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