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

Jeroen Rombouts and Marno Verbeek

Quantitative Finance, 2009, vol. 9, issue 6, 737-745

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: GARCH models; Multivariate volatility; Risk management; Time series analysis (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (9)

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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 (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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DOI: 10.1080/14697680902785284

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