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.
Abstract
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.
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白娟娟, 师荣蓉.
基于广义已实现测度的中国股市波动预测与 VaR
度量. 系统科学与数学, 2021, 41(3): 653-666. https://doi.org/10.12341/jssms20218
BAI Juanjuan, SHI Rongrong.
The Volatility Forecasting and VaR Measurement of Chinese Stock
Market Based on Generalized Realized Measures. Journal of Systems Science and Mathematical Sciences, 2021, 41(3): 653-666 https://doi.org/10.12341/jssms20218
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脚注
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