Evaluating Portfolio Value-at-Risk Using Semi-Parametric GARCH Models
32 Pages Posted: 20 Jan 2005
Date Written: 28 2009 1,
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: multivariate GARCH, semi-parametric estimation, value-at-risk, asset allocation
JEL Classification: C53, M, G3, G11, C14, C22
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