The Extreme Value Theory as a Tool to Measure Market Risk
AbstractAssessing the extreme events is crucial in financial risk management. All risk managers and financial institutions want to know the risk of their portfolio under rare events scenarios. We illustrate a multivariate market risk estimating method which employs Monte Carlo simulations to estimate Value-at-Risk (VaR) for a portfolio of 4 stock exchange indexes from Central Europe. The method uses the non-parametric empirical distribution to capture small risks and the parametric Extreme Value theory to capture large and rare risks. We compare estimates of this method with historical simulation and variance-covariance method under low and high volatility samples of data. In general historical simulation method overestimates the VaR for extreme events, while variance-covariance underestimates it. The method that we illustrate gives a result in between because it considers historical performance of the stocks and also corrects for the heavy tails of the distribution. We conclude that the estimate method that we illustrate here is useful in estimating VaR for extreme events, especially for high volatility times.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies in its series Working Papers IES with number 2011/26.
Date of creation: Jul 2011
Date of revision: Jul 2011
Value-at-Risk; Extreme Value Theory; copula.;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-08-02 (All new papers)
- NEP-BAN-2011-08-02 (Banking)
- NEP-ECM-2011-08-02 (Econometrics)
- NEP-RMG-2011-08-02 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lenka Herrmannova).
If references are entirely missing, you can add them using this form.