Table of contents : Preface Synopsis Abstract I. Introduction II. Linear Algebra III. Calculus IV. Probability Theory V. Quantum Mathematics Contents About the Author Part I Introduction 1 Series and Functions 1.1 Introduction 1.2 Basic Algebra 1.2.1 Binomial Expansion 1.3 Quadratic Polynomial 1.3.1 Higher Order Polynomial 1.4 Finite Series 1.4.1 Example: NPV 1.4.2 Example: Coupon Bond 1.4.3 Example: Valuation of a Firm 1.4.4 Example: 1/3 1.5 Infinite Series 1.6 Cauchy Convergence 1.6.1 Example: Geometric Series 1.7 Expansion of sqrt1+x 1.8 Problems 1.9 Functions 1.10 Exponential Function 1.10.1 Parametric Representation 1.10.2 Continuous Compounding 1.10.3 Logarithm Function 1.11 Supply and Demand Functions 1.12 Option Theory Payoff 1.13 Interest Rates; Coupon Bonds 1.14 Problems Part II Linear Algebra 2 Simultaneous Linear Equations 2.1 Introduction 2.2 Two Commodities 2.3 Vectors 2.4 Basis Vectors 2.4.1 Scalar Product 2.5 Linear Transformations; Matrices 2.6 EN: N-Dimensional Linear Vector Space 2.7 Linear Transformations of EN 2.8 Problems 3 Matrices 3.1 Introduction 3.2 Matrix Multiplication 3.3 Properties of NtimesN Matrices 3.4 System of Linear Equations 3.5 Determinant: 2times2 Case 3.6 Inverse of a 2times2 Matrix 3.7 Tensor (Outer) Product; Transpose 3.7.1 Transpose 3.8 Eigenvalues and Eigenvectors 3.8.1 Matrices: Spectral Decomposition 3.9 Problems 4 Square Matrices 4.1 Introduction 4.2 Determinant: 3times3 Case 4.3 Properties of Determinants 4.4 NtimesN Determinant 4.4.1 Inverse of a NtimesN Matrix 4.5 Leontief Input-Output Model 4.5.1 Hawkins-Simon Condition 4.5.2 Two Commodity Case 4.6 Symmetric Matrices 4.7 2times2 Symmetric Matrix 4.8 NtimesN Symmetric Matrix 4.9 Orthogonal Matrices 4.10 Symmetric Matrix: Diagonalization 4.10.1 Functions of a Symmetric Matrix 4.11 Hermitian Matrices 4.12 Diagonalizable Matrices 4.12.1 Non-symmetric Matrix 4.13 Change of Basis States 4.13.1 Symmetric Matrix: Change of Basis 4.13.2 Diagonalization and Rotation 4.13.3 Rotation and Inversion 4.13.4 Hermitian Matrix: Change of Basis 4.14 Problems Part III Calculus 5 Integration 5.1 Introduction 5.2 Sums Leading to Integrals 5.3 Definite and Indefinite Integrals 5.4 Applications in Economics 5.5 Multiple Integrals 5.5.1 Change of Variables 5.6 Gaussian Integration 5.6.1 Gaussian Integration for Options 5.7 N-Dimensional Gaussian Integration 5.8 Problems 6 Differentiation 6.1 Introduction 6.2 Differentiation: Inverse of Integration 6.3 Rules of Differentiation 6.4 Integration by Parts 6.5 Taylor Expansion 6.6 Minimum and Maximum 6.6.1 Maximizing Profit 6.7 Integration; Change of Variable 6.8 Partial Derivatives 6.8.1 Cobb-Douglas Production Function 6.8.2 Chain Rule; Jacobian 6.8.3 Polar Coordinates; Gaussian integration 6.9 Hessian Matrix: Critical Points 6.10 Firm's Profit Maximization 6.11 Constrained Optimization: Lagrange Multiplier 6.11.1 Interpretation of λc 6.12 Line Integral; Exact and Inexact Differentials 6.13 Problems 7 Ordinary Differential Equations 7.1 Introduction 7.2 Separable Differential Equations 7.3 Linear Differential Equations 7.3.1 Dynamics of Price: Supply and Demand 7.4 Bernoulli Differential Equation 7.5 Swan-Solow Model 7.6 Homogeneous Differential Equation 7.7 Second Order Linear Differential Equations 7.7.1 Special Case 7.8 Riccati Differential Equation 7.9 Inhomogeneous Second Order Differential Equations 7.9.1 Special Case 7.10 System of Linear Differential Equations 7.11 Problems Part IV Probability Theory 8 Random Variables 8.1 Introduction: Risk 8.1.1 Example 8.2 Probability Theory 8.3 Discrete Random Variables 8.3.1 Bernoulli Random Variable 8.3.2 Binomial Random Variable 8.3.3 Poisson Random Variable 8.4 Continuous Random Variables 8.4.1 Uniform Random Variable 8.4.2 Exponential Random Variable 8.4.3 Normal (Gaussian) Random Variable 8.5 Problems 9 Option Pricing and Binomial Model 9.1 Introduction 9.2 Pricing Options: Dynamic Replication 9.2.1 Single Step