dividend by a fundamental value (earnings), it is a hybrid indicator. As a rule, a moderate P/E is best when it resides somewhere between 10 and 25 (so that the current price per share is equal to the profits to be earned in ten to twenty-five years). This multiple is how value investments are defined. Value investors seek bargains, meaning lower P/E stocks. Growth investors are likely to pick stocks with higher P/E in the belief that greater multiples reflect greater potential for growth. P/E is best analyzed in terms of annual range from high to low rather than as a fixed value in time. Analysts look for low volatility in the year-to-year P/E range, seeking the ideal of range between 10 and 25 consistently. These generalizations do not provide specific guidance in stock selection. For this, it makes sense to begin with an analysis of fundamental volatility over several years. Those companies whose selected fundamentals are strong and improving—and with little volatility in the fundamental trend—will also tend to be strong technical trending stocks. This is the premise for starting with fundamental analysis as a comparison point for technical trend analysis. Key Point: A short list of key fundamental indicators helps pick stocks with strong value or growth potential.

The Concept of Fundamental Volatility Most investors understand technical volatility quite well. It is the tendency for price to trend in predictable or unpredictable ways. A high-volatility stock has greater market risks than a low-volatility stock. For many, trend analysis is the study of technical volatility. However, it is also possible to estimate the likelihood of technical volatility by first determining the status of a few fundamentals and to draw conclusions about fundamental volatility—and how that level of volatility is likely to be reflected in trend predictability on the technical side. The meaning of fundamental “volatility” is similar to most forms of trend analysis. A strong fundamental trend will include growing revenues and earnings, strong dividends per share, medium-range P/E ratio, and steady or declining debt to total capitalization ratio. However, just as technical volatility becomes meaningful as it

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moves through time, fundamental volatility must be studied with a few key points in mind: 1. What matters is the trend and not just status. Is the trend reflective of improvement or decline? Are ratios improving or falling off? In the analysis of fundamental trends, spotting changes (improvement or decline) over many years is revealing, whereas a review of only the latest fiscal year’s results does not provide any information concerning the trend itself. 2. The dollar values do not always tell you everything you need to know because so many fundamental trends rely on comparative ratios as well. Once you have the numbers for a period of years, some relationships (notably revenue in relation to earnings) must be studied in terms of how net return has changed over the period and not just changes in dollar values. 3. The trend is only a starting point in a more detailed overall analysis. Fundamental trends may not reflect what is going on with a company today, so changes like mergers and acquisitions, new product announcements, and a replacement management team, are less tangible fundamental influences that might affect next year’s results but are not reflected in the historical fundamental trend. Key Point: Fundamental volatility identifies a form of risk that carries over to the technical side as well.

Dividend per Share and Increased Dividends A starting point in quantifying fundamentals is an analysis of the dividend trend. Dividend analysis involves several components and is not as simple as it seems at first glance. As one analyst states, “the harder we look at the dividends picture, the more it seems like a puzzle, with pieces that just do not fit together.”2 This refers to the complexity of how dividends affect corporate cash flow as well as investor perception of a stock’s value; some discount the value of dividends while others view them as a major determinant in stock selection. The realm of dividend policies and payments does define fundamental value, and dividend trends should be analyzed carefully as part of the selection process. There are three specific tests worth performing to quantify the fundamental trend in terms of dividends: 1. Dividends per share is the annual dollar value of dividends, usually paid quarterly. For example, a $1 per share dividend (or $100 per 100 shares owned) is likely to be paid at the rate of twenty-five cents per quarter. The analysis of dividends per share is focused on whether dividends declared and paid rises remains level or falls each year. The more times a dividend is increased, the greater the positive outcome. Companies whose dividend is raised every year for ten years or more are defined as “dividend achievers.” This designation was created by Mergent, Inc. in 2003.3

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2. The trend in payout ratio defines even further the value of dividends. The payout ratio is the percentage of reported net earnings paid in dividends. This must be limited to a maximum of 100 percent for practical reasons, but many companies pay only a small portion of earnings in dividends. A positive payout ratio is at the very least steady over many years, and it is even better if the ratio grows over time. However, stockholders expecting dividends also must acknowledge the value of retaining a portion of earnings to fund other activities whether defined as expanding into new territories and products, acquiring capital assets, retiring debt, or funding acquisitions. Payments of dividends and increases, as measured by the payout ratio, play a key role in defining the value of a company and its stock: Companies that have a long-standing history of stable dividend payouts would be negatively affected by lowering or omitting dividend distributions. These companies would be positively affected by increasing dividend payouts or making additional payouts of the same dividends. Furthermore, companies without a dividend history are generally viewed favorably when they declare new dividends.4

The payout ratio clarifies increased dividend payments each year by disclosing whether the dollar amount keeps up with earnings. For example, it is possible to discover dividend growth every year along with a decrease in the payout ratio, a signal that the company has reduced its dividends in terms of the percentage of earnings returned to shareholders. With rapid market expansion, companies are likely to rely increasingly on long-term debt, so growth in the debt to total capitalization ratio does not always mean there is a problem.5 Payout ratio and dividends paid per share are best reviewed in conjunction with the reported debt to total capitalization ratio (the portion of capitalization represented by long-term debt). If all the dividend ratios (dividend per share, dividend increases, payout ratio, dividend yield) are positive but long-term debt has also risen, is one a substitute for the other? If dividend fundamentals are positive at the expense of shifting equity into debt, it means that future earnings will have to be increasingly used for debt service, meaning there will be a diminishing level of earnings available to fund dividends. Key Point: Analysis of dividend-related trends is complete only when reviewed along with the trend in the debt to total capitalization ratio.

For example, over an eight-year period, Verizon (VZ) increased its dividends every year, which appeared positive at first glance. However, when that increase is viewed along with the negative increase in the debt to total capitalization ratio, the overall picture is quite negative. This relationship is summarized in Table 14.1.

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Table 14.1: Dividends per share and debt to total capitalization ratio, Verizon (VZ) Fiscal Year Dividend per share 2010 2011 2012 2013 2014 2015 2016 2017

1.93 1.98 2.03 2.09 2.16 2.23 2.29 2.33

Debt/cap ratio 32.4 35.7 34.6 47.4 87.1 80.9 79.8 70.3

Source: CFRA Stock Reports

When there is no actual growth in terms of revenue and earnings, but positive dividend trends are offset by negative debt to total capitalization ratio growth, the practical realities of using debt to fund growth do not apply. In the case of Verizon, revenue grew over the period, but earnings were erratic. Net return (earnings divided by revenue) grew from 2.4 percent in 2010 to 23.9 percent in 2017. To a degree, increased revenue and impressive net increase in net return could justify the increased debt to total capitalization ratio. However, the end of 2017 level of 70.3 translates to an overall increase in long-term debt. Total capitalization was funded 70.3 percent by long-term debt by 2017, meaning only 29.7 percent was derived from shareholders’ equity. Given the erratic net earnings and negative trend in the debt to total capitalization ratio, the slight increases in dividends per share might not be justified over the long term. Investors might justifiably be concerned about such imbalanced dependence on long-term debt and what that means for future cash management. In this situation, increased dividends are of minimal value and increased long-term debt reflects a negative fundamental trend. 3. Dividend yield is yet another key element of dividend fundamentals, but it may also lead to inaccurate conclusions. The reported yield at any given moment is derived by dividing the annual dividend per share by the current stock price. Consequently, dividend yield rises as the stock price falls and declines as the stock price rises. Due to this mathematical reality, an investor should calculate dividend yield based on the actual purchase price and consistently use that yield rather than the yield that changes with an evolving price level. This points out yet another problem of perception. An investor noting a sizable increase in dividend yield might be tempted to invest immediately. This is especially true if the initial stock selection criteria includes seeking higher than average dividend yield. However, the yield will increase not only due to declarations of higher dividends but also because of strongly declining stock prices.

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Before assuming dividend yield reveals the entire story, the reasons behind the higher yield should be examined. If the fundamental news about a company is negative, the investment value is negative, not positive. For example, a company on the verge of declaring bankruptcy or being investigated for filing false financial statements with regulators is likely to see a decline in price per share and a corresponding increase in dividend yield. Once an investor has purchased shares, the dividend yield is fixed to the rate applicable to the share price. This does not change even as the price per share moves, even significantly. Even so, many investors track dividend yield as closely as price per share and may even assume that as the yield grows or shrinks, it affects their yield; it does not. The basis for calculating dividend yield is the price paid per share and the dividend paid per share.

P/E Ratio A second indicator is the price/earnings (P/E) ratio. This is the multiple derived by dividing price per share by earnings per share. The result, called the multiple, represents the number of years of earnings reflected in the current price per share. The medium level between 25 and 10 is generally assumed to be reasonable for stocks. However, the true meaning of P/E is not restricted to a multiple in the moment. What is meaningful is the breadth of yearly P/E range from high to low and the consistency of that range over many years. In a fundamentally volatile trend, P/E may range broadly, spiking high in some years and settling low in others. In a low-volatility company, P/E is likely to be far more consistent over several years. Key Point: In studying P/E, two methods should be used: the annual range from high to low and the trend in that range over time.

P/E most often is used to define stocks as bargain-priced (with low P/E) or as overpriced (with high P/E). This analysis, however, is best applied between companies in the same industry, as many market factors beyond the generalized assumptions about the “right” P/E level can vary due to the dissimilar attributes of one industry compared to another.6 The reason for analyzing P/E by range and by time is that P/E in the moment is not reliable. An annual range and multiyear trend provides a strong indication of fundamental volatility. The P/E as a single indicator at any given time involves two factors with different time frames. Price changes constantly and is current; earnings are fixed as of the latest financial quarter or fiscal year (and may also be modified based on independent audit). Thus, the earnings side may be several months out of date. The ramifications of this disparity include a possibility that cyclical and seasonal changes

Revenue and Earnings 

 291

in some industries will make today’s P/E unreliable. However, by reviewing several years of range in P/E, the picture is clarified.

Revenue and Earnings The study of revenue and earnings, perhaps more than any other fundamental indicator, defines fundamental volatility. In a low-volatility company, three attributes are expected: consistently rising revenue, consistently rising profits, and level or increasing net return. The combination of all three of these features is essential to understand the health of a company’s fundamentals. When revenue and earnings are declining and even moving into the range of net losses, the trends clearly are negative. However, a hidden negative pattern may also be found. This occurs when revenues are on the rise and earnings are flat or declining. At the same time, net return is falling. This means that earnings reflect a growing decline as a percentage of revenues. For example, an eight-year analysis of McDonald’s revenue and earnings reveals growth in the top line in only three of the eight years, with earnings inconsistent in the same period. Net return increased in five of those eight years. This is summarized in Table 14.2. Table 14.2: Revenues and earnings, eight years, McDonald’s (MCD)

Year 2010 2011 2012 2013 2014 2015 2016 2017

In $ millions Revenue Earnings $24,075 27,006 27,567 28,106 27,441 25,413 24,662 22,820

$4,946 5,503 5,465 5,586 4,758 4,529 4,687 5,192

Net Return 20.5% 20.4 19.8 19.9 17.3 17.8 19.0 22.8

Source: CFRA Stock Reports

To some extent, this negative relationship between revenue and earnings reflects a market plateau for the company and does not necessarily foretell a decline in the value of the company. However, the fundamentals were reflected in the stock price. At the beginning of 2010, the stock was valued in the mid-$40s, by October 2018 value had peaked at just over $168 per share. Between 2013 and the first quarter of 2015,

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the stock had moved into a primary consolidation trend with breadth range-bound between $85 and $100 per share. This technical trend occurred even as both revenue and net profits declined. However, by the end of 2015, the stock moved into a strong bullish trend and all growth occurred from 2016 through 2018. Key Point: Rising revenues can be misleading; if the net return declines as revenues rise, the overall fundamental trend is negative.

