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Can L-moments beat central moments in modelling risk? An empirical analysis

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  • Xiao Qin

Abstract

This article applies a new statistical moment, Trimmed L-comoment, in modelling Expected Shortfall ( ES ) and exploits an empirical study on China's stock markets. In comparison with existing models, out-of-sample forecasts and backtests indicate superior accuracy and precision for the models based on Trimmed L-comoments, especially to those based on central moments.

Suggested Citation

  • Xiao Qin, 2012. "Can L-moments beat central moments in modelling risk? An empirical analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1441-1447, October.
    • Handle: RePEc:taf:apeclt:v:19:y:2012:i:15:p:1441-1447
    DOI: 10.1080/13504851.2011.631889
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    References listed on IDEAS

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    1. Kerkhof, Jeroen & Melenberg, Bertrand, 2004. "Backtesting for risk-based regulatory capital," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 1845-1865, August.
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    Cited by:

    1. Kim, Woo Chang & Fabozzi, Frank J. & Cheridito, Patrick & Fox, Charles, 2014. "Controlling portfolio skewness and kurtosis without directly optimizing third and fourth moments," Economics Letters, Elsevier, vol. 122(2), pages 154-158.

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