Evaluating Portfolio Value-At-Risk Using Semi-Parametric GARCH Models

J.V.K. Rombouts and Marno Verbeek

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

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.

Keywords: asset allocation; multivariate GARCH; semi-parametric estimation; value-at-risk (search for similar items in EconPapers)
JEL-codes: C14 C22 C53 G11 G3 M (search for similar items in EconPapers)
Date: 2009-01-28
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Citations: View citations in EconPapers (9)

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https://repub.eur.nl/pub/1833/ERS-2004-107-FA.pdf (application/pdf)

Related works:
Working Paper: Evaluating portfolio value-at-risk using semi-parametric GARCH models (2009)
Working Paper: Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models (2005)
Working Paper: Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models (2004)
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