Stochastic Methods in Asset Pricing
by Lyasoff
ISBN: 9780262364034 | Copyright 2017
Instructor Requests
Expand/Collapse All | |
---|---|
Contents (pg. vii) | |
Preface (pg. xi) | |
Notation (pg. xv) | |
Preliminaries (pg. xvii) | |
1 Probability Spaces and Related Structures (pg. 1) | |
1.1 Randomness in the Financial Markets (pg. 1) | |
1.2 A Bird’s-Eye View of the One-Period Binomial Model (pg. 4) | |
1.3 Probability Spaces (pg. 8) | |
1.4 Coin Toss Space and Random Walk (pg. 17) | |
1.5 Borel (pg. 26) | |
2 Integration (pg. 35) | |
2.1 Measurable Functions and Random Variables (pg. 35) | |
2.2 Distribution Laws (pg. 42) | |
2.3 Lebesgue Integral (pg. 46) | |
2.4 Convergence of Integrals (pg. 55) | |
2.5 Integration Tools (pg. 57) | |
2.6 The Inverse of an Increasing Function (pg. 66) | |
3 Absolute Continuity, Conditioning, and Independence (pg. 69) | |
3.1 Quasi-invariance of the Gaussian Distribution under Translation (pg. 69) | |
3.2 Moment-Generating Functions, Laplace, and Fourier Transforms (pg. 72) | |
3.3 Conditioning and Independence (pg. 76) | |
3.4 Multivariate Gaussian Distribution (pg. 87) | |
3.5 Hermite–Gauss Quadratures (pg. 92) | |
4 Convergence of Random Variables (pg. 97) | |
4.1 Types of Convergence for Sequences of Random Variables (pg. 97) | |
4.2 Uniform Integrability (pg. 103) | |
4.3 Sequences of Independent Random Variables and Events (pg. 105) | |
4.4 Law of Large Numbers and the Central Limit Theorem (pg. 108) | |
5 The Art of Random Sampling (pg. 113) | |
5.1 Motivation (pg. 113) | |
5.2 Layer Cake Formulas (pg. 114) | |
5.3 The Antithetic Variates Method (pg. 117) | |
5.4 The Importance Sampling Method (pg. 119) | |
5.5 The Acceptance–Rejection Method (pg. 120) | |
6 Equilibrium Asset Pricing in Finite Economies (pg. 123) | |
6.1 Information Structure (pg. 124) | |
6.2 Risk Preferences (pg. 126) | |
6.3 The Multiperiod Endowment Economy (pg. 137) | |
6.4 General Equilibrium (pg. 144) | |
6.5 The Two Fundamental Theorems of Asset Pricing (pg. 150) | |
6.6 From Stochastic Discount Factors to Equivalent Measures and Local Martingales (pg. 155) | |
7 Crash Course on Discrete-Time Martingales (pg. 161) | |
7.1 Basic Concepts and Definitions (pg. 161) | |
7.2 Predictable Compensators (pg. 168) | |
7.3 Fundamental Inequalities and Convergence (pg. 170) | |
8 Stochastic Processes and Brownian Motion (pg. 175) | |
8.1 General Properties and Definitions (pg. 176) | |
8.2 Limit of the Binomial Asset Pricing Model (pg. 182) | |
8.3 Construction of Brownian Motion and First Properties (pg. 186) | |
8.4 The Wiener Measure (pg. 189) | |
8.5 Filtrations, Stopping Times, and Such (pg. 191) | |
8.6 Brownian Filtrations (pg. 206) | |
8.7 Total Variation (pg. 208) | |
8.8 Quadratic Variation (pg. 211) | |
8.9 Brownian Sample Paths Are Nowhere Differentiable (pg. 213) | |
8.10 Some Special Features of Brownian Sample Paths (pg. 215) | |
9 Crash Course on Continuous-Time Martingales (pg. 221) | |
9.1 Definitions and First Properties (pg. 221) | |