The negative relationship expressed in the net return of earnings to revenues is only one of many factors in fundamental trend analysis. In the example above, the consolidation primary trend could represent a supply and demand pause that will be followed by a new bullish primary trend in future quarters and years. The range of net yield between a high of 20.5 percent in 2010 and 22.8 percent in 2017 represents moderate growth in percentage terms, even with significant growth in price per share. During the same period, other fundamentals for MCD were positive. Dividends per share rose each year from 2.26 in 2010 up to 4.64 in 2017 and the payout ratio moved from 49 percent to 59 percent. At the same time, debt to total capitalization ratio increased from 44.0 to 112.4. The fundamental trends were mixed. This example demonstrates the importance of reviewing the whole picture, not only a small portion of it. Given the relatively small span of net return over the five years in the context of other fundamental trends, MCD reported overall positive fundamentals except for the troubling debt to capitalization ratio, which was above 100 percent by the end of the period.

Debt to Total Capitalization Ratio Debt to total capitalization ratio compares sources of total capitalization used by an organization. Dividing long-term debt by shareholders’ equity produces a percentage, which is expressed as a numerical value (usually to one decimal place) and without percentage signs. Beyond comparing these two sources of capitalization, the value of this ratio is found in tracking it over time. When a company’s debt to total capitalization ratio remains steady or declines, it is a positive trend. However, when it increases each year, it reveals a negative trend. As a company relies more and more on long-term debt, the corresponding debt service of the future must increase. This means that future earnings will have to be dedicated more to debt service and less to funding growth or paying dividends.7

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 293

Key Point: A growing debt to total capitalization ratio points to working capital problems in the future, when higher debt service will reduce expansion and dividends for stockholders.

This is a key fundamental trend because it reveals so much about management’s policies. When dividends per share and dividend payout ratio both increase every year but are offset by ever-higher debt to total capitalization ratio, it means the company cannot afford to pay dividends from higher earnings. Instead, those positive dividend trends are offset by negative debt trends. Debt analysis often is overlooked in fundamental analysis with a greater focus on the income statement, and specifically on revenue and earnings trends. In analysis of working capital, emphasis often is placed on the current ratio, which is derived by dividing current assets by current liabilities. However, current ratio is also easily controlled, even in periods when a company is losing money. With the ideal current ratio between 1.0 and 2.0, as cash flow deteriorates, it is easy to keep the current ratio in positive territory by increasing long-term debt. Because the current ratio is concerned only with current liabilities, these growing long-term debts are not considered in this analysis. Unfortunately, the current ratio presents only part of the greater picture. For example, a comparison of current ratio and debt to total capitalization ratio for JC Penney (JCP) over eight years reveals what would appear to be a safe current ratio level. But debt to total capitalization moved from 36.7 to 70.1 by 2017, a period with falling annual revenue and earnings—with most years reporting net losses. These trends are summarized in Table 14.3. Table 14.3: Fundamental trends, JC Penney (JCP)

Year 2010 2011 2012 2013 2014 2015 2016 2017

Current ratio 2.1 2.4 1.8 1.4 1.7 2.0 1.7 1.6

Debt/cap ratio 36.7 36.2 40.3 46.6 55.7 72.2 76.5 70.1

$ millions Revenue Earnings $17,556 17,759 17,260 12,985 11,859 12,257 12,625 12,547

$

251 389 – 152 – 985 – 1,278 – 717 – 513 1

Source: CFRA Stock Reports

This summary reveals the true overall fundamental trend. It is not realistic to point to current ratio as “proof” of sound management over working capital. Given the offsetting 91 percent increase in the debt to total capitalization ratio (from 36.7 up to

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70.1) and declining revenue and earnings, the current ratio does not reflect what was taking place during this period. The analysis of several key factors such as this also shows that fundamental analysis cannot be performed on limited trends but must include all the relevant trends underway. However, for technical trend analysis, the larger question is: Do fundamental trends end up reflected in the price history of the stock? In the case of JC Penney, the answer was yes. From 2010 through 2011, the stock was trading in a primary consolidation trend, range bound between $37 and $18 per share. Between 2012 and 2014, a bearish primary trend prevailed, with stock prices declining from a high of $43 down to a low of $6 per share. This remained in consolidation through 2016, with price ending at $8 per share. By September 2018, price had dropped to under $2 per share.

Comparing Fundamental Trends to Technical Trends The ultimate test of fundamental trend analysis is how it becomes reflected on stock charts. In fact, a consistent “cause and effect” is found between the two sides. Companies with strong fundamentals tend to also demonstrate bullish stock price trends and those with weak fundamentals tend to report bearish trends. Key Point: Fundamental trends ultimately will play out in price trends, but this does not always occur immediately.

This cause and effect becomes true over time, but the actual cause and effect is distorted by marketwide trends. For example, when the market (as measured by index movement such as the DJIA or S&P 500) is moving in a direction, individual stocks tend to exhibit a similar directional bias. Equally impacting technical trends are sector-specific economics. For example, when oil prices fell rapidly in 2014 and 2015, Exxon-Mobil (XOM), the largest US oil company, saw its shared decline from $103 down to $84 per share. The effect of lower oil prices was reflected both in fundamental and technical outcomes for the company. Apart from the relatively short-term economic and marketwide impacts on a stock’s value, longer-term relationships between fundamental and technical trends are quite clear. A series of fundamental trends are the starting points for this comparison. Figure 14.1 provides a five-year summary of dividends and the revenue/earnings history for Wells Fargo (WFC).

Comparing Fundamental Trends to Technical Trends 

dividends 1.60

d i v i d e n d s p e r

1.50 1.40 1.20 40%

1.00

35% p a 30% y o 25% u t 20%

.80 .60

s h a r e

.40

15% r a 10% t i 5% o

.20 .00

0% 2010

2011

2012 2013 2014 fiscal year

2015

2016

2017

revenue and earnings 43,000 r e v e n u e i n

42,500 42,000 41,500 41,000 40,500

e a r 25,000 n i n g 20,000 s

40,000

$ 39,500 m i 39,000 l 38,500

15,000 i n

38,000

10,000 $ m i l

2010

2011

2012 2013 2014 fiscal year

Source: Prepared by author from CFRA Stock Reports Figure 14.1:  Wells Fargo—fundamentals, eight years

2015

2016

2017

 295

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On the dividends side, both dividends per share and the payout ratio grew during this period. At the same time, revenue was erratic but net earnings continued rising. This was overall a very positive result for the eight-year period. Another positive outcome was reported by Verizon (VZ), as shown in Figure 14.2. dividends d i v i d e n d s

2,40 2.20 2.00 90%

1.80

80% p a 70% y o 60% u t 50%

1.60 1.40

p 1.20 e r 1.00

40% r a 30% t i 20% o

0.80 s h 0.60 a r 0.40 e

10%

0.20 0.00

0% 2010

2011

2012

2013

2014

2015

2016

2017

fiscal year

revenue and earnings 130,000 120,000 r e 110,000 v e 100,000 n u 90,000 e 80,000 30 25 20 15 2010

2011

2012

2013 2014 fiscal year

2015

Source: Prepared by author from CFRA Stock Reports Figure 14.2: Verizon—fundamentals, eight years

2016

2017

e a r n i n g s

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 297

Dividends per share increased gradually while the payout ratio was erratic. At the same time, revenues rose consistently while earnings did not move much. This was also a positive outcome with less impressive earnings growth. On the negative side, Big Lots (BIG) reported the most troubling of fundamental trends: rising revenue with falling net earnings, as shown in Figure 14.3. Earnings finally began moving upward toward the end of the period. revenue and earnings 6,000 r e 5,500 v e 5,000 n u 4,500 e

300 275 e a 250 r n 225 i n 200 g s 175 $ 150 m i 125 l

4,000 $ m 3,500 i l 3,000

100 2010

2011

2012 2013 2014 fiscal year

2015

2016

2017

Source: Prepared by author from CFRA Stock Reports Figure 14.3: Big Lots—fundamentals, eight years

Overall, the reported dollar value of both revenue and earnings were both low in comparison to Wells Fargo and Verizon. Another negative outcome was experienced by Canon (CAJ). Dividends were paid only for part of the period. However, the decline in both revenue and earnings through 2017 told the story of the fundamental trend; it reversed to the positive side in the last two years This is shown in Figure 14.4.

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 Chapter 14: Fundamentals: Connecting the Two Sides

dividends 1.80 1.60 1.40 1.20

110%

1.00

100% p 90% a y 80% o u 70% t 60% 50% 2010

2011

2012

2013

2014

2015

2016

2017

fiscal year

revenue and earnings 45,000 r e v e n u e i n $

44,000 43,000 42,000 41,000 40,000 39,000 38,000

m 37,000 i l 36,000

32 30 28 26 24 22 20 18 16 14 12

35,000 34,000 32,000 31,000 2010

2011

2012

2013 2014 fiscal year

2015

2016

2017

e a r n i n g s $ m i l

Source: Prepared by author from CFRA Stock Reports Figure 14.4: Canon—fundamentals, eight years

Although dividends rose per share over two years and the payout ratio climbed above 80 percent, the examination of the five-year history of revenue and earnings pointed to a troubling negative trend. Both fell substantially. Concerns for potential investors

Comparing Fundamental Trends to Technical Trends 

 299

would involve not only a desire to see improvement in the income side, hoping for a turnaround and positive change, but also a revised policy involving dividends and the payout ratio. It could make greater sense for the company to use its earnings to increase market share and seek profitable expansion and to suspend these high dividend payout levels until the revenue and earnings outlook improved. Key Point: The relationship between revenues and earnings on one side, and dividend trends on the other, is complex. In some cases, it makes sense to reduce the dividend trend in favor of long-term growth and expansion.

A final examination of the fundamentals is an eight-year examination of the debt to total capitalization ratio. This is summarized in Figure 14.5. 100% 90% 80% 70% 60% 50%

Verizon

Wells Fargo

40% 30% 20% Big Lots

10% Canon 0% 2010

2011

2012

2013

2014

2015

2016

2017

Source: Prepared by author from CFRA Stock Reports Figure 14.5: Debt to total capitalization ratio

Of these four companies, only Verizon and Wells Fargo reported debt to total capitalization ratio for all five years. Both trends were negative, rising through the eight years. The analysis next compares the fundamental trends to stock charts for the same period. Wells Fargo’s five-year chart consisted on a consolidation trend for years 2010

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and 2011 and then a strong bullish primary trend from 2012 through 2015, with prices rising strongly in all three years, trending from a low of $22 per share up to a high of $55. The positive move continued slightly through to 2017. When other fundamentals are examined next to the price chart, the relationship between fundamental and technical trends is clear (see Figure 14.6).

Source: Chart courtesy of StockCharts.com Figure 14.6: Wells Fargo—eight years

The Verizon chart moved in a different manner—bullish to consolidation—as revealed in Figure 14.7.

