基于QR-t-GARCH(1,1)模型沪深指数收益率风险度量的研究  

Research on Risk Measurement of Shanghai and Shenzhen Index Yield Based on QR-t-GARCH(1,1) Model

作　　者：刘亭 赵月旭 LIU Ting ,ZHAO Yue-xu(School of Economics, Hangzhou Dianzi University, Zhejiang Hangzhou 310018, Chin)

机构地区：[1]杭州电子科技大学经济学院

出　　处：《数理统计与管理》2018年第3期533-543,共11页Journal of Applied Statistics and Management

基　　金：国家自然科学基金资助项目(61473107,61273093)

摘　　要：以沪深综合指数收益率为研究对象，在t-GARCH（1，1）模型与st—GARCH（1，1）模型的基础上，引入分位数回归，分别建立了QR-t-GARCH（1，1）模型与QR-st—GARCH（1，1）模型。失败率检验结果表明，在5％、2．5％、1％的显著性水平下，加入分位数回归的GARCH（1，1）模型较GARCH（1，1）模型对指数收益率的风险度量效果更好，而且对异常值的稳健性也更强。该模型可对指数收益率的风险特征进行全面描述。Taking the Shanghai and Shenzhen comprehensive index yields as the research object, based on the models of t-GARCH（1,1） and st-CARCH（1,1）, the models of QR-t-GARCH（1,1） and QR-st- GARCH（1,1） were established by introducing the quantile regression. The results of failure rate test show that the CARCH（1,1） model which introduced quantile regression is more effective than the GARCH（1,1） model for the risk measurement of exponential yield at the significance level of 5%, 2.5%, 1% respectively, and its robustness for outliers is also stronger. The model can describe the risk characteristics of the exponential rate of return comprehensively.

关 键 词：沪深综合指数收益率 VAR值 分位数回归 t-GARCH模型 QR—t—GARCH模型 

分 类 号：F224.7[经济管理—国民经济] O212[理学—概率论与数理统计]