9.2 Poisson Process and First Encounter with Lévy Processes (pg. 225) | |
9.3 Regularity of Paths, Optional Stopping, and Convergence (pg. 227) | |
9.4 Doob–Meyer Decomposition (pg. 237) | |
9.5 Local Martingales and Semimartingales (pg. 240) | |
9.6 The Space of (pg. 248) | |
9.7 The Binomial Asset Pricing Model Revisited (pg. 252) | |
10 Stochastic Integration (pg. 257) | |
10.1 Basic Examples and Intuition (pg. 258) | |
10.2 Stochastic Integrals with Respect to Continuous Local Martingales (pg. 262) | |
10.3 Stochastic Integrals with Respect to Continuous Semimartingales (pg. 271) | |
10.4 Itô’s Formula (pg. 273) | |
10.5 Stochastic Integrals with Respect to Brownian Motion (pg. 275) | |
10.6 Girsanov’s Theorem (pg. 281) | |
10.7 Local Times and Tanaka’s Formula (pg. 285) | |
10.8 Reflected Brownian Motion (pg. 290) | |
11 Stochastic Differential Equations (pg. 295) | |
11.1 An Example (pg. 295) | |
11.2 Strong and Weak Solutions (pg. 296) | |
11.3 Existence of Solutions (pg. 307) | |
11.4 Linear Stochastic Differential Equations (pg. 315) | |
11.5 Some Common Diffusion Models Used in Asset Pricing (pg. 319) | |
12 The Connection between SDEs and PDEs (pg. 325) | |
12.1 Feynman–Kac Formula (pg. 325) | |
12.2 Fokker–Planck Equation (pg. 331) | |
13 Brief Introduction to Asset Pricing in Continuous Time (pg. 337) | |
13.1 Basic Concepts and Definitions (pg. 337) | |
13.2 Trading Strategy and Wealth Dynamics (pg. 345) | |
13.3 Equivalent Local Martingale Measures (pg. 348) | |
13.4 The Two Fundamental Theorems of Asset Pricing (pg. 352) | |
14 Replication and Arbitrage (pg. 357) | |
14.1 Résumé of Malliavin Calculus (pg. 357) | |
14.2 European-Style Contingent Claims (pg. 360) | |
14.3 The Martingale Solution to Merton’s Problem (pg. 366) | |
14.4 American-Style Contingent Claims (pg. 370) | |
14.5 Put–Call Symmetry and Foreign Exchange Options (pg. 378) | |
14.6 Exchange Options (pg. 380) | |
14.7 Stochastic Volatility Models (pg. 382) | |
14.8 Dupire’s Formula (pg. 394) | |
15 Résumé of Stochastic Calculus with Discontinuous Processes (pg. 397) | |
15.1 Martingales, Local Martingales, and Semimartingales with Jumps (pg. 397) | |
15.2 Stochastic Integrals with Respect to Semimartingales with Jumps (pg. 409) | |
15.3 Quadratic Variation and Itô’s Formula (pg. 417) | |
16 Random Measures and Lévy Processes (pg. 425) | |
16.1 Poisson Random Measures (pg. 425) | |
16.2 Lévy Processes (pg. 433) | |
16.3 Stochastic Integrals with Respect to Lévy Processes (pg. 439) | |
16.4 Stochastic Exponents (pg. 444) | |
16.5 Change of Measure and Removal of the Drift (pg. 447) | |
16.6 Lévy–Itô Diffusions (pg. 452) | |
16.7 An Asset Pricing Model with Jumps in the Returns (pg. 456) | |
17 Résumé of the Theory and Methods of Stochastic Optimal Control (pg. 463) | |
17.1 The Moon-Landing Problem (pg. 464) | |
17.2 Principle of Dynamic Programming and the HJB Equation (pg. 465) | |
17.3 Some Variations of the PDP and the HJB Equation (pg. 474) | |
18 Applications to Dynamic Asset Pricing (pg. 481) | |
