中国股票市场最优套期保值比率研究------基于高阶矩HAR模型

唐勇,崔金鑫

系统科学与数学 ›› 2018, Vol. 38 ›› Issue (9) : 1036-1054.

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系统科学与数学 ›› 2018, Vol. 38 ›› Issue (9) : 1036-1054. DOI: 10.12341/jssms13436
论文

中国股票市场最优套期保值比率研究------基于高阶矩HAR模型

    唐勇1,2,崔金鑫1,2
作者信息 +

Research on Optimal Hedging Ratio of Chinese Stock Market Based on Higher Moments HAR Model

    TANG Yong 1,2 ,CUI Jinxin 1,2
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文章历史 +

摘要

金融资产收益率高阶矩风险和跳跃行为是套期保值策略的重要影响因素.文章将已实现高阶矩测度和跳跃风险测度引入HAR 族波动率模型,构建高阶矩HAR 族波动模型,并将Copula 函数与最优高阶矩波动率模型相结合,建立含高阶矩的Copula-HAR-RV-CJ-SJV-D-SK套期保值模型.以沪深300指数和中证500指数以及对应的股指期货构建套期保值策略.实证表明,从方差减少比率和超额收益率两方面来看,基于新模型的套期保值效果在样本内和样本外均优于传统静态套期保值模型、 时变二元GARCH 族套期保值模型和Copula-GARCH族套期保值模型.

Abstract

The higher moments factor and jump behavior of financial asset yield are significantly influencing ingredients of the hedging decision. This article introduces the realized higher moments measure and jump risk measure to traditional HAR volatility models so as to construct higher moments HAR volatility models. Then this article combines the Copula model with the optimal higher moments volatility model, then constructs Copula-HAR-RV-CJ-SJV-D-SK model which includes higher moments factors. In empirical application, CSI500, CSI300 futures and homologous underlying index are used to construct hedging strategy. Considering the ratio of variance reduction and abnormal return, both in-sample and out-of-sample performance criteria show that the proposed model is better than traditional static hedging models, time-varying Bivariate GARCH family hedging models and Copula-GARCH family hedging models.

关键词

已实现高阶矩 / Copula-HAR-RV-CJ-SJV-D-SK 模型 / 最优套期保值比率.

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唐勇 , 崔金鑫. 中国股票市场最优套期保值比率研究------基于高阶矩HAR模型. 系统科学与数学, 2018, 38(9): 1036-1054. https://doi.org/10.12341/jssms13436
TANG Yong , CUI Jinxin. Research on Optimal Hedging Ratio of Chinese Stock Market Based on Higher Moments HAR Model. Journal of Systems Science and Mathematical Sciences, 2018, 38(9): 1036-1054 https://doi.org/10.12341/jssms13436
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