Financial Risk Forecasting: The Theory and Practice of Forecasting Market Risk with Implementation in R and MATLAB

Financial Risk Forecasting is a complete introduction topractical quantitative risk management, with a focus on marketrisk. Derived from the authors teaching notes and years spenttraining practitioners in risk management techniques, it bringstogether the three key disciplines of finance, statistics andmodeling (programming), to provide a thorough grounding in riskmanagement techniques.

Written by renowned risk expert Jon Danielsson, the book beginswith an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It thengoes on to present volatility forecasting with both univatiate andmultivatiate methods, discussing the various methods used byindustry, with a special focus on the GARCH family of models. Theevaluation of the quality of forecasts is discussed in detail.Next, the main concepts in risk and models to forecast risk arediscussed, especially volatility, value-at-risk and expectedshortfall. The focus is both on risk in basic assets such as stocksand foreign exchange, but also calculations of risk in bonds andoptions, with analytical methods such as delta-normal VaR andduration-normal VaR and Monte Carlo simulation. The book then moveson to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes byfocussing on the forecasting of risk in very large and uncommonevents with extreme value theory and considering the underlyingassumptions behind almost every risk model in practical use -that risk is exogenous - and what happens when thoseassumptions are violated.

Every method presented brings together theoretical discussionand derivation of key equations and a discussion of issues inpractical implementation. Each method is implemented in both MATLABand R, two of the most commonly used mathematical programminglanguages for risk forecasting with which the reader can implementthe models illustrated in the book.

The book includes four appendices. The first introduces basicconcepts in statistics and financial time series referred tothroughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the softwarepackages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing.

The book is accompanied by a website - www.financialriskforecasting.com- which features downloadable code as used in the book.