18.1 Merton’s Problem with Intertemporal Consumption and No Rebalancing Costs (pg. 481) | |
18.2 Merton’s Problem with Intertemporal Consumption and Rebalancing Costs (pg. 490) | |
18.3 Real Options (pg. 502) | |
18.4 The Exercise Boundary for American Calls and Puts (pg. 510) | |
18.5 Corporate Debt, Equity, Dividend Policy, and the Modigliani–Miller Proposition (pg. 517) | |
Appendix A: Résumé of Analysis and Topology (pg. 523) | |
Appendix B: Computer Code (pg. 541) | |
B.1 Working with Market Data (pg. 541) | |
B.2 Simulation of Multivariate Gaussian Laws (pg. 543) | |
B.3 Numerical Program for American-Style Call Options (pg. 546) | |
Select Bibliography (pg. 549) | |
Index (pg. 575) | |
Contents (pg. vii) | |
Preface (pg. xi) | |
Notation (pg. xv) | |
Preliminaries (pg. xvii) | |
1 Probability Spaces and Related Structures (pg. 1) | |
1.1 Randomness in the Financial Markets (pg. 1) | |
1.2 A Bird’s-Eye View of the One-Period Binomial Model (pg. 4) | |
1.3 Probability Spaces (pg. 8) | |
1.4 Coin Toss Space and Random Walk (pg. 17) | |
1.5 Borel (pg. 26) | |
2 Integration (pg. 35) | |
2.1 Measurable Functions and Random Variables (pg. 35) | |
2.2 Distribution Laws (pg. 42) | |
2.3 Lebesgue Integral (pg. 46) | |
2.4 Convergence of Integrals (pg. 55) | |
2.5 Integration Tools (pg. 57) | |
2.6 The Inverse of an Increasing Function (pg. 66) | |
3 Absolute Continuity, Conditioning, and Independence (pg. 69) | |
3.1 Quasi-invariance of the Gaussian Distribution under Translation (pg. 69) | |
3.2 Moment-Generating Functions, Laplace, and Fourier Transforms (pg. 72) | |
3.3 Conditioning and Independence (pg. 76) | |
3.4 Multivariate Gaussian Distribution (pg. 87) | |
3.5 Hermite–Gauss Quadratures (pg. 92) | |
4 Convergence of Random Variables (pg. 97) | |
4.1 Types of Convergence for Sequences of Random Variables (pg. 97) | |
4.2 Uniform Integrability (pg. 103) | |
4.3 Sequences of Independent Random Variables and Events (pg. 105) | |
4.4 Law of Large Numbers and the Central Limit Theorem (pg. 108) | |
5 The Art of Random Sampling (pg. 113) | |
5.1 Motivation (pg. 113) | |
5.2 Layer Cake Formulas (pg. 114) | |
5.3 The Antithetic Variates Method (pg. 117) | |
5.4 The Importance Sampling Method (pg. 119) | |
5.5 The Acceptance–Rejection Method (pg. 120) | |
6 Equilibrium Asset Pricing in Finite Economies (pg. 123) | |
6.1 Information Structure (pg. 124) | |
6.2 Risk Preferences (pg. 126) | |
6.3 The Multiperiod Endowment Economy (pg. 137) | |
6.4 General Equilibrium (pg. 144) | |
6.5 The Two Fundamental Theorems of Asset Pricing (pg. 150) | |
6.6 From Stochastic Discount Factors to Equivalent Measures and Local Martingales (pg. 155) | |
7 Crash Course on Discrete-Time Martingales (pg. 161) | |
7.1 Basic Concepts and Definitions (pg. 161) | |
7.2 Predictable Compensators (pg. 168) | |
7.3 Fundamental Inequalities and Convergence (pg. 170) | |
8 Stochastic Processes and Brownian Motion (pg. 175) | |
8.1 General Properties and Definitions (pg. 176) | |
8.2 Limit of the Binomial Asset Pricing Model (pg. 182) | |