Source: Chart courtesy of StockCharts.com Figure 14.7: Verizon—eight years

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 301

In Figure 14.7, the first three years moved in a bullish primary trend from a low of $17.50 up to a high of $42.50 per share. This reflected the steady growth in revenue levels but appeared to not react to lack of growth in earnings. However, from mid2013 through late 2018, a primary consolidation trend replaced the bullish move, with prices range-bound between $37.50 and $51. A completely different stock chart for eight years was discovered for Big Lots, which is found in Figure 14.8.

Source: Chart courtesy of StockCharts.com Figure 14.8: Big Lots—eight years

Big Lots experienced flat revenue and falling earnings results during this period. The stock chart was extremely volatile for the entire period, with prices ranging between $58 and $22 with big price swings of 10 points or more in both directions and with swings taking place over average time spans of two months. This might make Big Lots a good candidate for swing trading, given the fast movement of swing trends and lack of any permanent primary or secondary trends beyond this exceptionally volatile outcome. Does the price history reflect a reaction to the fundamental trend? To a degree it does. Revenue was flat, but earnings fell. In addition, the dollar value of earnings was so low that the fundamentals were chronically weak. Key Point: Weak fundamentals are likely to be reflected in declining price or worse, in price volatility.

The fourth company, Canon, also demonstrated how weak fundamentals translate to weak technical trends. Figure 14.9 summarizes their price history for eight years.

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Source: Chart courtesy of StockCharts.com Figure 14.9: Canon—eight years

Revenues and earnings both fell during much of this period. The decline was consistent, making the fundamental trend evident in a deteriorating set of results. This was reflected as well in a decline in stock price from over $50 per share at the start of 2011, down to prices as low as $28 at the end of 2017, followed by a 2018 rally to as high as $39. A clear correlation between fundamental and technical trends is likely to occur. Over a long-term period, such as eight years, the history of change in key fundamentals does reveal that, despite interim marketwide and economic forces, the fundamentals lead the technical levels consistently. In the next chapter, the examination of attributes making up trends are put together to shown how specific types of trend signals work collectively to forecast reversal and continuation of the technical trend. With so many sources of trend signals (price patterns, volume, gaps, moving averages, momentum oscillators, volatility, and fundamentals), how can the current technical trend be anticipated effectively? The answer is to rely on a collection of several signals of different types and to avoid confirmation bias by objectively studying the signals and drawing conclusions about what they reveal.

Comparing Fundamental Trends to Technical Trends 

Endnotes

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1 Au, Thomas. A Modern Approach to Graham and Dodd Investing. Hoboken, NJ: John Wiley & Sons, 2004, p. 28. 2 Black, Fischer. “The Dividend Puzzle.” Journal of Portfolio Management (1976)2, pp. 5–8. 3 www.mergent.com 4 Gill, Amarjit, Nahum Biger, and Rajendra Tibrewala. “Determinants of Dividend Payout Ratios: Evidence from United States.” The Open Business Journal (2010) 3, pp. 8–14. 5 Higgins, R.C. “Sustainable Growth under Inflation.” Finance Manage (1981)10, pp. 36–40. 6 Chisholm, A. M. An Introduction to International Capital Markets. West Sussex, UK: John Wiley & Sons, 2009. p. 428. 7 Gibson, Charles H. Financial Reporting and Analysis: Using Financial Accounting Information. Mason, OH: South-Western Cengage Learning, 2012, pp. 275–76.

Chapter 15 Overview: Putting It All Together The possible combinations of initial and confirming signals are vast. This chapter provides examples of several combined signals designed not only to demonstrate how dissimilar patterns and indicators work together, but also to show how trends develop, change, and reverse. To review a few of the basics of trend analysis: 1. There are three directional types of trends, bullish, bearish, and consolidation. The consolidation is most often described as a pause between other trends or as a period of indecision. These are true observations, but consolidation may last many months or even years. So as a primary trend, the consolidation pattern is a valid “directional” trend with its sideways movements and range-bound patterns. 2. Changes in trend direction may be anticipated by recognizing coming breakout signals, which include numerous types of indicators (candlesticks, price patterns, volume, moving averages, and momentum oscillators). Because a specific directional signal invariably indicates a change in the current trend, many observers believe that the end of consolidation cannot be identified because there is no trend to reverse. However, specific changes in the price behavior within consolidation do provide useable signals; these include narrowing breadth by way of wedges or triangles combined with price proximity to resistance or support. 3. Recognizing how different indicators cross-confirm improves the accuracy of trend forecasting. Understanding what something means in the moment is the key, and recognizing how different kinds of patterns (both reversal and continuation) behave together, is a more accurate method for spotting changes than reliance on single types of indicators. 4. Trends and trend patterns are all relative. When you review a two-year chart, certain patterns emerge that are not as visible as on a three-month chart. However, a small pattern on a longer-term chart has the same significance as a shorter pattern on a very limited chart period. For example, on a two-year chart, a three-month secondary trend appears only briefly, about the equivalent of a three-week or four-week secondary trend on a three-month chart. In studying the nature of trends, keeping this perspective in mind helps in ensuring that the analysis relates to the relative contrast between trend patterns and not only to actual duration. This key attribute of trends—applicability of patterns over all time periods—is a feature of the charts and examples that follow. Key Point: To track trends accurately, you need to know the types of trends, signals, and relative significance of trend shapes.

DOI 10.1515/9781547401086-015

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In this chapter, five specific types of changes to trends are examined: moves from directional to consolidation trends, volatility in secondary trends, large price moves as signals of a primary trend ending, secondary trends leading to resumption of primary trends, and failed breakouts during a consolidation trend. These represent only five trend patterns out of many possible variations. These were selected because they are patterns experienced repetitively, and because spotting the different signals adding to a coming change are evident when checking the many different types of indicators.

Moving from Downtrend to Consolidation The first of these five formation types is seen when a primary directional trend (bullish or bearish) ends with a move to consolidation. This occurs with several specific signals and involves two important points of recognition: understanding that the current primary trend is ending and then spotting a likely revision into a period of consolidation. This occurs often and is a rational pattern. Once a price evolves to the point that it exhausts a current trend, a period of uncertainty is likely to follow. Or, in the alternative, the end of a long-term trend can also lead to a period of agreement, not uncertainty. When buyers and sellers agree that a newly established range is reasonable for a stock, consolidation is the acknowledgment that the newly set range works, at least until a change in the supply and demand perception leads price into a new bullish or bearish phase. In this period, one attribute confirming consolidation is a narrowing of the breadth of trading. Key Point: A trend reversal does not always lead to movement in the opposite direction. It may also lead to a new consolidation trend.

An example of a downtrend resolving with a move into consolidation is seen in Figure 15.1. In this case, a volatile price pattern (as much as 11 points from top to bottom) was replaced with a 4-point range.

Moving from Downtrend to Consolidation 

 307

downtrend consolidation

Source: Chart courtesy of StockCharts.com Figure 15.1: Downtrend moving to consolidation

The downtrend took prices down 11 points in only two months. After a bounce to higher levels unable to move above $43 per share, price settled into a range between the previously set support of $36 and newly-set resistance of $40 per share. The consolidation trend, confirmed by the narrowing range, and as a result reduced volatility, demonstrated how consolidation replaces a fast-moving directional trend. The next move may be either bullish or bearish; to anticipate either, specific signals must appear. In consolidation, that usually means a further narrowing of breadth. Over the three months beyond the period shown, resistance held and support declined further down to approximately $33 per share. However, there were no strong signals indicating a bullish or bearish move away from consolidation. In consolidation, traders may be frustrated with the lack of strong directional movement; however, this pattern is a natural occurrence between other primary trends. No directional trend will last forever, and alternating bullish and bearish trends are difficult to track. The duration of any trend is impossible to know in advance, and past duration patterns are not reliable indicators. The advantage to consolidation is that it reassures traders that the supply and demand forces are working. It is not natural for the two sides to trade places repeatedly; it makes more sense to experience periods in which buyers or sellers are in control, alternating with periods of general agreement between the two sides (consolidation). This is confusing in the sense that the next step in evolution of price can not be known until a breakout occurs; however, this does not mean that consolidation is a lack of trend. It is a period of agreement, and the confusion is not about the range bound price level but about how long it will last and, more to the point, which direction price will move next. In the example above, the period between April 2013 and July 2014, accounted for most of the price movement, including conclusion of the downtrend and establishment of the consolidation trend. In Figure 15.2, a closer look is taken at this period,

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including explanation of how moving average crossover confirmed these primary trend movements.

head and shoulders: bearish signal as price fails to break out above resistance

resistance

resistance

bearish signal: price moves below both MAs

MA convergence forecasts coming trend reversal

Source: Chart courtesy of StockCharts.com Figure 15.2: Primary trend changes signaled with MA crossover

The combination of MA analysis and other signals tells the story of change from downtrend to consolidation. The first signal was price crossing below both MA lines in June 2013. This bearish indicator occurred as resistance was set at $43 per share. When MA lines converged from October through December, the resistance level was tested. A head and shoulders pattern then formed, confirming what the price crossover predicted: prices were likely to continue declining. Key Point: Trend direction is signaled by many different indicators, both reversal and continuation.

As the breadth of trading narrowed, resistance declined and was reset at $40 per share. At the same time, both MA lines closed ranks with price, confirming that the previous volatility was settling down. This trend, another signal of possible consolidation, was accompanied by the end of the bearish trend as support settled in around $36 and did not move lower until the end of the period charted in the previous chart.

Secondary Trend Volatility 

 309

Secondary Trend Volatility The move from one primary trend to another is likely to be signaled and confirmed by a variety of signals. By the same argument, secondary trends often provide short-term volatility within a long-term consolidation trend. Key Point: When primary trends are interrupted by secondary trends, high volatility in that period is not uncommon.

For example, in Figure 15.3 a long-term consolidation, with the price range-bound with a five-point breadth between $21 and $16 i, was tested with short-term volatility moving price as high as $25 and as low as $14, with several failed breakouts both above and below. This pattern was shown over two years on the chart in Figure 15.3.

failed breakouts resistance

support failed breakouts

Source: Chart courtesy of StockCharts.com Figure 15.3: Secondary trend volatility during primary consolidation

The narrow 5-point consolidation trend extended throughout the two years, even with repeated breakouts on both sides. All these failed, however, strengthening the consolidation trend for the long term. Taking a closer look at the three-month period between May and July 2013, the attributes of the failed breakout above resistance demonstrated how momentum and candlesticks combine to show how long consolidation held. This is found in Figure 15.4.

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identical three crows overbought

Source: Chart courtesy of StockCharts.com Figure 15.4: Bearish trend signaled by RSI

A pattern developed forecasting the failure of this breakout. As prices trended higher and eventually moved above resistance, RSI was in the overbought range for three full weeks. This is unusual; most of the time RSI remains in the middle between 70 and 30 and moves higher or lower only briefly. In this case, the overbought signal was exceptionally strong. As prices began retreating, the reaction swing was signaled by the pattern of identical three crows. This is like the three black crows but is a stronger bearish signal. Each session opens at the same price as the previous close, meaning there are no price gaps. A rare signal, identical three crows forecasts further price decline; and as the chart reveals, the initial overbought signal by RSI, followed by identical three crows, moved price away from the high and back into the range bound consolidation pattern. The consolidation was further confirmed by RSI remaining in the mid-range between 70 and 30 for the remainder of the period.

