Estimation and Testing of Portfolio Value-at-Risk Based on L-Comoment Matrices

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, N. R. & Tierney, D. E., 1973) and modified VaR (Zangari, P., 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. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:897–908, 2010