8.3 Construction of Brownian Motion and First Properties (pg. 186) | |
8.4 The Wiener Measure (pg. 189) | |
8.5 Filtrations, Stopping Times, and Such (pg. 191) | |
8.6 Brownian Filtrations (pg. 206) | |
8.7 Total Variation (pg. 208) | |
8.8 Quadratic Variation (pg. 211) | |
8.9 Brownian Sample Paths Are Nowhere Differentiable (pg. 213) | |
8.10 Some Special Features of Brownian Sample Paths (pg. 215) | |
9 Crash Course on Continuous-Time Martingales (pg. 221) | |
9.1 Definitions and First Properties (pg. 221) | |
9.2 Poisson Process and First Encounter with Lévy Processes (pg. 225) | |
9.3 Regularity of Paths, Optional Stopping, and Convergence (pg. 227) | |
9.4 Doob–Meyer Decomposition (pg. 237) | |
9.5 Local Martingales and Semimartingales (pg. 240) | |
9.6 The Space of (pg. 248) | |
9.7 The Binomial Asset Pricing Model Revisited (pg. 252) | |
10 Stochastic Integration (pg. 257) | |
10.1 Basic Examples and Intuition (pg. 258) | |
10.2 Stochastic Integrals with Respect to Continuous Local Martingales (pg. 262) | |
10.3 Stochastic Integrals with Respect to Continuous Semimartingales (pg. 271) | |
10.4 Itô’s Formula (pg. 273) | |
10.5 Stochastic Integrals with Respect to Brownian Motion (pg. 275) | |
10.6 Girsanov’s Theorem (pg. 281) | |
10.7 Local Times and Tanaka’s Formula (pg. 285) | |
10.8 Reflected Brownian Motion (pg. 290) | |
11 Stochastic Differential Equations (pg. 295) | |
11.1 An Example (pg. 295) | |
11.2 Strong and Weak Solutions (pg. 296) | |
11.3 Existence of Solutions (pg. 307) | |
11.4 Linear Stochastic Differential Equations (pg. 315) | |
11.5 Some Common Diffusion Models Used in Asset Pricing (pg. 319) | |
12 The Connection between SDEs and PDEs (pg. 325) | |
12.1 Feynman–Kac Formula (pg. 325) | |
12.2 Fokker–Planck Equation (pg. 331) | |
13 Brief Introduction to Asset Pricing in Continuous Time (pg. 337) | |
13.1 Basic Concepts and Definitions (pg. 337) | |
13.2 Trading Strategy and Wealth Dynamics (pg. 345) | |
13.3 Equivalent Local Martingale Measures (pg. 348) | |
13.4 The Two Fundamental Theorems of Asset Pricing (pg. 352) | |
14 Replication and Arbitrage (pg. 357) | |
14.1 Résumé of Malliavin Calculus (pg. 357) | |
14.2 European-Style Contingent Claims (pg. 360) | |
14.3 The Martingale Solution to Merton’s Problem (pg. 366) | |
14.4 American-Style Contingent Claims (pg. 370) | |
14.5 Put–Call Symmetry and Foreign Exchange Options (pg. 378) | |
14.6 Exchange Options (pg. 380) | |
14.7 Stochastic Volatility Models (pg. 382) | |
14.8 Dupire’s Formula (pg. 394) | |
15 Résumé of Stochastic Calculus with Discontinuous Processes (pg. 397) | |
15.1 Martingales, Local Martingales, and Semimartingales with Jumps (pg. 397) | |
15.2 Stochastic Integrals with Respect to Semimartingales with Jumps (pg. 409) | |
15.3 Quadratic Variation and Itô’s Formula (pg. 417) | |
16 Random Measures and Lévy Processes (pg. 425) | |
16.1 Poisson Random Measures (pg. 425) | |
16.2 Lévy Processes (pg. 433) | |
16.3 Stochastic Integrals with Respect to Lévy Processes (pg. 439) | |
16.4 Stochastic Exponents (pg. 444) | |
