Incorporating the Time-Varying Tail-Fatness into the Historical Simulation Method for Portfolio Value-at-Risk

Chu-Hsiung Lin (), Chang-Cheng Chang Chien () and Sunwu Winfred Chen ()
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Chu-Hsiung Lin: Department of Finance, National Kaohsiung First University of Science and Technology, Taiwan, ROC
Chang-Cheng Chang Chien: Department of Finance and Banking, Shih Chien University Kaohsiung Campus, National Kaohsiung First University of Science and Technology, Taiwan, ROC
Sunwu Winfred Chen: Department of Finance and Banking, Shih Chien University Kaohsiung Campus, National Kaohsiung First University of Science and Technology, Taiwan, ROC

Review of Pacific Basin Financial Markets and Policies (RPBFMP), 2006, vol. 09, issue 02, 257-274

Abstract: This study extends the method of Guermat and Harris (2002), the Power EWMA (exponentially weighted moving average) method in conjunction with historical simulation to estimating portfolio Value-at-Risk (VaR). Using historical daily return data of three hypothetical portfolios formed by international stock indices, we test the performance of this modified approach to see if it can improve the precise forecasting capability of historical simulation. We explicitly highlight the extended Power EWMA owns privileged flexibilities to capture time-varying tail-fatness and volatilities of financial returns, and therefore may promote the quality of extreme risk management. Our empirical results, derived from the Kupiec (1995) tests and failure ratios, show that our proposed method indeed offers substantial improvements on capturing dynamic returns distributions, and can significantly enhance the estimation accuracy of portfolio VaR.

Keywords: Value-at-Risk; historical simulation method; power exponentially weighted moving average (search for similar items in EconPapers)
JEL-codes: G1 G2 G3 (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1142/S0219091506000720

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