Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management
Recent literature has trumpeted the claim that extreme value theory (EVT) holds promise for accurate estimation of extreme quantiles and tail probabilities of financial asset returns, and hence hold promise for advances in the management of extreme financial risks. Our view, based on a disinterested assessment of EVT from the vantage point of financial risk management, is that the recent optimism is partly appropriate but also partly exaggerated, and that at any rate much of the potential of EVT remains latent. We substantiate this claim by sketching a number of pitfalls associate with use of EVT techniques. More constructively, we show how certain of the pitfalls can be avoided, and we sketch a number of explicit research directions that will help the potential of EVT to be realized.
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|Date of creation:||Mar 1998|
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- Francis X. Diebold & Jose A. Lopez, 1995.
"Modeling volatility dynamics,"
9522, Federal Reserve Bank of New York.
- Jon Danielsson & Casper G. de Vries, 1998. "Beyond the Sample: Extreme Quantile and Probability Estimation," FMG Discussion Papers dp298, Financial Markets Group.
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- repec:ner:tilbur:urn:nbn:nl:ui:12-142062 is not listed on IDEAS
- repec:ner:tilbur:urn:nbn:nl:ui:12-3108722 is not listed on IDEAS
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Einmahl, J.H.J., 1990. "The empirical distribution function as a tail estimator," Other publications TiSEM 08014dbd-2d84-43e5-ad47-7, Tilburg University, School of Economics and Management.
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