16.5 Change of Measure and Removal of the Drift (pg. 447) | |
16.6 Lévy–Itô Diffusions (pg. 452) | |
16.7 An Asset Pricing Model with Jumps in the Returns (pg. 456) | |
17 Résumé of the Theory and Methods of Stochastic Optimal Control (pg. 463) | |
17.1 The Moon-Landing Problem (pg. 464) | |
17.2 Principle of Dynamic Programming and the HJB Equation (pg. 465) | |
17.3 Some Variations of the PDP and the HJB Equation (pg. 474) | |
18 Applications to Dynamic Asset Pricing (pg. 481) | |
18.1 Merton’s Problem with Intertemporal Consumption and No Rebalancing Costs (pg. 481) | |
18.2 Merton’s Problem with Intertemporal Consumption and Rebalancing Costs (pg. 490) | |
18.3 Real Options (pg. 502) | |
18.4 The Exercise Boundary for American Calls and Puts (pg. 510) | |
18.5 Corporate Debt, Equity, Dividend Policy, and the Modigliani–Miller Proposition (pg. 517) | |
Appendix A: Résumé of Analysis and Topology (pg. 523) | |
Appendix B: Computer Code (pg. 541) | |
B.1 Working with Market Data (pg. 541) | |
B.2 Simulation of Multivariate Gaussian Laws (pg. 543) | |
B.3 Numerical Program for American-Style Call Options (pg. 546) | |
Select Bibliography (pg. 549) | |
Index (pg. 575) | |
1.1 Randomness in the Financial Markets (pg. 1) | |
1.2 A Bird’s-Eye View of the One-Period Binomial Model (pg. 4) | |
1.3 Probability Spaces (pg. 8) | |
1.4 Coin Toss Space and Random Walk (pg. 17) | |
1.5 Borel (pg. 26) | |
2.1 Measurable Functions and Random Variables (pg. 35) | |
2.2 Distribution Laws (pg. 42) | |
2.3 Lebesgue Integral (pg. 46) | |
2.4 Convergence of Integrals (pg. 55) | |
2.5 Integration Tools (pg. 57) | |
2.6 The Inverse of an Increasing Function (pg. 66) | |
3.1 Quasi-invariance of the Gaussian Distribution under Translation (pg. 69) | |
3.2 Moment-Generating Functions, Laplace, and Fourier Transforms (pg. 72) | |
3.3 Conditioning and Independence (pg. 76) | |
3.4 Multivariate Gaussian Distribution (pg. 87) | |
3.5 Hermite–Gauss Quadratures (pg. 92) | |
4.1 Types of Convergence for Sequences of Random Variables (pg. 97) | |
4.2 Uniform Integrability (pg. 103) | |
4.3 Sequences of Independent Random Variables and Events (pg. 105) | |
4.4 Law of Large Numbers and the Central Limit Theorem (pg. 108) | |
5.1 Motivation (pg. 113) | |
5.2 Layer Cake Formulas (pg. 114) | |
5.3 The Antithetic Variates Method (pg. 117) | |
5.4 The Importance Sampling Method (pg. 119) | |
5.5 The Acceptance–Rejection Method (pg. 120) | |
6.1 Information Structure (pg. 124) | |
6.2 Risk Preferences (pg. 126) | |
6.3 The Multiperiod Endowment Economy (pg. 137) | |
6.4 General Equilibrium (pg. 144) | |
6.5 The Two Fundamental Theorems of Asset Pricing (pg. 150) | |
6.6 From Stochastic Discount Factors to Equivalent Measures and Local Martingales (pg. 155) | |
7.1 Basic Concepts and Definitions (pg. 161) | |
7.2 Predictable Compensators (pg. 168) | |
7.3 Fundamental Inequalities and Convergence (pg. 170) | |
8.1 General Properties and Definitions (pg. 176) | |
8.2 Limit of the Binomial Asset Pricing Model (pg. 182) | |
