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Evaluating effects of excess kurtosis on VaR estimates: Evidence for international stock indices

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Author Info
J. Baixauli ()
Susana Alvarez ()
Abstract

The calculus of VaR involves dealing with the confidence level, the time horizon and the true underlying conditional distribution function of asset returns. In this paper, we shall examine the effects of using a specific distribution function that fits well the low-tail data of the observed distribution of asset returns on the accuracy of VaR estimates. In our analysis, we consider some distributional forms characterized by capturing the excess kurtosis characteristic of stock return distributions and we compare their performance using some international stock indices. Copyright Springer Science + Business Media, LLC 2006

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File URL: http://hdl.handle.net/10.1007/s11156-006-8541-9
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Publisher Info
Article provided by Springer in its journal Review of Quantitative Finance and Accounting.

Volume (Year): 27 (2006)
Issue (Month): 1 (August)
Pages: 27-46
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Handle: RePEc:kap:rqfnac:v:27:y:2006:i:1:p:27-46

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Related research
Keywords: Value at risk; Excess kurtosis; Low-tail behaviour; Nonparametric goodness-of-fit tests; Parametric bootstrap;

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  9. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
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  1. In Kim & In-Seok Baek & Jaesun Noh & Sol Kim, 2007. "The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 29(1), pages 69-110, July. [Downloadable!] (restricted)
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