Large Price Move Ending Primary Trend 

 311

Large Price Move Ending Primary Trend Primary trends conclude in many ways. Some just fizzle out, others reverse suddenly, and some are clearly marked by a large price move. Figure 15.5 has an example of a chart with clear signals of the end of a primary trend, consisting of a 3-point drop after a consistent run-up in price, and then a fix-point drop confirming that the bullish trend was over.

Source: Chart courtesy of StockCharts.com Figure 15.5: Large price decline ending primary trend

The possibility that the drop in late July 2014 was only a secondary trend or an extended retracement was present when it first occurred. However, once the second, large price drop occurred, it was clear that a new trend was underway. In fact, price levels fell as low as the range between $7 and $8 per share that were previously seen two years earlier. Key Point: Big changes in price levels, especially with gaps and volume spikes, are often found at the end of a primary trend.

Taking a closer look at the last three months of this chart, numerous signals confirmed the conclusion of the primary trend and replacement by a very low-breadth consolidation period. This is shown in Figure 15.6.

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 Chapter 15: Overview: Putting It All Together

trading range under one point

gap

volume spikes

bearish crossover

Source: Chart courtesy of StockCharts.com Figure 15.6: Sudden breadth shift confirmed by MACD and volume

The initial contrast from beginning to end of this period was seen in the low volume during October, offset by the volume spikes in November and then a quick return to low volume. This pattern was mirrored in price breadth: it was under 1 point throughout October and returned to this small breadth once the large price drop has taken place. When large price moves—especially with big gaps and volume spikes—occur, it often is accompanied by highly volatile breadth of trading and volume, forecasting even more volatility to follow. In this case, however, the comparison of price breadth and volume, interrupted by the volume spikes and price gap, set up the consolidation and confirmed that the primary bullish trend was done. The change from uptrend to consolidation was further confirmed by the change in momentum, as measured by MACD. The signal line showed little activity, but the large price gap and volume spike were anticipated by the bearish crossover that began immediately before these clear signals. However, after the crossover, both MACD MA lines remained below the signal line, and that line returned to its very narrow range, also mirroring the volume and price levels.

 313

Primary Trend with Secondary Trend 

Primary Trend with Secondary Trend Contrasting the change from primary trend to consolidation, the opposite pattern presents a problem in interpretation. When a primary trend suddenly undergoes a huge price gap in a direction opposite the trend, does it mean the trend is over? In the previous example, volume and momentum confirmed the likelihood that the primary trend was done. However, a similar pattern can also be found when a primary trend is only interrupted by a secondary trend with a likely return to the primary trend. For this, a set of clear signals must forecast this price pattern rather than signaling the end of the primary trend. The chart in Figure 15.7 provides an example of the interruption of a primary trend by a secondary trend lasting less than two months.

ima

h pr

ish

ll bu

i

pr

nd

re

yt

r ma

bullis

es

sum

d re

en ry tr

bearish secondary trend

Source: Chart courtesy of StockCharts.com Figure 15.7: Primary trend with secondary trend

How do you know this is a secondary trend rather than a new consolidation or downtrend? Looking at the entire two years, the pattern is easy to read in hindsight. However, at the point immediately after the 12-point drop in price, how could this be interpreted? Key Point: Changes in primary trends may lead to reversal or consolidation. Knowing which is likely requires thorough chart analysis.

The answer is found in the next chart (see Figure 15.8), which focused on four months from November 2013 through February 2014. This chart provides the clues forecasting a return to the primary trend rather than establishment of a new trend.

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gap and volume spikes

oversold

declines and remains low

Source: Chart courtesy of StockCharts.com Figure 15.8: Signals of secondary trend start and finish

The initial price gap accompanied by volume spikes looked very much like the end of a trend. In addition, preceding narrow trading breadth was followed by a similar narrowing in February. The on balance volume (OBV) also tracked the price decline with a drop in index level, which then tracked low volume and low-breadth price. However, when RSI was also reviewed, the forecast strongly indicated a return to higher price levels. RSI moved into oversold at the point of the big gap at mid-January. It remained in oversold territory for one month and did not return to mid-range until early February. It is unusual for RSI to remain outside of the 30–70 range for more than a few days. This revealed a low likelihood of either a new downtrend or consolidation. Looking back at the previous two-year chart, the new primary trend did resume, but not until late May. In the period of two months right after the large price gap, the eventual return to the primary bullish trend was not clear in looking at price and volume alone.

Consolidation Primary Trend with Failed Breakouts 

 315

However, the oversold condition of RSI revealed that price was likely to recover and begin moving upward once again.

Consolidation Primary Trend with Failed Breakouts The price patterns and secondary trends within a long-term primary consolidation trend can be confusing. The temptation is to assign great value to strong but shortterm price movements when, in review of a longer time span, some types of movements take on a character other than specific trends. These interim movements in price may represent failed breakouts from the range-bound trend and not new trends in their own right. For example, Figure 15.9 contains a series of strong price movements ranging from $10 down to $5 over a period of two years. The appearance of this chart is one of high volatility; however, when analyzed for the repetitive nature of price movement, a different picture emerges.

resistance

support

Source: Chart courtesy of StockCharts.com Figure 15.9: Series of failed breakouts from consolidation

In fact, as indicated on the chart, this two-year price history was a primary consolidation trend with a narrow range from just below $7 to just below $8.50. This 1.5-point range was extremely limited. The frequent moves above and below that range shared certain characteristics. First, they lasted between one and three months. These may be called secondary trends given their duration or they may be classified as failed breakouts. A second feature seen in each case was the gapping price action setting up the breakout and then marking a return into range. This means that all four instances (one above resistance and three below support) formed as island clusters (see Chapter 10). Third, the extent of these breakouts was never greater than 1.5 points away from

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the consolidation range. Fourth, and most notably, was the consistent and repetitive nature of these breakouts. Key Point: A signal that a primary consolidation trend will continue may consist of a series of breakout attempts and failed breakouts.

Each island cluster was characterized further by clear reversal signals and confirming secondary signals. These are not evident on the two-year chart with compressed trading and set up as a line chart. However, an analysis of a portion of this chart— between January and June 2014—is revealing in the identification of a reversal, confirmation, and continuation signals. These are shown in Figure 15.10.

identical three crows

breakout period

support

bullish side-by-side white lines (continuation)

bullish doji star

volume spike

Source: Chart courtesy of StockCharts.com Figure 15.10: Failed breakouts returning to consolidation

The breakout period from the beginning of the charted period through mid-April began with a bearish reversal signal the identical three crows. This was a stronger bearish signal than the more common three black crows and was quite rare. Its feature included three consecutive declining sessions with each opening price identical to the preceding closing price. The same pattern was highlighted earlier in Figure 15.4 (bearish trend signaled by RSI). This downward move was strong, notably as it occurred at the point of breakout below support. If confirmed, it could mark the beginning of a new bearish trend away from the primary consolidation trend. However, price settled at the $5.25 price level.

Conclusion 

 317

A bullish doji star forecast a bullish reversal three weeks before price began trending upward once more. The point of reversal contained strongly gapping price action accompanied by a large volume spike. The return into range was further confirmed with a continuation signal, the bullish side by side white lines. Price levels quickly returned to previously established support levels and the consolidation resumed. Although the island cluster in this case lasted more than two months, it was part of a repetitive pattern that was clearly found on the previous longer-term price chart.

Conclusion The study of trends relies on signals and confirmation. These may be found in some degree of regularity and with some level of consistency. It is rare to find a trend lacking in some form of signal. The occurrence of false signals and failed confirmation usually contains its own set of attributes: 1. Reversal occurs after a weak or short-term trend. When a trend is minimal— meaning it has a very slight degree of change—and when it is short term, lasting a matter of days rather than weeks or months, a reversal is also minimal. A true trend should contain specific and easily identified price movement. This is in one of three directions: upward, downward, or sideways. The longer the trend, the more important an initial reversal signal. 2. The reversal signal is weak. After a weak or short-duration trend, the reversal signal is likely to be weak as well. This means that rather than strong breadth of trading and specific offsetting directions between multiple sessions within the signal, the sessions meet the criteria, but only to a minimum degree. A weak reversal should be viewed with caution; it is the attribute of likely failure. 3. Confirmation is also weak. Be aware of confirmation bias. A weak reversal may be confirmed, but by an equally weak confirming signal. The analyst’s desire to confirm may lead to acceptance of weak reversals and confirmation signals, but in combination they point to a higher likelihood of failure. 4. The resulting price pattern is either indecisive or it acts contrary to the signals. The failure of a weak reversal and confirmation leads to failure of the price pattern itself. The price will display indecision or will completely ignore those weak signals. In hindsight, the weaknesses are easily spotted, but in the moment, impatience or assumption may easily mislead an investor into seeing the end of a trend when the momentary price movement lacks significance, represents a secondary or swing trend, or is only a retracement of a few sessions. 5. Proximity is not ideal. The most likely placement of a reversal signal is at proximity to resistance or support, or moving through those levels. If the move also involves strong price gaps and volume spikes, reversal is close to certain. When reversal signals appear at mid-range, the reversal is less likely and the price movement

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may represent normal trading within the established range. This is frustrating for investors wanting to see a reversal from a bullish or bearish trend, or a breakout from consolidation. However, every trend varies in duration and it makes sense to act only when the signals are strong. Trend analysis involves numerous signals and patterns. Analysis is improved when you can adopt an objective view and when the trend itself is acknowledged as likely to continue until a change is identified. This is one of the principles in the Dow theory: trends continue until specific signals show that they have ended (Chapter 1). Even so, in the haze of current price movement, this rule is easily overlooked. A starting point for all trend analysis is to recognize the uncertain nature of trends and to adopt the view that within a trend, price movement is likely to be erratic with offsetting secondary and swing trends and that what appears as a reversal or breakout could be misleading and uncertain. Key Point: Trends do not end without reason. They continue until signals appear revealing a likely conclusion; these are predictable and recognizable in trend patterns and changes.

Even with this uncertainty, however, investors can devise a set of policies to use signals and confirmation to recognize the attributes of a trend as it slows down or reverses. The rich body of potential signals in the form of price patterns, candlesticks, moving averages, momentum, volume, and volatility add up to an arsenal of analytical tools that define the skills of the chartist and that inevitably improve the timing of buy-and-hold decisions as well as the faster-moving swing trade. It all relies of how effectively you apply the skills of many signals making up the science of trend analysis.

