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http://dx.doi.org/10.5351/KJAS.2009.22.2.261

Assessments for MGARCH Models Using Back-Testing: Case Study  

Hwang, S.Y. (Department of Statistics, Sookmyung Women's University)
Choi, M.S. (Department of Statistics, Sookmyung Women's University)
Do, J.D. (Department of Statistics, Keimyung University)
Publication Information
The Korean Journal of Applied Statistics / v.22, no.2, 2009 , pp. 261-270 More about this Journal
Abstract
Current financial crisis triggered by shaky U.S. banking system adds to the emphasis on the importance of the volatility in controlling and understanding financial time series data. The ARCH and GARCH models have been useful in analyzing economic time series volatilities. In particular, multivariate GARCH(MGARCH, for short) provides both volatilities and conditional correlations between several time series and these are in turn applied to computations of hedge-ratio and VaR. In this short article, we try to assess various MGARCH models with respect to the back-testing performances in VaR study. To this end, 14 korean stock prices are analyzed and it is found that MGARCH outperforms rolling window, and BEKK and CCC are relatively conservative in back-testing performance.
Keywords
Muitivariate GARCH; Value at Risk (VaR); back-testing; stock prices data;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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