Simulation Techniques in Financial Risk Management

Praise for the First Edition

" a nice, self–contained introduction to simulation and computational techniques in finance "

        Mathematical Reviews

Simulation Techniques in Financial Risk Management, Second Edition takes a unique approach to the field of simulations by focusing on techniques necessary in the fields of finance and risk management. Thoroughly updated, the new edition expands on several key topics in these areas and presents many of the recent innovations in simulations and risk management, such as advanced option pricing models beyond the Black–Scholes paradigm, interest rate models, MCMC methods including stochastic volatility models simulations, model assets and model–free properties, jump diffusion, and state space modeling. The Second Edition features also features:

Updates to primary software used throughout the book, Microsoft Office® Excel® VBA New topical coverage on multiple assets, model–free properties, and related models More than 300 exercises at the end of each chapter, with select answers in the appendix, to help readers apply new concepts and test their understanding Extensive use of examples to illustrate how to use simulation techniques in risk management Practical case studies, such as the pricing of exotic options; simulations of Greeks in hedging; and the use of Bayesian ideas to assess the impact of jumps, so readers can reproduce the results of the studies A related website with additional solutions to problems in the text, and Excel VBA and S–Plus computer code for many of the examples within the book
Simulation Techniques in Financial Risk Management, Second Edition is an invaluable resource for risk managers in the financial and actuarial industries as well as a useful reference for readers interested in learning how to better gauge risk and make more informed decisions. The book is also an excellent textbook for upper–undergraduate and graduate–level courses in simulation and risk management.

Ngai Hang Chan, PhD, is Choh–Min Li Chair Professor of Statistics of the Department of Statistics at The Chinese University of Hong Kong. An elected Fellow of the Institute of Mathematical Statistics and the American Statistical Association, Professor Chan is also the co–editor and associate editor of 8 journals and author of Time Series: Applications to Finance with R and S–Plus, Second Edition and Handbook of Financial Risk Management: Simulations and Case Studies, both also published by Wiley. His research interests include statistical finance, risk management, time series, econometrics, and stochastic modeling.

Hoi–Ying Wong, PhD, is Professor in the Risk Management Science Program of the Department of Statistics at The Chinese University of Hong Kong. Professor Wong is also associate editor of one journal and the author of Handbook of Financial Risk Management: Simulations and Case Studies, also published by Wiley. His research interests include derivatives pricing, interest rate modeling, financial risk management, and statistical finance.

Ngai Hang Chan, PhD, is Choh–Min Li Chair Professor of Statistics of the Department of Statistics at The Chinese University of Hong Kong. An elected Fellow of the Institute of Mathematical Statistics and the American Statistical Association, Professor Chan is also the co–editor and associate editor of 8 journals and author of Time Series: Applications to Finance with R and S–Plus, Second Edition and Handbook of Financial Risk Management: Simulations and Case Studies, both also published by Wiley. His research interests include statistical finance, risk management, time series, econometrics, and stochastic modeling.

Hoi–Ying Wong, PhD, is Professor in the Risk Management Science Program of the Department of Statistics at The Chinese University of Hong Kong. Professor Wong is also associate editor of one journal and the author of Handbook of Financial Risk Management: Simulations and Case Studies, also published by Wiley. His research interests include derivatives pricing, interest rate modeling, financial risk management, and statistical finance.