VaR-APARCH模型与证券投资风险量化分析

基本统计分析发现,上证综合指数回报率分布存在尖峰肥尾性,不服从正态分布,并且还具有杠杆效应。本文应用APARCH模型在三种分布假设下对上证综合指数通过事后模拟和条件单步预测来计算上证综合指数的VaR风险值,然后把它与应用GARCH模型的估计结果进行比较分析。通过返回检验,我们发现,APARCH应用于VaR估计是统计有效的,并且明显优于GARHC模型。

VaR-APARCH Model for Risk Measures of Stock Market

Preliminary data analysis shows that the return rates distribution of SSE is fat-tailed and doesn’t obey normal distribution and there is"leverage effect"in Shanghai Stock market.In this paper,we propose an APARCH model with three different distributions assumption to estimate conditional VaR.This model is then compared with the GARCH model under the corresponding three distributions assumption.Using back-testing of historical daily return series we show that the APARCH model yields statistically valid VaR measures and gives better one-day ahead estimates that the GARCH model.