<p><br/>再发个，忘了从哪里搞来的了，论坛里可能有，姑且放这里吧</p><p>CHAPTER 1<br/>Black-Scholes and Pricing Fundamentals 1<br/>1.1 Forward Contracts 1<br/>1.2 Black-Scholes Partial Differential Equation 4<br/>1.3 Risk-Neutral Pricing 10<br/>1.4 Black-Scholes and Diffusion Process Implementation 17<br/>1.5 American Options 30<br/>1.6 Fundamental Pricing Formulas 33<br/>1.7 Change of Numeraire 35<br/>1.8 Girsanov’s Theorem 38<br/>1.9 The Forward Measure 41<br/>1.10 The Choice of Numeraire 42<br/>CHAPTER 2<br/>Monte Carlo Simulation 45<br/>2.1 Monte Carlo 45<br/>2.2 Generating Sample Paths and Normal Deviates 47<br/>2.3 Generating Correlated Normal Random Variables 50<br/>2.4 Quasi-Random Sequences 56<br/>2.5 Variance Reduction and Control Variate Techniques 67<br/>2.6 Monte Carlo Implementation 69<br/>2.7 Hedge Control Variates 76<br/>2.8 Path-Dependent Valuation 84<br/>2.9 Brownian Bridge Technique 92<br/>2.10 Jump-Diffusion Process and Constant Elasticity of<br/>Variance Diffusion Model 98<br/>2.11 Object-Oriented Monte Carlo Approach 102<br/>CHAPTER 3<br/>Binomial Trees 123<br/>3.1 Use of Binomial Trees 123<br/>3.2 Cox-Ross-Rubinstein Binomial Tree 131</p><p>3.3 Jarrow-Rudd Binomial Tree 132<br/>3.4 General Tree 133<br/>3.5 Dividend Payments 135<br/>3.6 American Exercise 137<br/>3.7 Binomial Tree Implementation 138<br/>3.8 Computing Hedge Statistics 140<br/>3.9 Binomial Model with Time-Varying Volatility 144<br/>3.10 Two-Variable Binomial Process 145<br/>3.11 Valuation of Convertible Bonds 150<br/>CHAPTER 4<br/>Trinomial Trees 165<br/>4.1 Use of Trinomial Trees 165<br/>4.2 Jarrow-Rudd Trinomial Tree 166<br/>4.3 Cox-Ross-Rubinstein Trinomial Tree 168<br/>4.4 Optimal Choice of λ 169<br/>4.5 Trinomial Tree Implementations 170<br/>4.6 Approximating Diffusion Processes with Trinomial Trees 174<br/>4.7 Implied Trees 178<br/>CHAPTER 5<br/>Finite-Difference Methods 183<br/>5.1 Explicit Difference Methods 183<br/>5.2 Explicit Finite-Difference Implementation 186<br/>5.3 Implicit Difference Method 191<br/>5.4 LU Decomposition Method 194<br/>5.5 Implicit Difference Method Implementation 196<br/>5.6 Object-Oriented Finite-Difference Implementation 202<br/>5.7 Iterative Methods 232<br/>5.8 Crank-Nicolson Scheme 235<br/>5.9 Alternating Direction Implicit Method 241<br/>CHAPTER 6<br/>Exotic Options 246<br/>6.1 Barrier Options 246<br/>6.2 Barrier Option Implementation 255<br/>6.3 Asian Options 258<br/>6.4 Geometric Averaging 258<br/>6.5 Arithmetic Averaging 260<br/>6.6 Seasoned Asian Options 261<br/>6.7 Lookback Options 262<br/>6.8 Implementation of Floating Lookback Option 265<br/>6.9 Implementation of Fixed Lookback Option 268</p><p>CHAPTER 7<br/>Stochastic Volatility 274<br/>7.1 Implied Volatility 274<br/>7.2 Volatility Skews and Smiles 276<br/>7.3 Empirical Explanations 283<br/>7.4 Implied Volatility Surfaces 284<br/>7.5 One-Factor Models 303<br/>7.6 Constant Elasticity of Variance Models 305<br/>7.7 Recovering Implied