摘要
以我国创业板指数为研究对象,在正态分布、t分布和GED分布假设下比较分析不同类型的GARCH模型,预测不同置信水平下收益率序列的Va R值,并对结果进行比较和检验,得出如下结论:尽管EGARCH和PARCH模型预测的Va R值比GARCH和TGARCH模型更加精确,但模型种类的选择并非Va R值度量的关键,而分布假设与显著性水平则是影响Va R值精确度的关键因素。在正态分布下,当置信水平较低时,估计的Va R值能较好地刻画收益序列的尾部特征,但当显著性水平很高(如99%)时,估计的Va R值存在低估风险的现象;在t-分布下估计的Va R值存在高估风险的现象;在GED分布下,无论显著性水平的高低,GARCH类模型均能很好地刻画收益序列的尾部特征。
As the research object,this article takes our country the GEM index in normal distribution,t-distribution and GED distribution assumption that comparative analysis of the different types of GARCH model,predict the Va R of yield sequence under different confidence level,and carries on the comparison to the results and inspection,the following conclusion:although PARCH and EGARCH model to predict the Va R than GARCH and TGARCH model is more accurate,but not Va R measurement model selection of the key factors,the key factors influencing the Va R measurement is distribution hypothesis and the level of significance. Under the normal distribution,when the confidence level is low,can well depict earnings estimates of Va R of the end of the sequence characteristics,but when significance level is very high(99%),estimates of Va R has the phenomenon of underpriced risk;Under the distribution of t-estimates of Va R value overestimate risk phenomenon;Under the GED distribution,regardless of the significance level of high and low,GARCH kind of model can well describe benefits of the end of the sequence features.
出处
《经济与管理》
CSSCI
2016年第3期57-63,共7页
Economy and Management
基金
国家社科基金项目(12CJY037)