Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management
AbstractRecent 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 holds 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 associated 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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Bibliographic InfoPaper provided by Wharton School Center for Financial Institutions, University of Pennsylvania in its series Center for Financial Institutions Working Papers with number 98-10.
Date of creation: Apr 1998
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- Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-081, New York University, Leonard N. Stern School of Business-.
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- Einmahl, J.H.J., 1990. "The empirical distribution function as a tail estimator," Open Access publications from Tilburg University urn:nbn:nl:ui:12-142062, Tilburg University.
- 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.
- Engle, Robert F & Gonzalez-Rivera, Gloria, 1991. "Semiparametric ARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 345-59, October.
- Francis X. Diebold & Jose A. Lopez, 1995.
"Modeling volatility dynamics,"
9522, Federal Reserve Bank of New York.
- Koedijk, C.G. & Schafgans, M.M.A. & Vries, C.G. de, 1990. "The tail index of exchange rate returns," Open Access publications from Tilburg University urn:nbn:nl:ui:12-3108722, Tilburg University.
- Jon Danielsson & Casper G. de Vries, 1998.
"Beyond the Sample: Extreme Quantile and Probability Estimation,"
FMG Discussion Papers
dp298, Financial Markets Group.
- Jón Daníelsson & Casper G. de Vries, 1998. "Beyond the Sample: Extreme Quantile and Probability Estimation," Tinbergen Institute Discussion Papers 98-016/2, Tinbergen Institute.
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