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Index A Abandoned baby signal 127, 173, 262 Accumulation/distribution 213–14 A/D index 2 14–15 A/D line  53–55, 219 Adjusted A/D  219–20 Agreement 184, 187, 199, 202, 306–7 Analysts  7–8, 34, 48, 94, 179–80, 183–84, 187–88, 191, 237 Ascending channels 58–59 Assumptions 1–4, 15–16, 18, 20–22, 27, 35–39, 47–48, 50, 280 –– random 18, 35 ATR (average true range) 279–81 Attributes 25, 74, 76, 150, 163–65, 171, 257, 306, 317–18 Average reversal indicators 130 Average true range. See ATR Averages –– moving 28–30, 34–35, 37–38, 73–74, 94, 240–44, 248, 254, 266 –– second 10, 12, 15 B Baby, abandoned 96, 126–27, 169, 173, 235, 238 Band width 196, 198 Bands 29, 33, 84, 197, 199, 244–45 –– lower 29–34, 43, 84, 93–94, 197–99, 244–45 Bargain-priced stock approaches 131 Basis 4, 15, 39, 50, 69, 133, 290 BB. See Bollinger Bands Bearish 67, 98–100, 113–14, 120–22, 126–29, 156–58, 195–96, 248–52, 275–76 Bearish breakout 198 Bearish confirmation 175 Bearish crossover 243, 250, 312 Bearish direction 82, 282 Bearish divergence 54, 214–15, 220–21 Bearish harami 118–19, 217, 231, 265, 268 Bearish harami cross 118, 265 Bearish meeting lines 121–22 Bearish movements 97–98, 265 Bearish piercing lines 120–21 Bearish price movement 193 Bearish reversal 93, 118, 126, 138–39, 146, 155, 175, 195, 221 DOI 10.1515/9781547401086-017

–– legitimate 64 –– rising wedge signals 274 –– signaled 176 –– strong 104 Bearish reversal signal 32, 316 Bearish side-by-side lines 159, 195 Bearish signal 93, 100, 119, 126, 128, 138, 248, 250, 308 –– black 159 –– confirming 62 –– initial 250 –– strong 231 –– stronger 310, 316 Bearish thrusting lines 155 Bearish trend 41, 64–65, 67, 191, 193, 307–8, 310, 316, 318 –– new 198, 316 –– new primary 11 –– new secondary 265 –– possible 171 –– primary 66, 139, 272, 278 –– secondary 231, 267 Bearish version 6, 117, 119–20, 159, 226, 237–38 Beta, stock’s 54, 72 Big Lots 297, 299, 301 Black crows 96, 122–25, 172, 195, 238, 268, 310, 316 Black session 117–21, 126, 155, 157, 159, 225–26, 231 –– consecutive 124–25 Blind spots 51, 180, 184, 218 Bollinger Bands (BB) 29–35, 43, 51, 84, 93–94, 96–97, 196–99, 244–45, 273–74 Bollinger Bands aid in interpreting price trends 31 Bollinger Squeeze 183, 196–99 Bottom 31–32, 56–57, 95, 104–6, 108–12, 118–20, 135–37, 141–43, 245 –– rectangle 107, 144–45 Bottom formations, double 146–47 Bouncing price 60–61 Breadth 22, 37–38, 113, 176, 186–87, 194–95, 236, 273–75, 277–78 –– 10-point 58 –– current 53, 71, 187, 253, 272 –– fifty-two-week 272

324 

 Index

Breadth of trading 29–30, 53–55, 57–59, 89, 91–92, 96, 103, 272–76, 278–80 Breadth test 272–73 Breakaway 103, 232, 236–39 Breakaway gaps 103, 232, 238 Breakout 45–46, 69–71, 97–100, 169–71, 183–89, 191–99, 203–8, 220–23, 232–36 –– following 207, 258 –– forecasting 187 –– potential 212, 260 –– short-term 60 –– strong 155, 186 –– true 97, 194, 199 Breakout gaps 190 Breakout period 197, 316 Breakout price movement 205 Breakout reversal and continuation 197 Breakout signals 191, 237 –– recognizing coming 305 –– strong 196 Breakouts and reversals 46 Bubble effect 15–16 Bull markets 6, 8, 10, 16, 41, 165 Bull trend 99, 136, 149, 161 –– long-term primary 121, 128, 149, 274 Bullish 67–68, 82–83, 97–99, 113–14, 120–23, 126–28, 169–71, 248–49, 263–65 –– side-by-side 157 Bullish breakout 171, 197, 251 –– strong 252 Bullish confirmation 173, 175 Bullish continuation 156, 221, 238, 274 Bullish continuation signal 151, 187 –– strong 169 Bullish crossover 249–51, 264–65 Bullish divergence 54, 214–15, 220–21 Bullish doji star 268, 316 Bullish engulfing 117–18, 128–29, 173, 192, 246 Bullish engulfing signals 192 Bullish gap 160–61, 226 Bullish harami 118–19, 170–72, 262, 265, 267 Bullish indicator 45, 142 Bullish morning star reversal signal 197 Bullish piercing lines 120, 210 Bullish price movement 64, 279 Bullish reversal 46, 93, 99, 138, 155, 173, 175, 210, 217 –– expected 109 –– signaling 110 –– strong 104, 169, 197

Bullish reversal candlestick 198 Bullish reversal signal 93, 274 –– strong 122 Bullish reversals start 136 Bullish side-by-side 197, 265, 316 Bullish side-by-side continuation signal 264 Bullish side-by-side lines 158, 264 Bullish sign 226 Bullish signal 31, 119, 128, 138, 144, 228, 250–51, 260–61 –– strong 192, 210 –– weak 172 –– white side-by-side lines 174 Bullish signal results 248 Bullish tasuki gap continuation signal 265 Bullish tasuki gap signal 173 Bullish thrusting lines 155–56, 192, 194, 210, 261 Bullish thrusting lines continuation signal 210 Bullish trend 30, 41, 62, 64, 76–77, 141, 197–98, 209–10, 265 –– established 62 –– established primary 249 –– initial 86 –– long-term 9, 18, 101, 208 –– long-term primary 9, 207, 215, 218 –– major 10 –– new 101–2, 228 –– new primary 110 –– secondary 261 –– strong 94, 107, 171, 292 Bullish trend direction 247 Bullish trend gaps 141 Bullish version 116–19, 121, 126, 155–56, 237–38 Buyers 8, 16, 54, 56–57, 97, 99, 104, 183–84, 186 Buyers and sellers 18–19, 57–58, 184, 186–87, 193, 199, 257, 261, 271 C Calculations 20, 28, 212, 215, 218, 241, 266, 272–73 Candlestick analysis 98, 112, 122, 155, 227 Candlestick reversal signal 216 Candlestick signals 56, 73, 112, 122, 137–38, 158, 217, 238 –– strong 34, 239 –– three-session 240

Index  Candlesticks 112, 115, 129, 151–53, 254, 262, 269, 305, 309 –– black 95, 112, 125, 127–28, 158 –– long 112–14, 124, 135, 152–53, 171 Canon 297–99, 301–2 Capitalization, total 177, 208, 289, 292–93 Capitalization ratio, debt to total 177, 208, 285, 288–89, 292–93, 299 CBOE (Chicago Boards Option Exchange) 282 CFRA stock reports 289, 291, 293, 295–99 Chaikin money flow 218–19 Chaikin oscillator 219–22 Channel 57, 89–92, 94, 174 –– falling 90–91 –– lower 90–91 Channel line types 89, 91 Channel lines 71, 73–76, 78, 80, 82, 84, 88–92, 96, 131 Chart 74–83, 151–55, 188–98, 201–8, 210–14, 229–36, 239–44, 251–54, 260–66 –– longer-term 130, 174, 305 –– previous 174, 192, 216, 234, 308 Chart analysis 155, 174, 239, 313 Chart courtesy 61–70, 76–83, 119–29, 139–50, 156–61, 190–97, 249–54, 274–79, 307–16 Chart gaps 80 Charted period 65, 103, 126, 145, 154, 160, 220, 264, 316 Chartists 20, 25, 29, 84, 134, 141, 164, 318 Chicago Boards Option Exchange (CBOE) 282 Clear reversal signals 45, 90, 316 Close proximity 108, 110, 168, 175, 192, 223, 226, 232 Closing prices 27–28, 112–15, 123–25, 128, 215, 218, 241, 266, 273 –– days of 263 CMF (Chaikin money flow) 218–19 Coincidental price patterns 141, 179 Coming price trends 199 Coming trend reversal 308 Commitment 179–80 Common gaps 102–3, 228–30, 236, 277 Companies 4–6, 17–20, 40–41, 47–49, 75, 164, 167–68, 285–88, 290–94 –– low-volatility 290–91 –– traded 4 Comparing Fundamental Trends 294–95, 297, 299, 301, 303 Confidence 20–22, 90, 97, 131, 137–38, 168, 235, 237, 244

 325

Confidence level 17, 21, 201 Confirmation 6–13, 74–76, 137–40, 163–64, 166–71, 173–75, 177–80, 215–18, 241–44 –– clear 68, 180 –– independent 212, 223–24 –– initial 159, 198 –– multiple 163, 195 –– strong 55, 57, 95, 164, 170–72, 174, 197, 199, 226 –– weak 169, 171–72, 176 Confirmation bias 74, 178–81, 201, 280, 302, 317 Confirmation signals 134, 163–64, 166, 168, 170–72, 174, 176, 178, 180 –– distinct 176 –– lagging 254 –– secondary 174 –– strong 171 –– useful 245 Confirmation trends 202–3 Confirming signals 114–15, 180, 198–99, 201, 217, 221, 243, 251, 257 Connecting 285–86, 288, 290, 292, 294, 296, 298, 300, 302 Consolidation 85–86, 97–99, 135–36, 143–44, 173–74, 183–99, 271, 305–7, 312–18 –– downtrend to 306–8 –– higher price 229 –– long 86, 99, 309 –– long period of 99, 146 –– long-term 234, 262, 309 –– period of 17, 96–97, 100, 172, 180, 184–85, 188–89, 191, 208 Consolidation breakout 198 Consolidation pattern 157–58, 183–84, 186, 188, 190, 192, 194, 196, 198 –– extended 85, 229 Consolidation plateaus 193, 195 Consolidation primary trend 315 Consolidation range 191, 232, 263, 268, 316 Consolidation reading 185 Consolidation resistance, prior 229 Consolidation trend 183–89, 191, 193, 195–96, 228–29, 262–63, 271, 276–77, 306–7 Continuation 66–68, 135–48, 150–57, 159, 161, 175–78, 183, 189–92, 264–65 –– long-legged doji signals 153 –– marked 190 –– strong 53, 209 –– trend’s 81

326 

 Index

–– white bullish side-by-side lines forecast 158 Continuation and consolidation 136, 183, 187 Continuation candlestick signal 226 Continuation confirmation 171 Continuation patterns 135–38, 140, 142, 144, 146, 148–50, 154–58, 160–62, 189 Continuation signal –– filled 176 –– reliable 155 Continuation signal types 135 Continuation signaling 151, 245 Continuation signals 56–57, 135–38, 140–41, 149–55, 176, 178, 183, 225–26, 316–17 Continuation signals forecast 135 Contrarians 2–4, 49, 75, 165–66, 224 Convergence 246–47, 251 Corrections 2, 14, 44, 46, 184, 233 Cost 18, 40, 133, 237 Crosses 56, 93, 118–19, 241–44, 250, 264 Crossover 243–44, 247–49, 252, 263, 265, 308, 312 Crows 125, 172, 310, 316 Current ratio 293–94 Cyclical secondary trends 173 D Data set 36, 38, 43 Days 1–3, 14, 28–29, 93–95, 118, 122, 124, 160, 237–38 –– long 46, 112, 208 –– previous 120, 124–25, 128, 155–56, 159, 223, 237 –– second 122, 231, 237–38 Debt 18, 177, 208, 285, 288–89, 292–93, 299 Debt service 288, 292 Decision tree 48 Declining 53, 55, 148, 151, 156, 208, 211, 213, 291 Declining resistance 84, 93, 146, 211 –– marked 93 Declining stocks 53–54 Demand 1–2, 16–19, 55–57, 62, 71, 163, 184, 201–2, 258 Descending triangle 66–67, 111, 188–89, 212, 274–76 Deviations 26, 28 Diamond 110–11, 147 Dilemma, prisoner’s 49, 51 Direction 1, 7–9, 41–43, 55, 59–62, 82–85, 114–15, 141, 186–87

