Asymmetric GARCH Value-at-Risk over MSCI in Financial Crisis

Han-Ching Huang, Yong-Chern Su and Jen-Tien Tsui
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Han-Ching Huang: Department of Finance, Chung Yuan Christian University, Taoyuan City, Taiwan 32023, R.O.C,
Yong-Chern Su: Department of Finance, National Taiwan University, Taiwan,
Jen-Tien Tsui: Department of Finance, National Taiwan University, Taiwan.

International Journal of Economics and Financial Issues, 2015, vol. 5, issue 2, 390-398

Abstract: This paper uses four asymmetric generalized autoregressive conditional heteroskedasticity (GARCH) models, which are GJR-GARCH, NA-GARCH, Threshold GARCH (T-GARCH), and AV-GARCH to compare their performance on value-at-risk (VaR) forecasting to the symmetric GARCH model. In addition, we adopt four different mean equations which are autoregressive moving average (ARMA[1,1]), AR(1), MA(1), and in-mean to find out a more appropriate GARCH method in estimating VaR of MSCI World Index in financial crisis. We pick up 900 daily information of MSCI World Index from 2006 to 2009. We find that GARCH-in-mean (GARCHM[1,1]), MA-GARCHM(1,1), AR(1)-T-GARCHM(1,1), and ARMA(1,1)-TGARCHM( 1,1) outperform other models in terms of number of violations. ARMA(1,1)-T-GARCHM(1,1) performs the best in terms of mean violation range, mean violation percentage, aggregate violation range, aggregate violation percentage, and max violation range. Other than T-GARCH models, number of violations decrease by using in-mean or MA(1) mean equation. Generally speaking, the better the performance in terms of violation, the larger the capital requirement is needed.

Keywords: Market Risk; Value-at-Risk; GARCH; MSCI; Financial Crisis (search for similar items in EconPapers)
JEL-codes: G2 G21 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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