Value at Risk Estimation for Heavy Tailed Distributions

The International Journal of Business and Finance Research, v. 8 (3) p. 109-125, 2014

17 Pages Posted: 12 Dec 2014

See all articles by Imed Gammoudi

Imed Gammoudi

University of Sousse

Lotfi BelKacem

University of Sousse - Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ)

Mohamed El Ghourabi

University of Tunis, Larodec

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Date Written: 2014

Abstract

The aim of this paper is to derive a coherent risk measure for heavy tailed GARCH processes using extreme value theory. For the proposed measure, the risk associated to a given portfolio is less than the sum of the stand-alone risks of its components. This measure which is value at risk (VaR), is the limiting result of an infinity shift of location and is less sensitive with respect to location change. Based on two international stock markets applications and an empirical backtesting procedure, the proposed VaR is found to be more accurate in all quantile levels.

Keywords: Risk Management, Extreme Value Theory, Non-linear Models, Backtesting, Stock Market Index

JEL Classification: C22, C58, G15

Suggested Citation

Gammoudi, Imed and BelKacem, Lotfi and El Ghourabi, Mohamed, Value at Risk Estimation for Heavy Tailed Distributions (2014). The International Journal of Business and Finance Research, v. 8 (3) p. 109-125, 2014. Available at SSRN: https://ssrn.com/abstract=2451712

Imed Gammoudi (Contact Author)

University of Sousse ( email )

rue Abdelaziz el Behi
Sousse, Sousse 4000
Tunisia

Lotfi BelKacem

University of Sousse - Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ) ( email )

Sousse
Tunisia

Mohamed El Ghourabi

University of Tunis, Larodec ( email )

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