证券组合SKST-APARCH模型和VaR估计分析

金融资产无条件收益分布表现为偏度和峰度共存，运用ARCH模型族在波动和Valt分析中往往将对称的后尾t、GED误差分布与不对称冲击结合在一起来解决序列不对称特性．由于偏度和峰度并非相互独立．这样未能根本上解决问题。本文在APARCH模型中引入偏t分布（Skst）模型对上证指数和深证A股指数的波动及VaR进行了实证分析，并与Gauss、t、GED等对称分布下的估计进行了比较，结果显示Skst能较好的拟舍波动、较准估计VaR．

SKST-APARCH model and VaR estimation of securities portfolio

The unconditional distribution of financial return series not only shows the skewness but also the excess of kurtosis.In the analysis of volatility and VaR of applying ARCH models,the traditional method combined the symmetrical fat-tails of Student and GED errors distribution and the asymmetrical leverage effect can not solve the asymmetrical problems in the series because the skewness and the excess of kurtosis are not independent in practical.The SKST(skewed student distribution) is introduced into APARCH model for empirical study on volatility and VaR of the SSE Composite and SSE A-share indices in this paper.The result shows for whether volatility or VaR in sample the SKST performs more exact compared with the symmetric distribution of Gauss,Student and GED.