Volatility Surfaces 307<br/>7.8 Local Volatility Surfaces 309<br/>7.9 Jump-Diffusion Models 313<br/>7.10 Two-Factor Models 315<br/>7.11 Hedging with Stochastic Volatility 321<br/>CHAPTER 8<br/>Statistical Models 324<br/>8.1 Overview 324<br/>8.2 Moving Average Models 329<br/>8.3 Exponential Moving Average Models 331<br/>8.4 GARCH Models 334<br/>8.5 Asymmetric GARCH 337<br/>8.6 GARCH Models for High-Frequency Data 340<br/>8.7 Estimation Problems 353<br/>8.8 GARCH Option Pricing Model 354<br/>8.9 GARCH Forecasting 362<br/>CHAPTER 9<br/>Stochastic Multifactor Models 367<br/>9.1 Change of Measure for Independent Random Variables 368<br/>9.2 Change of Measure for Correlated Random Variables 370<br/>9.3 N-Dimensional Random Walks and Brownian Motion 371<br/>9.4 N-Dimensional Generalized Wiener Process 373<br/>9.5 Multivariate Diffusion Processes 374<br/>9.6 Monte Carlo Simulation of Multivariate Diffusion Processes 375<br/>9.7 N-Dimensional Lognormal Process 376<br/>9.8 Ito’s Lemma for Functions of Vector-Valued Diffusion Processes 388<br/>9.9 Principal Component Analysis 389<br/>CHAPTER 10<br/>Single-Factor Interest Rate Models 395<br/>10.1 Short Rate Process 398<br/>10.2 Deriving the Bond Pricing Partial Differential Equation 399<br/>10.3 Risk-Neutral Drift of the Short Rate 401<br/>10.4 Single-Factor Models 402</p><p>10.5 Vasicek Model 404<br/>10.6 Pricing Zero-Coupon Bonds in the Vasicek Model 411<br/>10.7 Pricing European Options on Zero-Coupon Bonds<br/>with Vasicek 420<br/>10.8 Hull-White Extended Vasicek Model 425<br/>10.9 European Options on Coupon-Bearing Bonds 429<br/>10.10 Cox-Ingersoll-Ross Model 431<br/>10.11 Extended (Time-Homogenous) CIR Model 436<br/>10.12 Black-Derman-Toy Short Rate Model 438<br/>10.13 Black’s Model to Price Caps 439<br/>10.14 Black’s Model to Price Swaptions 443<br/>10.15 Pricing Caps, Caplets, and Swaptions with Short Rate Models 448<br/>10.16 Valuation of Swaps 455<br/>10.17 Calibration in Practice 457<br/>CHAPTER 11<br/>Tree-Building Procedures 467<br/>11.1 Building Binomial Short Rate Trees for Black, Derman, and Toy 468<br/>11.2 Building the BDT Tree Calibrated to the Yield Curve 471<br/>11.3 Building the BDT Tree Calibrated to the Yield and<br/>Volatility Curve 476<br/>11.4 Building a Hull-White Tree Consistent with the Yield Curve 485<br/>11.5 Building a Lognormal Hull-White (Black-Karasinski) Tree 495<br/>11.6 Building Trees Fitted to Yield and Volatility Curves 501<br/>11.7 Vasicek and Black-Karasinski Models 509<br/>11.8 Cox-Ingersoll-Ross Implementation 515<br/>11.9 A General Deterministic-Shift Extension 520<br/>11.10 Shift-Extended Vasicek Model 524<br/>11.11 Shift-Extended Cox-Ingersoll-Ross Model 541<br/>11.12 Pricing Fixed Income Derivatives with the Models 549<br/>CHAPTER 12<br/>Two-Factor Models and the Heath-Jarrow-Morton Model 554<br/>12.1 The Two-Factor Gaussian G2++ Model 556<br/>12.2 Building a G2++ Tree 563<br/>12.3 Two-Factor