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Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns

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  • Cheng, Wan-Hsiu
  • Hung, Jui-Cheng
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    Abstract

    This paper utilizes the most flexible skewed generalized t (SGT) distribution for describing petroleum and metal volatilities that are characterized by leptokurtosis and skewness in order to provide better approximations of the reality. The empirical results indicate that the forecasted Value-at-Risk (VaR) obtained using the SGT distribution provides the most accurate out-of-sample forecasts for both the petroleum and metal markets. With regard to the unconditional and conditional coverage tests, the SGT distribution produces the most appropriate VaR estimates in terms of the total number of rejections; this is followed by the nonparametric distribution, generalized error distribution (GED), and finally the normal distribution. Similarly, in the dynamic quantile test, the VaR estimates generated by the SGT and nonparametric distributions perform better than that generated by other distributions. Finally, in the superior predictive test, the SGT distribution has significantly lower capital requirements than the nonparametric distribution for most commodities.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Empirical Finance.

    Volume (Year): 18 (2011)
    Issue (Month): 1 (January)
    Pages: 160-173

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    Handle: RePEc:eee:empfin:v:18:y:2011:i:1:p:160-173

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    Web page: http://www.elsevier.com/locate/jempfin

    Related research

    Keywords: Skewed generalized t distribution Volatility Value-at-Risk;

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    Cited by:
    1. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, vol. 33(5), pages 903-911, September.
    2. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Working Papers 2014-325, Department of Research, Ipag Business School.

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