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Stochastic Simulation and Applications in Finance with MATLAB Programs
explains the fundamentals of Monte Carlo simulation techniques, their use in the
numerical resolution of stochastic differential equations and their current
applications in finance. Building on an integrated approach, it provides a
pedagogical treatment of the need-to-know materials in risk management and
financial engineering.
The book takes readers through the basic concepts, covering the most recent
research and problems in the area, including: the quadratic re-sampling
technique, the Least Squared Method, the dynamic programming and Stratified
State Aggregation technique to price American options, the extreme value
simulation technique to price exotic options and the retrieval of volatility
method to estimate Greeks. The authors also present modern term structure of
interest rate models and pricing swaptions with the BGM market model, and give a
full explanation of corporate securities valuation and credit risk based on the
structural approach of Merton. Case studies on financial guarantees illustrate
how to implement the simulation techniques in pricing and hedging.
The book also includes an accompanying CD-ROM which provides MATLAB programs
for the practical examples and case studies, which will give the reader
confidence in using and adapting specific ways to solve problems involving
stochastic processes in finance.
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