Abstract
This study employs L-comoments introduced by Serfling and Xiao (2007) into portfolio Value-at-Risk estimation through two models: the Cornish-Fisher expansion (Draper and Tierney 1973) and modified VaR (Zangari 1996). Backtesting outcomes indicate that modified VaR outperforms and L-comoments give better estimates of portfolio skewness and excess kurtosis than do classical central moments in modeling heavy-tailed distributions.
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