8.3 Construction of Brownian Motion and First Properties (pg. 186) | |
8.4 The Wiener Measure (pg. 189) | |
8.5 Filtrations, Stopping Times, and Such (pg. 191) | |
8.6 Brownian Filtrations (pg. 206) | |
8.7 Total Variation (pg. 208) | |
8.8 Quadratic Variation (pg. 211) | |
8.9 Brownian Sample Paths Are Nowhere Differentiable (pg. 213) | |
8.10 Some Special Features of Brownian Sample Paths (pg. 215) | |
9.1 Definitions and First Properties (pg. 221) | |
9.2 Poisson Process and First Encounter with Lévy Processes (pg. 225) | |
9.3 Regularity of Paths, Optional Stopping, and Convergence (pg. 227) | |
9.4 Doob–Meyer Decomposition (pg. 237) | |
9.5 Local Martingales and Semimartingales (pg. 240) | |
9.6 The Space of (pg. 248) | |
9.7 The Binomial Asset Pricing Model Revisited (pg. 252) | |
10.1 Basic Examples and Intuition (pg. 258) | |
10.2 Stochastic Integrals with Respect to Continuous Local Martingales (pg. 262) | |
10.3 Stochastic Integrals with Respect to Continuous Semimartingales (pg. 271) | |
10.4 Itô’s Formula (pg. 273) | |
10.5 Stochastic Integrals with Respect to Brownian Motion (pg. 275) | |
10.6 Girsanov’s Theorem (pg. 281) | |
10.7 Local Times and Tanaka’s Formula (pg. 285) | |
10.8 Reflected Brownian Motion (pg. 290) | |
11.1 An Example (pg. 295) | |
11.2 Strong and Weak Solutions (pg. 296) | |
11.3 Existence of Solutions (pg. 307) | |
11.4 Linear Stochastic Differential Equations (pg. 315) | |
11.5 Some Common Diffusion Models Used in Asset Pricing (pg. 319) | |
12.1 Feynman–Kac Formula (pg. 325) | |
12.2 Fokker–Planck Equation (pg. 331) | |
13.1 Basic Concepts and Definitions (pg. 337) | |
13.2 Trading Strategy and Wealth Dynamics (pg. 345) | |
13.3 Equivalent Local Martingale Measures (pg. 348) | |
13.4 The Two Fundamental Theorems of Asset Pricing (pg. 352) | |
14.1 Résumé of Malliavin Calculus (pg. 357) | |
14.2 European-Style Contingent Claims (pg. 360) | |
14.3 The Martingale Solution to Merton’s Problem (pg. 366) | |
14.4 American-Style Contingent Claims (pg. 370) | |
14.5 Put–Call Symmetry and Foreign Exchange Options (pg. 378) | |
14.6 Exchange Options (pg. 380) | |
14.7 Stochastic Volatility Models (pg. 382) | |
14.8 Dupire’s Formula (pg. 394) | |
15.1 Martingales, Local Martingales, and Semimartingales with Jumps (pg. 397) | |
15.2 Stochastic Integrals with Respect to Semimartingales with Jumps (pg. 409) | |
15.3 Quadratic Variation and Itô’s Formula (pg. 417) | |
16.1 Poisson Random Measures (pg. 425) | |
16.2 Lévy Processes (pg. 433) | |
16.3 Stochastic Integrals with Respect to Lévy Processes (pg. 439) | |
16.4 Stochastic Exponents (pg. 444) | |
16.5 Change of Measure and Removal of the Drift (pg. 447) | |
16.6 Lévy–Itô Diffusions (pg. 452) | |
16.7 An Asset Pricing Model with Jumps in the Returns (pg. 456) | |
17.1 The Moon-Landing Problem (pg. 464) | |
17.2 Principle of Dynamic Programming and the HJB Equation (pg. 465) | |
17.3 Some Variations of the PDP and the HJB Equation (pg. 474) | |
18.1 Merton’s Problem with Intertemporal Consumption and No Rebalancing Costs (pg. 481) | |
