"Stochastic Simulation and Applications in Finance with Matlab Programs" begins by covering the basics of probability and statistics, which are essential to the understanding the later chapters on random processes and computational simulation techniques, it then goes on to discuss Monte Carlo simulations. In addition to the most commonly used techniques, the authors also cover the latest developments such as Markov Chain Monte Carlo and importance sampling methods, which are not discussed in other texts. The final part of the book covers random processes, stochastic differential equations and Brownian Bridges.This book features CD-ROM with examples and programs relating to end of chapter tests and examples and includes accompanying simulation programs in Matlab - a leading programming language commonly used in industry and academia. It covers the latest stochastic processes including American Bermudan Swaps and Markov Chain processes, not covered in other literature. It features case studies and examples from the financial industry as well as test exercises. It offers an in-depth, rigorous explanation of how to apply stochastic simulations to financial engineering problems. Each chapter starts with an introduction to the topic (assuming prior knowledge of linear algebra, differential calculus and programming) taking the reader through to the most advanced elements of each topic
