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Two-Step Methods in VaR Prediction and the Importance of Fat Tails
Company: Quantitative Finance
Company Url: Click here to open
Year Of Publication: 2014
Month Of Publication: August
Resource Link: Click here to open
Download Count: 0
View Count: 1320
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 8-20-2014
Publisher: Administrator
This paper proposes a two-step methodology for Value-at-Risk prediction. The first step involves estimation of a GARCH model using quasi-maximum likelihood estimation and the second step uses model filtered returns with the skewed t distribution of Azzalini and Capitanio [J. R. Stat. Soc. B, 2003, 65, 367–389]. The predictive performance of this method is compared to the single-step joint estimation of the same data generating process, to the well-known GARCH-Evt model and to a comprehensive set of other market risk models. Backtesting results show that the proposed two-step method outperforms most benchmarks including the classical joint estimation method of same data generating process and it performs competitively with respect to the GARCH-Evt model. This paper recommends two robust models to risk managers of emerging market stock portfolios. Both models are estimated in two steps: the GJR-GARCH-Evt model and the two-step GARCH-St model proposed in this study.
Ergen, Ibrahim Sign in to follow this author
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