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A comparison of extreme value theory approaches for determining value at risk

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Brooks, C., Clare, A. D., Dalle Molle, J. W. and Persand, G. (2005) A comparison of extreme value theory approaches for determining value at risk. Journal of Empirical Finance, 12 (2). pp. 339-352. ISSN 0927-5398

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To link to this article DOI: 10.1016/j.jempfin.2004.01.004

Abstract/Summary

This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > ICMA Centre
ID Code:20555
Uncontrolled Keywords:Bootstrap; Value at risk (VaR); Generalised Pareto Distribution; Parametric; Semi-nonparametric and small sample bias corrected tail index estimators; GARCH models
Publisher:Elsevier

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