基于广义已实现测度的中国股市波动预测与VaR度量  

The Volatility Forecasting and VaR Measurement of Chinese Stock Market Based on Generalized Realized Measures

作　　者：白娟娟 师荣蓉[2] BAI Juanjuan;SHI Rongrong(School of Mathematics,Northwest University,Xi’an 710127;School of Economics and Management,Northwest University,Xi’an 71QV27)

机构地区：[1]西北大学数学学院,西安710127 [2]西北大学经济管理学院,西安710127

出　　处：《系统科学与数学》2021年第3期653-666,共14页Journal of Systems Science and Mathematical Sciences

基　　金：国家社科基金重点项目(19AJL010);陕西省软科学一般项目(2020KRM212);陕西省教育厅智库项目(20JT067)资助课题。

摘　　要：基于上证综合指数和深证成份指数,文章将广义已实现测度引入ARFIMA-Realized GARCH模型,同时考虑已实现方差、已实现极差、已实现双幂次变差和已实现极差双幂次变差,比较不同已实现测度下模型的波动率预测能力和VaR度量效果.实证结果表明:ARFIMA-Realized GARCH模型能够充分捕获波动率的非对称性、长记忆性和持续性等特征;采用已实现方差的ARFIMA-Realized GARCH模型具有最优的波动率预测能力;已实现平均绝对离差能够改进模型的拟合效果,并且引入已实现风险值显著提高了ARFIMA-Realized GARCH模型的VaR预测精度.Based on Shanghai Composite Index and Shenzhen Component Index,the paper introduces generalized realized measures to the ARFIMA-Realized GARCH model and considers realized variance,realized range-based volatility,realized bipower variance and realized range-based bipower variance at the same time,then volatility forecasting ability and VaR measurement effect of models under different realized measures are compared.The results show that the ARFIMA-Realized GARCH model can fully capture the asymmetry,long term memory and persistence of volatility.With realized variance,the ARFIMA-Realized GARCH model has the best volatility forecasting ability.The realized mean absolute deviation can improve the fitting effect of the model,and the introduction of realized value-at-risk significantly improves the VaR forecasting accuracy of ARFIMA-Realized GARCH model.

关 键 词：ARFIMA-Realized GARCH模型 已实现测度 波动率预测 VAR度量 

分 类 号：F832.51[经济管理—金融学] F224