–– new 95–96, 137, 145, 248, 258 –– opposite 48–49, 87, 90, 92, 108, 238, 242, 258, 263 –– reversed 125 –– trend’s 96, 150 Direction price 60, 186, 194, 307 Directional signals 226, 275, 305 –– clear 194 Directional trend 305, 307 –– fast-moving 307 –– primary 306 Divergence 54, 130–31, 175–76, 180, 201, 212–15, 220–22, 246–47, 263 –– moving average convergence 259, 263–65 Divergence Analysis 175 Divergence signals 131, 177, 221–22 Diversification 21, 39, 136 Dividend analysis 287 Dividend fundamentals 288–89 Dividend trends 287, 299 –– positive 289, 293 Dividends 18, 20, 37, 130, 133, 177, 237, 285–90, 292–99 –– value of 287–88 DJIA (Dow Jones Industrial Average) 5, 7–11, 15, 17, 95, 97, 134, 294 DJIA trend reversal 12 Doji 95, 114, 118–19, 126–27, 173, 226, 237 Doji star 95, 119–20, 195, 235, 237 Dollar values 22, 287, 301 Double bottom 31–32, 45, 47, 65, 73, 108–10, 145–47, 169, 210 Double bottom signals 60, 267 Double continuation signal 150 Double crossover 250–52 Double tops 32–33, 92, 97, 105, 107–10, 137, 142, 145–46, 245 –– third 146 Double tops and bottoms 39, 56, 108, 110, 135, 245 Dow 1–2, 4, 6, 8–10, 12, 14, 16, 18, 20 Dow theory 4–9, 12, 74, 318 Dow theory applied 9, 11 Downside breakout 187, 193 Downside gap 30, 119, 125–26, 157–59, 176, 190, 211, 226 Downtrend 91–93, 118–19, 122–25, 136, 175–76, 183–87, 189–93, 249–53, 306–8 –– coming 221 –– current 66

Index  –– forecast 176 –– initial 189 –– lacking 124 –– new 119, 195–96, 211–12, 314 –– prior 159 –– secondary 184 –– sharp 128 –– short-lived 145 –– short-term 122 –– strong 106, 122, 155, 176, 250 Downtrend climax 208–10 Downtrend line 77 Downtrend movement 184 Downward gap 117, 121, 142, 155, 157, 225, 228, 237–38, 243 Duration 1–2, 12–13, 36–38, 53, 58–59, 63–64, 89–90, 189–91, 257–62 –– long 131, 186 Dynamic trend 71, 89, 97, 99, 184–87, 189, 193, 229 –– previous 186, 263 E Earnings 2–4, 36, 40–41, 47, 130–31, 187, 224, 285–99, 301–2 Earnings surprises 2, 7, 12–14, 19–20, 33, 224, 240 –– reaction to 3, 14 Earnings trends 34, 130, 186, 293 Eastern continuation signals 151, 153, 155, 157, 159, 161 Eastern patterns 112–13, 115, 117, 119, 121, 123, 125, 127, 129 Efficient market hypothesis. See EMH EMA (exponential moving average) 93, 219–20, 241, 260 EMA lines 263–64 EMA signals 263–64 EMH (efficient market hypothesis) 1–2, 4, 6–8, 10, 12–18, 20, 22, 39 EMH, primary trend confirmation challenges 15 Emotions 50, 164–66, 181 Engulfing pattern 95, 117–18, 237 Equities 18, 38–39, 285, 289, 292 Equity positions 37–38, 132, 161 Evening star 96, 125–27, 235 Exceptions 83–84, 151, 239–40, 260–61 Ex-dividend date 237 Ex-dividend gaps 236–37 Exhaustion gaps 104, 228, 234–35, 238–39, 252

 327

F Factors 2, 18, 22, 56, 165, 168, 186, 290, 292 Failed breakouts 102, 107, 109, 171, 204, 206, 258, 309, 315–16 Falling price trends 60 Falling resistance lines 67 Fat tails 26–29, 51 Fibonacci retracement 87–89 Fibonacci sequence 87–89 Final bearish confirmation 159 Financial information 4 Flags 73, 85–87, 135, 137, 148–50, 174, 183, 196 Flags and pennants 85–86, 135, 148, 150 Forecast 60–61, 84–85, 98–99, 117–18, 129–30, 135–36, 192, 218, 271 Formations, diamond 95, 110–11, 147 Fundamental analysis 19–22, 75, 177, 285–86, 293–94 Fundamental analysis and confirmation 177 Fundamental trend analysis 47, 287, 292, 294 Fundamental trends 47, 75, 177–78, 282, 286–87, 292–94, 297, 299, 301–2 Fundamental volatility 23, 75, 177, 282, 286–87, 290–91 Fundamentals 15–16, 18–20, 46–47, 75, 163–64, 177, 285–86, 290–92, 294–302 –– strong 285, 294 –– weak 208, 294, 301 G Game theory 47–50 Gap patterns 208–9, 211, 222, 237 Gap proximity 238–39 Gap risk 239–40 Gapping continuation signal 197 Gapping price pattern 159, 231 Gaps 102–4, 140–42, 159–61, 189–90, 210–12, 222–30, 232–40, 245, 276–77 –– bearish harami 237 –– big 312, 314 –– bullish harami 237 –– downward moving price 142 –– downward-moving 99, 105, 237 –– initial 79, 170 –– initial price 314 –– large 218, 223–24, 226, 228 –– large one-session 268 –– large price 34, 39, 77, 197, 312, 314 –– repetitive price 78, 252 –– strong 141, 150, 235–36

328 

 Index

–– strong downward price 154 –– strong price 103, 317 –– tasuki 135, 159–60, 225, 265 –– unfilled 226 –– upward price 262 –– volume spikes and price 211, 312 Gaps filled 160, 225 Goldman Sachs 5, 167, 181 Gravestone 114–15 Growing price trend 186 Growth 33, 59, 164, 285–86, 288–89, 291–92, 301 Growth stocks 2, 286

Interpreting price trends 31 Inter-session gaps 239 Inverse head and shoulders 45, 95, 101–2, 135, 140 Investors 4–7, 15–16, 19–21, 43–46, 48–51, 136–38, 163–68, 178–80, 289–90 Investors and traders 5, 16, 137, 165 Investors tracking prices on charts 96 Island cluster 235–36, 277, 315–17

H Hammer 95, 115–16, 173, 235, 261 –– inverted 95, 116–17 Harami 95, 118–19, 237 Harami cross 95, 118–19, 174–75, 237 Head and shoulders 92, 95, 100–101, 104–5, 135, 137, 139–40, 308 Head and shoulders and confirmation 139–40 Health, trend’s 273 HFTs (high frequency traders) 202 Hidden gaps 225, 230–31, 237 High frequency traders (HFTs) 202 High prices 59–60, 69, 127, 215, 272 History 9, 16, 35, 51, 302 Hypothesis, efficient market 7, 12–13, 39

K Knowledgeable investors 6–7

I Increased Dividends 287, 289 Index 4–5, 9, 11–12, 15, 42–43, 215–16, 218, 259–60, 280–82 –– relative strength 42, 215, 259, 261–62 Index movement 97, 215, 294 Index value 5, 15, 23, 42, 215, 259–60, 263 Indicated reversal direction 215 Indicators 28–29, 92–94, 123, 137–38, 201–2, 218–19, 221–22, 243–44, 305–6 –– candlestick 112, 114, 131, 225 –– fundamental 36, 177, 224, 285–86, 291 –– leading 202–3, 217–18, 261, 266 –– price-based range 40 Individual investors 167, 180 Industrials 8–10 Initial reversal signals 128, 251, 317 Initial signal 39, 178, 231, 250 Insurance 21, 133 Interest 4, 8, 29, 37, 40, 55, 76, 167, 184

J JC Penney (JCP) 293–94 Journal 23, 94, 162, 181, 254–55, 283, 303

L Lagging indicators 217, 242, 250–51, 254, 257, 261 Large price move ending primary trend 311 Large volume spikes 204, 317 Lasting bullish trend 207 Lines 53–55, 76, 83–84, 241–44, 246–54, 259, 265–67, 308, 312 –– horizontal 112, 114 –– meeting 96, 120–22, 157 –– piercing 96, 120–21, 155, 267 –– straight 76, 84, 186 –– thrusting 135, 155–56, 192 –– white 157, 197–98, 264–65, 316–17 Lines signals 96 Long-legged doji 98, 114–15, 135, 153–54, 176 Long-term debt 71, 177, 208, 288–89, 292 Long-term primary trend 38, 58, 79, 123, 125, 129, 131, 208 Long-term trends 16, 22, 29, 34, 68, 70, 75, 174, 177 Losses 19, 21–22, 48, 50, 54, 133, 165, 167, 179–80 Low prices 57, 59, 61, 64, 79, 83, 215, 218, 266 Low prices mark resistance 59 Low volume 184, 207–9, 258, 312 M MACD (moving average convergence divergence) 259, 263–65, 268, 312 MACD lines 264–65 Magical thinking and trends 50–51 Managers 132, 179

Index  Market behavior 2–3, 15, 97, 166 Market breakouts 46 Market conditions 54, 179 Market culture 50 Market prices react 12 Market risks 21, 29, 177, 271, 285–86 Market sentiment 41 Market share 18, 165, 286, 299 Market trends 6 –– broader 54 Market value 285–86 Market volatility 282–83 Markets 1–2, 4–9, 12–19, 35–36, 46–50, 53–55, 75, 163–66, 177–79 –– broader 53–54, 97 –– efficient 12–13 –– sub-prime 167 Marking risk 271–72, 274, 276, 278, 280, 282 MCD 291–92 Measurement 41, 53, 257–58 Meeting lines signal 121 MFI (money flow index) 215–17 MFM (money flow multiplier) 219 MFR (money flow ratio) 215 Middle band 29–33, 43, 94, 244 Mid-range 40, 42, 222, 258–59, 280, 310, 314, 317 Misplaced reversal signal 138 Momentum 13, 41–43, 55–56, 99, 130–32, 172–75, 246, 257–61, 263 –– price-related 215 Momentum and timing of preceding Trends 172–73 Momentum changes 13, 15 Momentum indicators 78, 280 Momentum of reversal 99 Momentum oscillators 34–35, 42–43, 73–74, 174–75, 241–42, 257–60, 262, 264, 266 Momentum shift 248 Momentum signals 60, 104, 114 –– critical 263 Momentum trading 41 Momentum trends 268 Money flow index 215–17 Money flow ratio (MFR) 215 Month-long downtrend, strong 123 Morning and evening stars 96, 125–26 Morning star 125–26, 197–98, 235, 237 Movement 5–8, 17, 30–31, 33–34, 40–42, 163–64, 172–74, 185–86, 257–59

