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http://ssrn.com/abstract=1504109
 
 

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Forecasting Expected Shortfall with a Generalized Asymmetric Student-T Distribution


Dongming Zhu


Peking University

John W. Galbraith


McGill University - Department of Economics; Center for Interuniversity Research and Analysis on Organization (CIRANO)

May 1, 2009

CIRANO - Scientific Publications Paper No. 2009s-24

Abstract:     
Financial returns typically display heavy tails and some skewness, and conditional variance models with these features often outperform more limited models. The difference in performance may be especially important in estimating quantities that depend on tail features, including risk measures such as the expected shortfall. Here, using a recent generalization of the asymmetric Student-t distribution to allow separate parameters to control skewness and the thickness of each tail, we fit daily financial returns and forecast expected shortfall for the S&P 500 index and a number of individual company stocks; the generalized distribution is used for the standardized innovations in a nonlinear, asymmetric GARCH-type model. The results provide empirical evidence for the usefulness of the generalized distribution in improving prediction of downside market risk of financial assets.

Number of Pages in PDF File: 19

Keywords: asymmetric distribution, expected shortfall, GARCH model

JEL Classification: C16, G10

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Date posted: November 12, 2009  

Suggested Citation

Zhu, Dongming and Galbraith, John W., Forecasting Expected Shortfall with a Generalized Asymmetric Student-T Distribution (May 1, 2009). CIRANO - Scientific Publications Paper No. 2009s-24. Available at SSRN: http://ssrn.com/abstract=1504109 or http://dx.doi.org/10.2139/ssrn.1504109

Contact Information

Dongming Zhu
Peking University ( email )
Beijing, 100871
China
John W. Galbraith (Contact Author)
McGill University - Department of Economics ( email )
1001 Sherbrooke St. W
Montreal, Quebec H3A 1G5
Canada
Center for Interuniversity Research and Analysis on Organization (CIRANO) ( email )
2020 rue University, 25th floor
Montreal H3C 3J7, Quebec
Canada
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