蒙特卡洛模拟和金融MONTE CARLO SIMULATION AND FINANCE chm umd 阿里云 下载 夸克云 pdf azw3 kindle

Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon.

This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.

Acknowledgments

Chapter 1 Introduction

Chapter 2 Some Basic Theory of Finance

　Introduction to Pricing: Single PeriodModels

　Multiperiod Models

　Determining the Process Bt

　Minimum Variance Portfolios and the Capital Asset Pricing Model

　Entropy: choosing a Q measure

　Models in Continuous Time

　Problems

Chapter 3 Basic Monte Carlo Methods

　Uniform Random Number Generation

　Apparent Randomness of Pseudo-Random Number Generators

　Generating Random Numbers from Non-Uniform Continuous Distributions

　Generating Random Numbers from Discrete Distributions

　Random Samples Associated with Markov Chains

　Simulating Stochastic Partial Differential Equations

　Problems

Chapter 4 Variance Reduction Techniques

　Introduction

　Variance reduction for one-dimensional Monte-Carlo Integration

　Problems

　Chapter 5 Simulating the value of Options

　Asian Options

　Pricing a Call option under stochastic interest rates

　Simulating Barrier and lookback options

　Survivorship Bias

　Problems

Chapter 6 Quasi- Monte Carlo Multiple Integration

　Introduction

　Theory of Low discrepancy sequences

　Examples of low discrepancy sequences

　Problems

Chapter 7 Estimation and Calibration

　Introduction

　Finding a Root

　Maximization of Functions

　MaximumLikelihood Estimation

　Using Historical Data to estimate the parameters in Diffusion Models

　Estimating Volatility

　Estimating Hedge ratios and Correlation Coefficients

　Problems

Chapter 8 Sensitivity Analysis, Estimating Derivatives and the Greeks

　Estimating Derivatives

　Infinitesimal Perturbation Analysis: Pathwise differentiation

　Calibrating aModel using simulations

　Problems

Chapter 9 Other Directions and Conclusions

　Alternative Models

　ARCH and GARCH

　Conclusions

Notes

References

Index

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作者简介：

　　DON L. McLEISH is Professor of Statistics and Actuarial Science at the University of Waterloo. His research has focused on probability, statistical methods and models in general, and their application to financial data, including wide-tail alternatives to the normal distribution and the consequences for derivatives and asset pricing. He has contributed to the application of Monte Carlo techniques, variance reduction, and stochastic calculus to problems in finance, and is cofounder of the University of Waterloo's Center for Advance Studies in Finance. McLeish is also coauthor, with C.G. Small, of The Theory and Application of Statistical Inference Functions and Hilbert Space Methods in Probability and Statistical Inference (Wiley).

书籍介绍

Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.