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

  • Rombouts, J.V.K.
  • Verbeek, M.J.C.M.

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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Paper provided by 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 in its series ERIM Report Series Research in Management with number ERS-2004-107-F&A.

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Date of creation: 28 Jan 2009
Date of revision:
Handle: RePEc:ems:eureri:1833
Contact details of provider: Postal: RSM Erasmus University & Erasmus School of Economics, PoBox 1738, 3000 DR Rotterdam
Phone: 31-10-408 1182
Fax: 31-10-408 9020
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  1. repec:fth:inseep:2000-05 is not listed on IDEAS
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