This unique resource provides simulation techniques for financial risk managers ensuring you become well versed in many recent innovations, including Gibbs sampling, the use of heavy-tailed distributions in VaR calculations, construction of volatility smile, and state space modeling. The authors illustrate key concepts with examples and case studies you can reproduce using either S-PLUS(r) or Visual Basic(r) and provide exercises so you can apply new concepts and test your knowledge. Simulation Techniques in Financial Risk Management is invaluable both as a resource for risk managers in the financial and actuarial industries and as a coursebook for upper-level undergraduate and graduate courses in simulation and risk management.
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NGAI HANG CHAN, PhD, is Chairman and Professor of Statistics of the Department of Statistics at The Chinese University of Hong Kong where he was formerly Director of the Risk Management Science Program. He is an elected Fellow of the Institute of Mathematical Statistics, the author of Time Series: Applications to Finance (Wiley), and is also the associate editor of six journals. His research interests include statistical finance, risk management, time series, econometrics, and stochastic modeling. HOI-YING WONG, PhD, is Assistant Professor in the Risk Management Science Program of the Department of Statistics at The Chinese University of Hong Kong. His research interests include derivatives pricing, interest rate modeling, financial risk management, and statistical finance.
A unique resource of simulation techniques designed for financial risk managers
Simulation Techniques in Financial Risk Management takes a unique approach to the field of simulations by focusing on techniques needed by practitioners in the financial and risk management industries. Key concepts are illustrated with extensive use of examples and case studies in finance and risk management; readers can then reproduce the results of the studies using either S-PLUS® or Visual Basic®.
The book consists of three parts:
Readers become well versed in many of the recent innovations in simulations and risk management, such as Gibbs sampling, the use of heavy-tailed distributions in VaR calculations, construction of volatility smile, and state space modeling. Exercises at the end of each chapter provide the opportunity for readers to apply new concepts and test their knowledge. Answers for selected exercises offer additional insights to help readers consolidate their understanding.
This text is an invaluable resource for risk managers in the financial and actuarial industries and will help them to better gauge risk and make more informed decisions. Moreover, it is recommended as a coursebook for upper-level undergraduate and graduate courses in simulation and risk management.
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