Estimation and testing of portfolio Value‐at‐Risk based on L‐comoment matrices
将L-协动差引入投资组合在险价值估计，通过两种模型比较发现修正VaR表现更优，且L-协动差比经典中心矩能更好估计偏度和超额峰度，适用于厚尾分布。
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