Book description
Financial Risk Forecasting
is a complete introduction to practical quantitative risk management,
with a focus on market risk. Derived from the authors teaching notes and
years spent training practitioners in risk management techniques, it
brings together the three key disciplines of finance, statistics and
modeling (programming), to provide a thorough grounding in risk
management techniques.
Written by renowned risk expert Jon Danielsson,
the book begins with an introduction to financial markets and market
prices, volatility clusters, fat tails and nonlinear dependence. It
then goes on to present volatility forecasting with both univatiate
and multivatiate methods, discussing the various methods used by
industry, with a special focus on the GARCH family of models. The
evaluation of the quality of forecasts is discussed in detail. Next,
the main concepts in risk and models to forecast risk are discussed,
especially volatility, value-at-risk and expected shortfall. The focus
is both on risk in basic assets such as stocks and foreign exchange,
but also calculations of risk in bonds and options, with analytical
methods such as delta-normal VaR and duration-normal VaR and Monte
Carlo simulation. The book then moves on to the evaluation of risk
models with methods like backtesting, followed by a discussion on
stress testing. The book concludes by focussing on the forecasting of
risk in very large and uncommon events with extreme value theory and
considering the underlying assumptions behind almost every risk model
in practical use - that risk is exogenous - and what happens when
those assumptions are violated.
Every method presented brings together theoretical discussion and
derivation of key equations and a discussion of issues in practical
implementation. Each method is implemented in both MATLAB and R, two
of the most commonly used mathematical programming languages for risk
forecasting with which the reader can implement the models illustrated
in the book.
The book includes four appendices. The first introduces basic
concepts in statistics and financial time series referred to
throughout the book. The second and third introduce R and MATLAB,
providing a discussion of the basic implementation of the software
packages. 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.
Jón Daníelsson has a PhD in the economics of
financial markets and is a reader in finance at the London School of
Economics. His research interests include financial stability, extreme
market movements, risk, market liquidity and financial crisis. He has
published extensively in both academic and practitioner journals, has
consulted with a variety of private sector and public institutions,
frequently gives executive education courses and has presented his
work in a number of universities and institutions. In addition, he has
been a frequent commentator of issues in financial markets in the
media, appearing on CNN, the BBC, and many other TV and radio
stations, with comments and op-ed pieces in newspapers like the
Financial Times.
