基于跳跃和符号跳跃变差的HAR-RV预测其MCS检验

doi:F 830.9

系统管理学报 ›› 2015, Vol. 24 ›› Issue (5): 700-710.DOI: F 830.9

基于跳跃和符号跳跃变差的HAR-RV预测其MCS检验

马锋，魏宇，黄登仕，张鹏云

西南交通大学经济管理学院，成都 610031

收稿日期:2013-12-30 修回日期:2014-04-28
作者简介:马锋（1986-），男，博士生。研究方向为金融工程和金融复杂性。E-mail：mafeng575@126.com
基金资助:
国家自然科学基金资助项目（71371157，71401077，71090402，71071131）；高等学校博士学科点专项科研基金资助课题（20120184110020）；教育部人文社科基金规划资助项目（14YJC790073）；教育部博士点基金资助项目（20120184110020）；四川省科技青年基金资助项目（15QNJJ0032）

The HAR-RV Forecasting Model with the Jump and Signed Jump Variations and Its MCS Test

MA Feng，WEI Yu，HUANG Deng-shi，ZHANG Peng-yun

Received:2013-12-30 Revised:2014-04-28

摘要/Abstract

摘要： 以沪深300指数的高频数据为例，运用滚动时间窗的样本外预测方法以及比SPA检验更具优势的模型信度设定检验（Model Confidence Set，MCS），实证分析了跳跃、符号跳跃变差及符号正负向跳跃变差对HAR-RV、HAR-RV-J、HAR-RV-CJ和HAR-RV-TCJ等4种基础波动率模型预测能力的影响。研究发现：符号跳跃变差不仅可以提高各波动率模型的拟合精度，而且还可以提高模型的预测精度；符号正向和负向跳跃变差相比符号跳跃变差对未来波动率具有更好的解释能力，且它们对未来波动率的影响是不对称的；加入符号正、负向跳跃变差的HAR-RV-TCJ模型的预测效果是众多模型中表现最好的，尤其是它的对数形式。

关键词: 跳跃检验, 跳跃符号变差, MCS检验

Abstract: Taking 5-minute high frequency data of the CSI 300 index as an example, and applying the out-of-sample rolling time window forecasting combined with Model Confidence Set which is proved superior to SPA test, we explore the impact of the jump, signed and signed negative (and positive) jump variation on future volatility. The empirical results show that, signed jump variation not only increases the goodness of fit of the model, but also improves the forecasting accuracy of the model. By comparison, the signed jump variation, signed negative and positive jump variation have better explanations to the future volatility, which is asymmetry. The HAR-RV-SJV-D model is the best one among models discussed in this paper, especially its logarithmic form.

Key words: the jump test, signed jump variation, Model Confidence Set

马锋，魏宇，黄登仕，张鹏云. 基于跳跃和符号跳跃变差的HAR-RV预测其MCS检验[J]. 系统管理学报, 2015, 24(5): 700-710.

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