本书中介绍了蒙特卡罗方法在金融中的用途，并且将模拟用作呈现金融工程中模型和思想的工具。本书大致分为三个部分。**部分介绍了蒙特卡罗方法的基本原理，衍生定价基础以及金融工程中一些*重要模型的实现。第二部分描述了如何改进模拟**度和效率。*后的第三部分讲述了几个特别的论题：价格敏感度估计，美式期权定价以及金融投资组合中的市场风险和信贷风险评估。

1 Foundations
1.1 Principles of Monte Carlo
1.1.1 Introduction
1.1.2 First Examples
1.1.3 Efficiency of Simulation Estimators
1.2 Principles of Derivatives Pricing
1.2.1 Pricing and Replication
1.2.2 Arbitrage and Risk-Neutral Pricing
1.2.3 Change of Numeraire
1.2.4 The Market Price of Risk
2 Generating Random Numbers and Random Variables
2.1 Random Number Generation
2.1.1 General Considerations
2.1.2 Linear Congruential Generators
2.1.3 Implementation of Linear Congruential Generators
2.1.4 Lattice Structure
2.1.5 Combined Generators and Other Methods
2.2 General Sampling Methods
2.2.1 Inverse Transform Method
2.2.2 Acceptance-Rejection Method
2.3 Normal Random Variables and Vectors
2.3.1 Basic Properties
2.3.2 Generating Univariate Normals
2.3.3 Generating Multivariate Normals
3 Generating Sample Paths
3.1 Brownian Motion
3.1.1 One Dimension
3.1.2 Multiple Dimensions
3.2 Geometric Brownian Motion
3.2.1 Basic Properties
3.2.2 Path-Dependent Options
3.2.3 Multiple Dimensions
3.3 Gaussian Short Rate Models
3.3.1 Basic Models and Simulation
3.3.2 Bond Prices
3.3 Multifactor Models
3.4 Square-Root Diffusions
3.4.1 Transition Density
3.4.2 Sampling Gamma and Poisson
3.4.3 Bond Prices
3.4.4 Extensions
3.5 Processes with Jumps
3.5.1 A Jump-Diffusion Model
3.5.2 Pure-Jump Processes
3.6 Forward Rate Models: Continuous Rates
3.6.1 The HJM Framework
3.6.2 The Discrete Drift
3.6.3 Implementation
3.7 Forward Rate Models: Simple Rates
3.7.1 LIBOR Market Model Dynamics
3.7.2 Pricing Derivatives
3.7.3 Simulation
3.7.4 Volatility Structure and Calibration
4 Variance Reduction Techniques
4.1 Control Variates
4.1.1 Method and Examples
4.1.2 Multiple Controls
4.1.3 Small-Sample Issues
4.1.4 Nonlinear Controls
4.2 Antithetic Variates
4.3 Stratified Sampling
4.3.1 Method and Examples
4.3.2 Applications
4.3.3 Poststratification
4.4 Latin Hypercube Sampling
4.5 Matching Underlying Assets
4.5.1 Moment Matching Through Path Adjustments
4.5.2 Weighted Monte Carlo
4.6 Importance Sampling
4.6.1 Principles and First Examples
4.6.2 Path-Dependent Options
4.7 Concluding Remarks
5 Quasi-Monte Carlo
6 Discretization Methods
7 Estimating Sensitivities
8 Pricing American Options
9 Applications in Risk Management
A Appendix: Convergence and Confidence Intervals
B Appendix: Results from Stochastic Calculus
C Appendix: The Term Structure of Interest Rates
References
Index

“……我鼓励对金融学中蒙特卡罗方法有兴趣的每一个人都阅读此书。这本书写得很出色，并且配有精选的参考书目和一个有帮助的索引，确实值得购买。”.
——Ralf Werner，OR Spectrum Operations Research Spectrum，Issue 27，2005
“本书的出版是计算金融学的一件大事。多年来，蒙特卡罗方法成功地应用于解决各式各样的金融数学问题。通过本书的出版，作者应为将这些应用提升到一个新水平的这次不错的尝试而得到更高的声誉。……”...
——A Zhigljavsky，Journal of the Operational Research Society，Vol．57，2006