 329

–– clear trend 10, 61 Moving average convergence divergence. See MACD Moving average trading rules in South Asian stock markets 254 N Narrow range 78–79, 86, 149, 177, 184, 198, 263, 312, 315 Narrowing breadth 34, 111, 187, 195–96, 273, 275–76, 305 Neckline 100–102, 110, 137, 139–40 Negative trend 289, 292 Net return 20, 287, 289, 291–92 News 3, 7, 16, 18, 20, 224, 258, 260 Non-signal 138, 172 Normal distribution 26, 28–29, 38 O OBV (On balance volume) 212–14, 314 Offset 60, 133, 166, 237, 289, 293, 312 Offsetting bullish reversal 217 Oil prices 278, 294 Online charting services 93, 216, 241 Opening 42, 112–14, 128, 159, 218 Opening price 112, 115, 123, 125, 223, 230, 237, 316 Oscillator 41, 220, 257–60, 266–68 Outcomes 26–29, 35, 37–38, 43–44, 48, 50, 137, 164, 166 Overbought 6, 21, 23, 41–43, 92, 215, 217–18, 257–63, 266–68 Overbought conditions 130, 215, 218, 257, 263, 266 Overbought signals 218, 267, 310 Overconfidence 165–68 Overreaction 2–3, 13–14, 17, 37, 41, 165, 224, 260 Oversold 23, 104, 130, 215–16, 257, 259–62, 266–68, 314 Oversold conditions 21, 35, 92, 215–16, 218, 266, 315 Oversold range 42, 217, 258–59 P, Q Past price behavior 39 Past price performance 20, 242 Payout ratio 20, 47, 285, 288, 292, 296–99 P/E ratio 41, 44, 71, 130, 177, 186–87, 285, 290 Peaks 211, 213, 280–81 Pennants 73, 85–87, 135, 137, 148–50, 183, 196

330 

 Index

Piercing lines reversal signal 155 Piercing lines signal 210 Plateau 25, 58, 183, 193–95, 263 Portfolio 19, 21–22, 38, 54, 132–33, 136, 177, 179 Portfolio managers 20–22, 37–39, 44, 47, 167, 178, 180 Portfolios, permanent 37, 45, 131–32, 178, 180 Positions 3, 21, 37–38, 41–42, 47, 94, 179, 184, 253 Possible outcomes 20, 27, 35, 49, 222 Potential reversal signals 244 Power spike 44–45 Preceding trends 172–73 Price –– average 28, 198 –– combined 203, 210 –– current 14, 17, 56, 177, 184, 248, 252, 286, 290 –– current stock 18, 289 –– final 143, 266 –– growing stock 48 –– higher 35, 115 –– individual stock 16 –– large 111, 230, 306, 311–12 –– lower 35, 205 –– momentary 33 –– moved 32, 94, 108, 154, 205, 227, 252, 310 –– moving 123, 141, 186, 194, 223, 236, 252, 309 –– opening and closing 113–14, 128, 218 –– right 17, 184 –– rising 123, 203, 208, 212 –– settlement 266 –– spiking 104–5 –– stock’s 19, 37, 57, 81, 127, 224 –– tracking stock 5, 28 Price action 1, 3, 62, 175, 224, 228, 236, 271 –– gapping 223, 225, 317 Price activity 56, 97, 191 Price and volume 23, 44, 131, 202–3, 205, 214, 216, 219, 314 Price averages 29, 242 Price behavior 1, 3, 23, 25, 38–39, 44, 46, 96, 164 –– single stock’s 54 Price bottoms 84, 281 Price breadth 153, 273, 281, 312 Price breakout 203, 263 –– strong 69 Price breaks 51, 68, 99, 103, 151, 184, 186, 225

Price changes 14, 37, 39, 84, 214, 239, 290 –– previous 4 Price charts 9, 19, 30, 102, 121, 223–24, 230, 238, 241 –– previous longer-term 317 Price confirmation 242 Price continuation 85 –– dynamic 271 Price correlation 4 Price crosses 248, 252 –– current stock 248 Price crossover 244, 247–50, 308 Price declining 32, 205, 301 Price direction 36, 85, 97, 135, 140, 215, 221, 271, 281–82 –– offsetting 84 –– previous 79 Price formation signals 274 Price gaps 56–57, 59, 78, 96, 106, 210–11, 238–39, 276–77, 312–13 Price history 294, 301 Price increments 78–79, 84 Price indicators 29, 166, 243 Price jumps signal change 223–24, 226, 228, 230, 232, 234, 236, 238, 240 Price levels 35, 37, 39, 56, 82–84, 263, 272, 311–12, 316–17 Price movement 1–3, 7–9, 25, 33–38, 40–42, 163, 183–84, 201–2, 317–18 –– cause 17 –– consistent downward 153 –– current 318 –– downward 129, 227 –– dynamic 81 –– gapping 57, 204 –– inconsistent 80 –– influence 56 –– longer-term 76 –– managing 199 –– momentary 317 –– opposite 184, 247 –– overlapping 125 –– past 39 –– range-bound 99 –– rational 15–16 –– short-term 1, 3, 85, 163, 224, 315 –– steady 264 –– technical 25 –– unpredictable 271 –– upward 91

Index  Price pattern indicator 119 Price pattern signals 30, 43 Price patterns 12–13, 33–36, 39, 73–74, 164, 171–72, 234–35, 258, 317–18 Price peaks 59, 124, 204 Price proximity 56, 212, 260, 305 Price range 69, 71, 77, 79–80, 171–72, 232, 242, 244, 253 Price retracement 33 Price retreats 91, 104, 108 Price reversals 20, 98, 217, 224 –– probability of 34 –– short-term 245 –– strong 133 Price reverses 84, 248 Price sets 33, 123 Price signals 73–74, 185, 201, 214, 221, 237–38 –– strongest 223 Price spikes 59, 82, 108, 224, 245 –– 11-point 272 –– interim 82 –– large 111 Price strength 73, 165, 177 Price swings 277 Price tests resistance 197 Price theories 12–13, 17 Price tops 131, 280 Price trend analysis 21, 34 Price trends 4, 19–20, 37, 58, 130–31, 177, 181, 285, 294 –– bullish stock 294 –– current 130 –– historical 20 –– stock’s 202 –– strong 285 Price uncertainty 137, 271 Price volatility 14, 21, 34, 75, 244, 278, 301 –– lower stock 285 Price/earnings 286, 290 Prices drop 6, 67 –– large 311–12 Prices opening 239 Prices ranging 79, 280, 301 Prices spike 245 –– low 82 Primary bullish trend 151, 156, 231, 236, 266, 272, 279, 312, 314 Primary consolidation trend 192, 234, 243, 263, 276–77, 292, 294, 301, 315–16 –– longer-term 229

 331

–– long-term 232, 315 Primary downtrends 184, 190, 253 –– new 212 Primary trend movements 308 Primary uptrend 146, 184, 212, 231, 239 –– new 191 –– previous 108 –– slow-moving 229 Profits 18–19, 44, 48, 50, 133, 136, 269, 271, 285–86 Proximity 96, 108, 113–14, 122, 132–33, 151–52, 168–69, 171, 272–73 Proximity of reversals 34, 258 Proximity of reversals to resistance and support 34 Psychology, behavioral 163–65 R Railroads 4–5, 7–8 Random variables 38, 43 Ratio 286–88, 290, 292 –– price earnings 25 Raw money flow (RMF) 215 Reaction high and low prices 59 Reaction highs 32, 59, 64–66 Reaction lows 31, 63–67 Reaction price movement 60 Rectangle top 106–7, 143 Rectangle top and bottom 95, 106, 143 Relationship 25, 44, 47, 88, 94, 137, 287–88, 299–300 Relative strength index. See RSI Repetitive bearish reversal signals 196 Resistance 53–73, 96–100, 102–5, 112–16, 151–55, 168–69, 205–14, 220–28, 232–36 –– falling 70, 84, 89, 91 –– flat 65, 275 –– marking 107, 128 –– new 62, 153, 171, 205, 210 –– previous 59, 62, 66 –– prior 102–3, 194, 203, 221, 229, 235 –– test 60, 85, 100 –– tested 197, 205 –– track 252–53 Resistance level 64, 76, 146, 232, 234, 308 –– new 63, 102, 236 Resistance price 69–70 Resistance zones 68–69 Resumption of major trend 10–11 Retrace 6, 14, 85, 87

332 

 Index

Retracement 7, 30, 73–74, 85–89, 97, 150–51, 210–12, 263–64, 279 Retracement patterns 86 Revenue 22, 34, 186, 287, 289, 291–93, 296–97, 299, 301–2 Revenue and earnings 47, 177, 224, 285, 289, 291, 295–99, 302 Reversal 33–34, 41–46, 73–75, 95–101, 131–32, 134–45, 147–55, 185–86, 257–59 –– beginning of 113, 232 –– candlestick 128, 238, 261 –– coming 33, 63, 104, 115, 119, 196, 204 –– confirmation of 61, 171, 259 –– forecast 55–56, 65, 73, 99, 116, 130, 215, 302 –– forecasting 111, 161, 201 –– identifying 114, 138 –– initial 134, 178 –– likelihood of 46, 108, 115, 235 –– marks 154, 204 –– meeting lines 156 –– piercing lines 155 –– potential 51, 104, 241, 259 –– retracements form 85 –– short-term 33, 74, 113, 133 –– signaled 174 –– spot 108, 214 –– stock 97 –– strong 12, 25, 74, 109, 213, 215, 234, 236, 258 –– strong single-session 235 –– weak 317 Reversal and confirmation 9, 12, 168, 171 Reversal candlesticks 114, 118 Reversal forecast 92, 118 Reversal in Eastern patterns 112–13, 115, 117, 119, 121, 123, 125, 127, 129 Reversal in Western patterns 100–101, 103, 105, 107, 109, 111 Reversal indicators 95, 122, 131, 282 –– favorite 168 –– strong 119, 125 Reversal meeting lines 156 Reversal patterns 95–96, 98, 100, 102, 104, 106, 108, 110, 137–38 Reversal signal –– exceptional 125 –– final 195 Reversal signals 8–9, 97–100, 112–13, 115, 118–19, 131, 137–38, 245–46, 317 –– reliable 170

–– useful 120 Reversal signals beginning 21 Reversal trends 130–31 Reverse 38–39, 41, 45–46, 74, 97, 124, 131–32, 137–38, 257–60 Reverse direction 39, 110 Revert 233, 260 Right proximity 118–19, 124, 130 Rising volume signals 202 Risk 20–23, 25, 45–46, 49–50, 54, 166–67, 268, 271, 282 –– psychology of 165–66 Risk management 19–20, 27, 133 Risk management process 19, 21, 23 Risk transfer 21 RMF (raw money flow) 215 RMH 1–2, 4, 6, 8, 10, 12, 14, 16, 18 Rounding bottom 105–6, 142–43, 150 Rounding top 104–5, 142–43 RS 260 RSI (relative strength index) 42, 215, 259–63, 266–68, 280, 310, 314–16 Rules 6, 8, 33–34, 37, 46–48, 83–84, 223–25, 242, 244 Runaway gaps 104, 111, 124, 170–71, 230, 233–34 RWH (random walk hypothesis) 8, 12, 17–19, 21, 34, 39 S Sample data 35, 38, 43, 47 Scaling 78–80, 113, 152, 271 Science of trend analysis 4, 21, 27, 164, 258, 318 Secondary downtrend, strong 234 Secondary trend activity 95 Secondary trend identification 243 Secondary trend movements 262–63, 266 Secondary trend volatility 309 Secondary trends 9–13, 36–38, 73–75, 82–84, 100–101, 226–29, 231–35, 248–49, 313 –– analysis of 262, 285 –– distinct 58 –– fast-moving 228, 265 –– forming 108 –– short-term 130 Secondary trends offset 46 Sellers 18–19, 54, 56–58, 96–97, 104, 115, 183–84, 186–87, 306–7 Services, free charting 28, 78, 260

