【英文原版书】Measuring Risk in Complex Stochastic Systems.pdf

Measuring Risk in
Complex Stochastic Systems
J. Franke, W. H¨ardle,G. Stahl
Empirical Volatility
Parameter Estimates

2
Preface
Complex dynamic processes of life and sciences generate risks that have to be taken. The
need for clear and distinctive definitions of different kinds of risks, adequate methods
and parsimonious models is obvious. The identification of important risk factors and
the quantification of risk stemming from an interplay between many risk factors is a
prerequisite for mastering the challenges of risk perception, analysis and management
essfully. The plexity of stochastic systems, especially in finance, have
catalysed the use of advanced statistical methods for these tasks.
The methodological approach to solving risk management tasks may, however, be under-
taken from many different angles. A financial institution may focus on the risk created
by the use of options and other derivatives in global financial processing, an auditor
will try to evaluate internal risk management models in detail, a mathematician may
be interested in analysing the involved nonlinearities or concentrate on extreme and
rare events of plex stochastic system, whereas a statistician may be interested
in model and variable selection, practical implementations and parsimonious modelling.
An economist may think about the possible impact of risk management tools in the
framework of efficient regulation of financial markets or efficient allocation of capital.
This book gives a diversified portfolio of these scenarios. We first present a set of papers
on credit risk management, and then focus on extreme value analysis. The Value at
Risk (VaR) concept is discussed in the next block of papers, followed by several articles
on change points. The papers were presented during a conference on Measuring Risk in
Complex Stochastic Systems that took place in Berlin on September 25th - 30th 1999.
The conference anised within the Seminar Berlin-Paris,