Annals of Operations Research

, Volume 151, Issue 1, pp 241–267

A conditional-SGT-VaR approach with alternative GARCH models


DOI: 10.1007/s10479-006-0118-4

Cite this article as:
Bali, T.G. & Theodossiou, P. Ann Oper Res (2007) 151: 241. doi:10.1007/s10479-006-0118-4


This paper proposes a conditional technique for the estimation of VaR and expected shortfall measures based on the skewed generalized t (SGT) distribution. The estimation of the conditional mean and conditional variance of returns is based on ten popular variations of the GARCH model. The results indicate that the TS-GARCH and EGARCH models have the best overall performance. The remaining GARCH specifications, except in a few cases, produce acceptable results. An unconditional SGT-VaR performs well on an in-sample evaluation and fails the tests on an out-of-sample evaluation. The latter indicates the need to incorporate time-varying mean and volatility estimates in the computation of VaR and expected shortfall measures.


GARCH models Skewed generalized t distribution Conditional value at risk Expected shortfall 

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  1. 1.Department of Economics & Finance, Zicklin School of BusinessBaruch CollegeNew YorkUSA
  2. 2.Aristotle’s University of Thessaloniki, Greece and Rutgers University, School of BusinessCamdenUSA

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