Hull-White Model 575<br/>12.4 Heath-Jarrow-Morton Model 579<br/>12.5 Pricing Discount Bond Options with Gaussian HJM 584<br/>12.6 Pricing Discount Bond Options in General HJM 585<br/>12.7 Single-Factor HJM Discrete-State Model 586<br/>12.8 Arbitrage-Free Restrictions in a Single-Factor Model 591<br/>12.9 Computation of Arbitrage-Free Term Structure Evolutions 595<br/>12.10 Single-Factor HJM Implementation 598<br/>12.11 Synthetic Swap Valuation 606</p><p>12.12 Two-Factor HJM Model 612<br/>12.13 Two-Factor HJM Model Implementation 616<br/>12.14 The Ritchken and Sankarasubramanian Model 620<br/>12.15 RS Spot Rate Process 623<br/>12.16 Li-Ritchken-Sankarasubramanian Model 624<br/>12.17 Implementing an LRS Trinomial Tree 626<br/>CHAPTER 13<br/>LIBOR Market Models 630<br/>13.1 LIBOR Market Models 632<br/>13.2 Specifications of the Instantaneous Volatility of Forward Rates 636<br/>13.3 Implementation of Hull-White LIBOR Market Model 640<br/>13.4 Calibration of LIBOR Market Model to Caps 641<br/>13.5 Pricing Swaptions with Lognormal Forward-Swap Model 642<br/>13.6 Approximate Swaption Pricing with Hull-White Approach 646<br/>13.7 LFM Formula for Swaption Volatilities 648<br/>13.8 Monte Carlo Pricing of Swaptions Using LFM 650<br/>13.9 Improved Monte Carlo Pricing of Swaptions with a<br/>Predictor-Corrector 655<br/>13.10 Incompatibility between LSM and LSF 663<br/>13.11 Instantaneous and Terminal Correlation Structures 665<br/>13.12 Calibration to Swaption Prices 669<br/>13.13 Connecting Caplet and S × 1-Swaption Volatilities 670<br/>13.14 Including Caplet Smile in LFM 673<br/>13.15 Stochastic Extension of LIBOR Market Model 677<br/>13.16 Computing Greeks in Forward LIBOR Models 688<br/>CHAPTER 14<br/>Bermudan and Exotic Interest Rate Derivatives 710<br/>14.1 Bermudan Swaptions 710<br/>14.2 Implementation for Bermudan Swaptions 713<br/>14.3 Andersen’s Method 718<br/>14.4 Longstaff and Schwartz Method 721<br/>14.5 Stochastic Mesh Method 730<br/>14.6 Valuation of Range Notes 733<br/>14.7 Valuation of Index-Amortizing Swaps 742<br/>14.8 Valuation of Trigger Swaps 752<br/>14.9 Quanto Derivatives 754<br/>14.10 Gaussian Quadrature 760<br/>APPENDIX A<br/>Probability Review 771<br/>A.1 Probability Spaces 771<br/>A.2 Continuous Probability Spaces 773</p><p>A.3 Single Random Variables 773<br/>A.4 Binomial Random Variables 774<br/>A.5 Normal Random Variables 775<br/>A.6 Conditional Expectations 776<br/>A.7 Probability Limit Theorems 778<br/>A.8 Multidimensional Case 779<br/>A.9 Dirac’s Delta Function 780<br/>APPENDIX B<br/>Stochastic Calculus Review 783<br/>B.1 Brownian Motion 783<br/>B.2 Brownian Motion with Drift and Volatility 784<br/>B.3 Stochastic Integrals 785<br/>B.4 Ito’s Formula 788<br/>B.5 Geometric Brownian Motion 789<br/>B.6 Stochastic Leibnitz Rule 789<br/>B.7 Quadratic Variation and Covariation 790<br/>References 793<br/>About the CD-ROM 803<br/>GNU General Public License 807<br/>Index 813</p>