18.2 Merton’s Problem with Intertemporal Consumption and Rebalancing Costs (pg. 490) | |
18.3 Real Options (pg. 502) | |
18.4 The Exercise Boundary for American Calls and Puts (pg. 510) | |
18.5 Corporate Debt, Equity, Dividend Policy, and the Modigliani–Miller Proposition (pg. 517) | |
B.1 Working with Market Data (pg. 541) | |
B.2 Simulation of Multivariate Gaussian Laws (pg. 543) | |
B.3 Numerical Program for American-Style Call Options (pg. 546) | |
1.1 Randomness in the Financial Markets (pg. 1) | |
1.2 A Bird’s-Eye View of the One-Period Binomial Model (pg. 4) | |
1.3 Probability Spaces (pg. 8) | |
1.4 Coin Toss Space and Random Walk (pg. 17) | |
1.5 Borel (pg. 26) | |
2.1 Measurable Functions and Random Variables (pg. 35) | |
2.2 Distribution Laws (pg. 42) | |
2.3 Lebesgue Integral (pg. 46) | |
2.4 Convergence of Integrals (pg. 55) | |
2.5 Integration Tools (pg. 57) | |
2.6 The Inverse of an Increasing Function (pg. 66) | |
3.1 Quasi-invariance of the Gaussian Distribution under Translation (pg. 69) | |
3.2 Moment-Generating Functions, Laplace, and Fourier Transforms (pg. 72) | |
3.3 Conditioning and Independence (pg. 76) | |
3.4 Multivariate Gaussian Distribution (pg. 87) | |
3.5 Hermite–Gauss Quadratures (pg. 92) | |
4.1 Types of Convergence for Sequences of Random Variables (pg. 97) | |
4.2 Uniform Integrability (pg. 103) | |
4.3 Sequences of Independent Random Variables and Events (pg. 105) | |
4.4 Law of Large Numbers and the Central Limit Theorem (pg. 108) | |
5.1 Motivation (pg. 113) | |
5.2 Layer Cake Formulas (pg. 114) | |
5.3 The Antithetic Variates Method (pg. 117) | |
5.4 The Importance Sampling Method (pg. 119) | |
5.5 The Acceptance–Rejection Method (pg. 120) | |
6.1 Information Structure (pg. 124) | |
6.2 Risk Preferences (pg. 126) | |
6.3 The Multiperiod Endowment Economy (pg. 137) | |
6.4 General Equilibrium (pg. 144) | |
6.5 The Two Fundamental Theorems of Asset Pricing (pg. 150) | |
6.6 From Stochastic Discount Factors to Equivalent Measures and Local Martingales (pg. 155) | |
7.1 Basic Concepts and Definitions (pg. 161) | |
7.2 Predictable Compensators (pg. 168) | |
7.3 Fundamental Inequalities and Convergence (pg. 170) | |
8.1 General Properties and Definitions (pg. 176) | |
8.2 Limit of the Binomial Asset Pricing Model (pg. 182) | |
8.3 Construction of Brownian Motion and First Properties (pg. 186) | |
8.4 The Wiener Measure (pg. 189) | |
8.5 Filtrations, Stopping Times, and Such (pg. 191) | |
8.6 Brownian Filtrations (pg. 206) | |
8.7 Total Variation (pg. 208) | |
8.8 Quadratic Variation (pg. 211) | |
8.9 Brownian Sample Paths Are Nowhere Differentiable (pg. 213) | |
8.10 Some Special Features of Brownian Sample Paths (pg. 215) | |
9.1 Definitions and First Properties (pg. 221) | |
9.2 Poisson Process and First Encounter with Lévy Processes (pg. 225) | |
9.3 Regularity of Paths, Optional Stopping, and Convergence (pg. 227) | |
9.4 Doob–Meyer Decomposition (pg. 237) | |
9.5 Local Martingales and Semimartingales (pg. 240) | |
