Evaluating portfolio Value-at-Risk using semi-parametric GARCH models

Rombouts, Jeroen;Verbeek, Marno
(2009) Quantitative Finance — Vol. 9, n° 6, p. 737-745 (2009)

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  • Rombouts, JeroenUCLouvain
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  • Verbeek, Marno
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Abstract
In this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes. Examining the within-sample VaRs of a set of given portfolios shows that the semi-parametric model performs uniformly well, while parametric models in several cases have unacceptable failure rates. Interestingly, distributional assumptions appear to have a much larger impact on the performance of the VaR estimates than the particular parametric specification chosen for the GARCH equations.
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Rombouts, J., & Verbeek, M. (2009). Evaluating portfolio Value-at-Risk using semi-parametric GARCH models. Quantitative Finance, 9(6), 737-745. https://doi.org/10.1080/14697680902785284 (Original work published 2009)