Binomial Model 9.3 Dynamic Portfolio 9.3.1 Single Step Option Price 9.4 Martingale: Risk-Neutral Valuation 9.5 N-Steps Binomial Option Price 9.6 N=2 Option Price: Binomial Tree 9.7 Binomial Option Price: Put-Call Parity 9.8 Summary 9.9 Problems 10 Probability Distribution Functions 10.1 Introduction 10.1.1 Cumulative Distribution Function 10.2 Axioms of Probability Theory 10.3 Joint Probability Density 10.4 Independent Random Variables 10.5 Central Limit Theorem: Law of Large Numbers 10.5.1 Binomial Random Variable 10.5.2 Limit of Binomial Distribution 10.6 Correlated Random Variables 10.6.1 Bernoulli Random Variables 10.6.2 Gaussian Random Variables 10.7 Marginal Probability Density 10.8 Conditional Expectation Value 10.8.1 Bernoulli Random Variables 10.8.2 Binomial Random Variables 10.8.3 Poisson Random Variables 10.8.4 Gaussian Random Variables 10.9 Problems 11 Stochastic Processes and Black–Scholes Equation 11.1 Introduction 11.2 Stochastic Differential Equation 11.3 Gaussian White Noise and Delta Function 11.3.1 Integrals of White Noise 11.4 Ito Calculus 11.5 Lognormal Stock Price 11.5.1 Geometric Mean of Stock Price 11.6 Linear Langevin Equation 11.6.1 Security's Random Paths 11.7 Black–Scholes Equation; Hedged Portfolio 11.8 Assumptions in the Black–Scholes 11.9 Martingale: Black–Scholes Model 11.10 Black–Scholes Option Price 11.10.1 Put-Call Parity 11.11 Black–Scholes Limit of the Binomial Model 11.12 Problems 12 Stochastic Processes and Merton Equation 12.1 Introduction 12.2 Firm's Stochastic Differential Equation 12.3 Contingent Claims on Firm 12.4 No Arbitrage Portfolio 12.5 Merton Equation 12.6 Risky Corporate Coupon Bond 12.7 Zero Coupon Corporate Bond 12.8 Zero Coupon Bond Yield Spread 12.9 Default Probability and Leverage 12.10 Recovery Rate of Defaulted Bonds 12.11 Merton's Risky Coupon Bond Part V Quantum Mathematics 13 Functional Analysis 13.1 Introduction 13.2 Dirac Bracket: Vector Notation 13.3 Continuous Basis States 13.4 Dirac Delta Function 13.5 Basis States for Function Space 13.6 Operators on Function Space 13.7 Gaussian Kernel 13.8 Fourier Transform 13.8.1 Taylor Expansion 13.8.2 Green's Function 13.8.3 Black–Scholes Option Price 13.9 Functional Differentiation 13.10 Functional Integration 13.11 Gaussian White Noise 13.12 Simple Harmonic Oscillator 13.13 Acceleration Action 14 Hamiltonians 14.1 Introduction 14.2 Black–Scholes and Merton Hamiltonian 14.3 Option Pricing Kernel 14.4 Black–Scholes Pricing Kernel 14.5 Merton Oscillator Hamiltonian 14.6 Hamiltonian: Martingale Condition 14.7 Hamiltonian and Potentials 14.8 Double Knock Out Barrier Option 15 Path Integrals 15.1 Introduction 15.2 Feynman Path Integral 15.3 Path Dependent Options 15.4 Merton Lagrangian 15.5 Black-Scholes Discrete Path Integral 15.6 Path Integral: Time-Dependent Volatility 15.7 Black-Scholes Continuous Path Integral 15.8 Stationary Action: Euler-Lagrange Equation 15.9 Black-Scholes Euler-Lagrange Equation 15.10 Stationary Action: Time Dependent Volatility 15.11 Harmonic Oscillator Pricing Kernel 15.12 Merton Oscillator Pricing Kernel 15.13 Martingale: Merton Model 16 Quantum Fields for Bonds and Interest Rates 16.1 Introduction 16.2 Coupon Bonds 16.3 Forward Interest Rates 16.4 Action and Lagrangian 16.5 Correlation Function 16.6 Time Dependent State Space mathcalVt 16.7 Time Dependent Hamiltonian 16.8 Path Integral: Martingale 16.9 Numeraire 16.10 Zero Coupon Bond Call Option 16.11 Libor: Simple Interest Rate 16.12 Libor Market Model 16.13 Libor Forward Interest Rates 16.14 Libor Lagrangian 16.15 Libor Hamiltonian: Martingale 16.16 Black's Caplet Price Appendix Mathematics of Numbers A.1 Introduction A.2 Integers A.2.1 Prime Numbers A.2.2 Irrational Numbers A.2.3 Transcendental Numbers A.3 Real Numbers A.3.1 Decimal Expansion A.3.2 Complex Numbers A.4 Cantor's Diagonal Construction A.5 Higher Order Infinities A.6 Meta-mathematics A.7 Gödel's Incompleteness Appendix References Index