9.6 The Space of (pg. 248) | |
9.7 The Binomial Asset Pricing Model Revisited (pg. 252) | |
10.1 Basic Examples and Intuition (pg. 258) | |
10.2 Stochastic Integrals with Respect to Continuous Local Martingales (pg. 262) | |
10.3 Stochastic Integrals with Respect to Continuous Semimartingales (pg. 271) | |
10.4 Itô’s Formula (pg. 273) | |
10.5 Stochastic Integrals with Respect to Brownian Motion (pg. 275) | |
10.6 Girsanov’s Theorem (pg. 281) | |
10.7 Local Times and Tanaka’s Formula (pg. 285) | |
10.8 Reflected Brownian Motion (pg. 290) | |
11.1 An Example (pg. 295) | |
11.2 Strong and Weak Solutions (pg. 296) | |
11.3 Existence of Solutions (pg. 307) | |
11.4 Linear Stochastic Differential Equations (pg. 315) | |
11.5 Some Common Diffusion Models Used in Asset Pricing (pg. 319) | |
12.1 Feynman–Kac Formula (pg. 325) | |
12.2 Fokker–Planck Equation (pg. 331) | |
13.1 Basic Concepts and Definitions (pg. 337) | |
13.2 Trading Strategy and Wealth Dynamics (pg. 345) | |
13.3 Equivalent Local Martingale Measures (pg. 348) | |
13.4 The Two Fundamental Theorems of Asset Pricing (pg. 352) | |
14.1 Résumé of Malliavin Calculus (pg. 357) | |
14.2 European-Style Contingent Claims (pg. 360) | |
14.3 The Martingale Solution to Merton’s Problem (pg. 366) | |
14.4 American-Style Contingent Claims (pg. 370) | |
14.5 Put–Call Symmetry and Foreign Exchange Options (pg. 378) | |
14.6 Exchange Options (pg. 380) | |
14.7 Stochastic Volatility Models (pg. 382) | |
14.8 Dupire’s Formula (pg. 394) | |
15.1 Martingales, Local Martingales, and Semimartingales with Jumps (pg. 397) | |
15.2 Stochastic Integrals with Respect to Semimartingales with Jumps (pg. 409) | |
15.3 Quadratic Variation and Itô’s Formula (pg. 417) | |
16.1 Poisson Random Measures (pg. 425) | |
16.2 Lévy Processes (pg. 433) | |
16.3 Stochastic Integrals with Respect to Lévy Processes (pg. 439) | |
16.4 Stochastic Exponents (pg. 444) | |
16.5 Change of Measure and Removal of the Drift (pg. 447) | |
16.6 Lévy–Itô Diffusions (pg. 452) | |
16.7 An Asset Pricing Model with Jumps in the Returns (pg. 456) | |
17.1 The Moon-Landing Problem (pg. 464) | |
17.2 Principle of Dynamic Programming and the HJB Equation (pg. 465) | |
17.3 Some Variations of the PDP and the HJB Equation (pg. 474) | |
18.1 Merton’s Problem with Intertemporal Consumption and No Rebalancing Costs (pg. 481) | |
18.2 Merton’s Problem with Intertemporal Consumption and Rebalancing Costs (pg. 490) | |
18.3 Real Options (pg. 502) | |
18.4 The Exercise Boundary for American Calls and Puts (pg. 510) | |
18.5 Corporate Debt, Equity, Dividend Policy, and the Modigliani–Miller Proposition (pg. 517) | |
B.1 Working with Market Data (pg. 541) | |
B.2 Simulation of Multivariate Gaussian Laws (pg. 543) | |
B.3 Numerical Program for American-Style Call Options (pg. 546) |
Instructors Only | |
---|---|
You must have an instructor account and submit a request to access instructor materials for this book.
|
eTextbook
Go paperless today! Available online anytime, nothing to download or install.
Features
|