Simulation Techniques in Financial Risk Management /
Ngai Hang Chan and Hoi Ying Wong
- 2nd ed.
- New Jersey Wiley 2015
- xviii, 205 p., 24 cm.
- Wiley Series in Statistics in Practice .
Bookwell/1268/180118/114.95$
This is the introductory chapter of the book, which discusses some of the features of simulations. One can see that simulation is a powerful tool for analyzing complex situations. The book also explains different techniques in simulations and their applications in risk management. Practical implementation of risk management methods usually requires substantial computations. The computational requirement comes from calculating summaries, such as value-at-risk, hedging ratio, market β, and so on. Therefore, many of the simulation techniques developed by statisticians for summarizing data are equally applicable in the risk management context. The book gives some typical examples. In risk management, one often encounters stochastic processes such as Brownian motions, geometric Brownian motion, and lognormal distributions. Although some of these entities may be understood analytically, quantities derived from them are often less tractable.