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A conditional-SGT-VaR approach with alternative GARCH models

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Abstract

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.

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Authors and Affiliations

  1. Department of Economics & Finance, Zicklin School of Business, Baruch College, CUNY, 55 Lexington Avenue, Box B10-225, New York, NY, 10010, USA

    Turan G. Bali (Professor of Finance)

  2. Aristotle’s University of Thessaloniki, Greece and Rutgers University, School of Business, 227 Penn Street, Camden, NJ, 08102, USA

    Panayiotis Theodossiou

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  1. Turan G. Bali
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  2. Panayiotis Theodossiou
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Correspondence to Turan G. Bali.

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Bali, T.G., Theodossiou, P. A conditional-SGT-VaR approach with alternative GARCH models. Ann Oper Res 151, 241–267 (2007). https://doi.org/10.1007/s10479-006-0118-4

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