The Zurich Workshop on Quantitative Risk
Management
Venue and Time:
Federal Institute of Technology (ETH ),
Zurich
Lecture Theatre HG D3.2
Wednesday-Friday, October 2-4,
2002
Workshop Presenters:
Prof.
Alexander McNeil , ETH Zurich
Prof. Rüdiger Frey ,
University of Leipzig
Special invited lecture: Prof. Paul Embrechts , ETH
Zurich
See more
information about workshop presenters including biographies.
Objective:
Financial risk management confronts us with a real world of
rapidly fluctuating values, heavy-tailed risks and complex interdependencies,
which forces us to go beyond standard statistical models and simplifying
assumptions of normality to develop more sophisticated methodology. This course
aims to familiarize practitioners of risk management with the quantitative tools
necessary for a sound modelling of financial risks. The main technical issues
are volatility, extreme values and correlation
or dependence.
The course focuses on the application of
advanced statistical methodology to real world risk management problems in the
area of market risk , credit risk, and occasionally
operational risk. Advanced quantitative methodology will be presented clearly
and accessibly. Moreover, we will illustrate ideas with practical sessions
using S-Plus.
Course Contents:
- The Basics of Quantitative Risk Management
- financial risks and losses, risk measures, VaR, expected shortfall or
conditional VaR, risk factors and mappings, delta-gamma approximations for
derivatives
- Standard Statistical Methods
- variance-covariance, historical simulation, Monte Carlo, limits of
standard methods
- Fundamentals of Modelling Dependent Risks
- basic multivariate statistics, multivariate normal distribution,
multivariate normal mixture models, elliptical distributions, hyperbolic
distributions
- Modelling Financial Time Series
- basic time series concepts, review of ARMA models, empirical properties
(stylized facts) of financial time series, arguments for stochastic
volatility, ARCH and GARCH models
- Basic Topics in Extreme Value Theory
- maxima and worst case losses, extreme value distributions, generalised
Pareto distribution (GPD), peaks-over -thresholds (POT) method, modelling
excess losses and heavy tails, estimation of quantiles (VaR) and expected
shortfall
- Advanced Topics in EVT and Time Series
- Outperforming historical simulation with EVT, EVT for dependent time
series, Hill estimation, EVT in a stochastic volatility framework
- Copulas, Correlation and Dependent Extreme Values
- introduction to copulas, useful copula families, drawbacks and fallacies
of ordinary correlation, rank correlation, tail dependence, bounds for VaR
of dependent risks
- Multivariate Models: Calibration and Simulation
- efficient correlation estimation, tests for multivariate normality and
ellipticity, fitting copulas to data, Monte Carlo simulation of dependent
risk factors
- Portfolio Credit Risk: Models
- models for dependent defaults (latent variable models and mixture
models), industry examples(KMV/Moodys, CreditMetrics, CreditRisk+), mapping
between models
- Portfolio Credit Risk: Calibration and Model Risk
- understanding sources of model risk, the role of copulas in standard
models, statistical issues in default modelling, implications for basket
credit derivatives
- Advanced Multivariate Market Risk Models
- multivariate risk factor properties, multivariate time series models,
multivariate GARCH models, multivariate EVT
Examples with S-PLUS and S+FinMetrics
We will reinforce these ideas with
practical sessions using S-PLUS and S+FinMetrics . S-PLUS is the powerful
data analysis environment of Insightful
and S+FinMetrics
is a new toolkit for the analysis of financial data, which will be launched in
Summer 2002. S+FinMetrics will undoubtedly be the most advanced available
toolkit for the statistical and econometric analysis of financial time series
data.
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