Index  Session gaps 230 –– white 120 Sessions 27–28, 112–19, 123–26, 152–54, 156–57, 214–15, 230–31, 234–35, 239–41 –– long 113, 237 –– middle 126–27, 129, 238 –– previous 123, 125, 128, 159, 239 –– second 117, 121, 237 Sessions opening, white 155–56 Share price 133, 244, 285, 290 Short-term continuation signals 148 Short-term price patterns 36–37, 75 Short-term reversal signals 108 Short-term trends 1, 3, 41, 74, 81–82, 173, 257, 259, 317 Shoulders 45, 47, 92, 95, 100–102, 104–5, 135, 137, 139–40 Shoulders patterns 31, 56, 100–101, 137, 139, 308 Side-by-side lines, black 157–58 Signal confirmation 168 Signal line 263–65, 312 Signal patterns 73, 75 Signal strength 191 Signal values 231, 277 Signaling bearish reversal 110 Signaling trend movement 60 Signals 73–75, 114–19, 129–32, 135–42, 235–45, 247–50, 257–64, 305–9, 316–18 –– clear 85, 90, 99, 183, 238, 311–13 –– combined 93, 305 –– double 95, 145 –– early 134, 184, 187 –– false 111, 317 –– important 55, 231, 245 –– independent 227, 244 –– multiple 73, 185, 191 –– occurring 95, 145 –– positive 130–31 –– reliable 94, 143, 239, 242 –– repetitive 146, 183 –– short-term 73, 85, 95 –– strong 126, 130, 171–72, 238, 243, 247, 250, 271, 275 –– stronger 68, 243 –– strongest 96, 132, 227 –– technical 15, 34, 55–56, 137, 169, 258 –– unconfirmed 175–76 –– valid 138, 183, 202 –– weak 74, 172, 317

 333

Signals of supply and demand adjustment 71 Signals reversal 112, 118–19, 227 Slope 13, 27, 35, 37–38, 63, 73, 80, 83, 131 SMA (simple moving average) 29, 241, 244 South Asian stock markets 254 Spikes 44–46, 79, 83–84, 98–99, 105–6, 108, 190, 203, 272 –– excessive 84 Spiking price sessions 110 Spinning top 98, 114–15, 135, 153–55, 169 Spot 82–83, 89, 92, 95–96, 114, 180, 202, 271, 273 Spot market trends 222 Squeeze 96, 128–29, 196–98 Standard deviations 26–30, 33, 43, 84, 94, 244, 273 Statistical analysis 35, 43–45, 257, 274 Statistical tendencies 13–14, 23, 25, 34, 166 Statistically speaking 25–26, 28, 30, 32, 34, 36, 38, 40, 42 Statisticians 26–28, 33, 38–39 Statistics 25, 43–44, 47, 49–50, 83 Stochastic oscillator 259, 266–69 Stock charts 79, 82, 100, 102, 240–41, 260, 294, 299, 301 –– long-term 36 Stock market 181 Stock market investors 49 Stock market prices 23, 51 Stock price behavior 2, 4 Stock price breaks 221 Stock price crosses 248 Stock price levels 37 Stock price trends 35 Stock prices 2–4, 17–19, 27, 29, 38, 43–44, 130, 164–65, 289 Stock prices declining 289, 294 Stock prices of well-managed companies 18 Stock selection 177, 286–87 Stock trading 27, 41 Stock trends 22, 26–28, 35, 38, 40, 43–44, 177, 282 –– channeling 59 Stock values 5, 285 Stocks 5–6, 15–18, 25, 53–55, 97, 127–31, 133–34, 177–79, 285–86 –– channeling 57–58 –– company’s 12, 177, 258 –– higher-priced 5, 77

334 

 Index

–– individual 5–6, 8–9, 12, 16–17, 40–41, 43, 53–55, 95, 97 –– volatile 45, 241 Strategies 50, 94, 133, 163, 179 Strength, trend’s 258–59 Strong continuation signals 66, 137, 151 Strong price movement reverts 1 Strong price movements ranging 315 Strong reversal signals 98, 101, 103, 117, 131, 208, 258 –– lacking 74 Supply 1, 56–57, 62, 184, 285, 292, 306–7 Supply and demand 1–2, 16–19, 33, 36, 55–57, 163, 184, 201–2, 258 –– equilibrium of 18 Supply and demand adjustment 71 Support and rzones 68–69 Support zones 68, 70, 131 Surprises 2, 14, 20, 41, 178, 193, 224–25 Swing traders 1, 26, 29, 37, 39, 57, 59, 131–32, 224 Swing trend movement 239 Swing trend reversals 78, 94 Swing trends 12–13, 25, 35–37, 73–75, 100, 113–14, 172, 238–39, 257–58 Symmetrical triangle 67–68, 86, 98, 111, 187 T Technical indicators 20, 32, 75, 164 Theory 1, 4, 6–9, 12–14, 18, 23, 27 Theory of price movements 23 Theory of trends 2, 4, 6, 8, 10, 12, 14, 16, 18 Thrusting and separating lines 155, 157 Thrusting lines continuation signal 155 Thrusting lines signal 176 Total capitalization ratio 177, 208, 285–86, 288–89, 292–93, 299 Tracking 28, 37, 39–40, 43–44, 59–60, 75–76, 95, 135–36, 138 –– close 254 Tracking price trends 201–2, 204, 206, 208, 210, 212, 214, 216, 218 Tracking stock trends 19 Tracking trends 29, 244 Traders 1, 3–6, 8, 25, 74, 133, 165, 183–85, 307 Trades 1–2, 39, 49, 131–32, 137, 180, 198, 201–2, 271 –– ill-timed 74–75, 163 Trading gaps 225, 228 Trading rules, technical 74, 242

Transportation Average 7, 11–12, 15 Trend analysis indicators 222 Trend analysis value 244 Trend analysts 39, 48, 71 Trend behavior 3, 7, 19, 29, 42–43, 45, 57, 140 Trend climax 208–10 Trend climax and gap patterns 208–9, 211 Trend continuation 265 –– marking bullish 10–11 Trend direction 71, 93–94, 305, 308 –– primary 185, 233 Trend health 130, 273 Trend indicators 43 Trend momentum 13, 175 Trend movement 12, 25, 57, 201 –– historical 22 –– marked secondary 129 Trend reversal 34, 39, 73, 98, 112, 131–32, 137, 175, 222 –– confirming 177 –– possible 244 –– primary 94, 102, 110, 224 –– probability of 34 –– secondary 73–74, 217 Trend signals 302 Trend signals work 302 Trend strength 273 Trend volatility 81, 177 Trendline and channel line 71, 73, 75, 131 Trendlines 20, 22, 68, 71, 73, 75–84, 89, 96, 131 –– consistent 84 –– established 78, 84 –– identifying 87 –– internal 82–84, 87 –– middle bearish 83 –– perfect 76 –– repetitive downward 77 –– valid 83 Trendlines and channel lines 73–74, 76, 78, 80, 82, 84, 86, 88, 90 Trendlines and channel lines track 96 Trends –– bullish swing 139 –– coming consolidation 222 –– established consolidation 235 –– identifying consolidation 198 –– long-term consolidation 309 –– market’s 71 –– marketwide 294

Index  –– medium 6 –– modified consolidation 177 –– multiyear 44, 290 –– narrow 5-point consolidation 309 –– new consolidation 229, 236, 238, 252, 306 –– new consolidation plateau 194 –– secondary consolidation 228 –– short-duration 317 –– single-stock 46 –– strong 74, 112, 151, 178, 234, 258 –– track 28, 131, 161, 305 –– weak 118, 151–52, 176 –– weakening 103, 112 Triangle breakout 187 Triangles 65, 67, 85–86, 111, 183, 187, 189, 196, 274–76 –– ascending 65–66, 69, 111, 151, 153, 187, 221, 276 Triangles and wedges 111 Triangle-Shaped Trends 65, 67 Two-session reversal signal 119 Two-session volume spike 203 Two-year chart 191, 194, 305, 316 U UK stock prices 254 Uncertainty 25–26, 41, 45, 54, 58, 60, 186, 195–96, 306 Upper band 29–33, 43, 196–97, 199, 244–45 Upside breakout 187, 190, 193, 198 Upside gap 117, 119, 125–26, 155, 157–59, 169, 173, 192, 226–27 Uptrend 81–82, 114–19, 121–26, 172–76, 183–87, 193–96, 209–13, 225–28, 251–53 –– coming 142 –– gradual 232 –– new 106, 232, 252, 263 –– secondary 184–85 –– short-term 128 –– strong 65, 99, 180, 243 Uptrend line 76 Uptrend signals 192 Uptrend’s success 203 V Validation 83–84 Valuation 12, 25, 44 Value 2–3, 21–22, 87, 177–78, 220–22, 241–42, 262–63, 285–86, 291–92 –– fundamental 16, 40, 286–87

 335

–– risk-adjusted 20 –– signaling 229 –– stock’s 133, 287, 294 Value investments 132, 285–86 Variables 20, 22, 27, 29, 33, 36, 43, 97 Verizon 288–89, 296–97, 299–300 VIX 282–83 Volatile 1, 32, 60–61, 77, 79–81, 111, 123, 127, 272 Volatile price patterns 61, 91, 306 Volatility 29–30, 33–34, 45–46, 53–54, 60–61, 77–81, 131–32, 271–83, 286 –– high 44, 197, 268, 271–72, 277, 309, 315 –– technical 177, 268, 286 Volatility index 282 Volatility indicator 273, 282 Volatility levels 31, 274–75, 277 Volume 8, 22–23, 131–32, 190, 201–8, 212, 214–19, 223–24, 312–14 –– comparing price to 60, 131 –– day’s 212 –– decreasing 278–79 –– high 8, 37, 86, 104, 204–7 –– increasing 278 –– rising 203 Volume indicators 35, 39, 43, 46, 201, 212–13, 215–16, 218, 222 Volume levels 8, 73, 190, 278–79 –– chart’s 192 Volume signals 201–2, 204, 206, 208, 210, 212, 214, 222, 258–59 –– strong 210 Volume signals aid, calculated 212 Volume spike –– second 45, 205 –– strong 99, 208 Volume spikes 44–45, 78–79, 84, 104, 189–92, 204–8, 210–12, 223, 311–12 –– distinct 45, 190 Volume spikes and gaps 189–90 Volume spikes and indicators 222 Volume surge 203, 208–10 Volume trend 278 –– low 207 Volume-marked breakouts 204–5, 207 W, X, Y Wait and see forecast 183 Weakness 29, 31–32, 34, 37–38, 130, 163–65, 177, 208, 258

336 

 Index

Wedges 63–65, 67, 111, 246, 274–75, 305 –– falling 64–65, 111, 261, 274–75 Wedge-shaped trends 63 Wells Fargo (WFC) 294–95, 297, 299–300 Western continuation signals 138–39, 141, 143, 145, 147, 149 Western patterns 100–101, 103, 105, 107, 109, 111–12 Western reversal signals 112 Western signals 115, 151

White candlestick 112, 123, 128, 157–58 –– long 113, 152, 170–71 White lines continuation signal 265 White session 117–21, 125–26, 155–57, 225–26 –– second 159, 226 White soldiers 96, 122–25, 210, 238 Z Zones 33, 68–69, 199, 257, 260 –– resistance and support 68, 70