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中国管理科学 ›› 2017, Vol. 25 ›› Issue (10): 1-10.doi: 10.16381/j.cnki.issn1003-207x.2017.10.001

• 论文 •    下一篇

下行风险、符号跳跃风险与行业组合资产定价

龚旭1,2, 文凤华3, 黄创霞4,5, 杨晓光5   

  1. 1. 厦门大学经济学院, 福建 厦门 361005;
    2. 厦门大学管理学院、中国能源政策研究院、能源经济与政策协同创新中心, 福建 厦门 361005;
    3. 中南大学商学院, 湖南 长沙 410083;
    4. 长沙理工大学数学与计算科学学院, 湖南 长沙 410114;
    5. 中国科学院数学与系统科学研究院管理、决策与信息系统重点实验室, 北京 100190
  • 收稿日期:2016-12-25 修回日期:2017-05-25 出版日期:2017-10-20 发布日期:2017-12-15
  • 通讯作者: 文凤华(1972-),男(汉族),湖南益阳人,中南大学商学院教授,博士生导师,管理科学与工程博士,研究方向:金融工程与金融风险管理,E-mail:mailtowfh@126.com. E-mail:mailtowfh@126.com
  • 基金资助:

    国家自然科学基金资助项目(71701176,71371195,71471020,71431008,71633006);中国博士后科学基金(2017M612121);中南大学中央高校基本科研业务费专项资金资助(2015zzts006)

Downside Risk, Signed Jump Risk and Asset Pricing of Industry Portfolios

GONG Xu1,2, WEN Feng-hua3, HUANG Chuang-xia4,5, YANG Xiao-guang5   

  1. 1. School of Economics, Xiamen University, Xiamen 361005, China;
    2. School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Ceuter for Energy Economics and Energy Policy, Xiamen University, Xiamen 361005, China;
    3. School of Business, Central South University, Changsha 410083, China;
    4. College of Mathematics and Computing Science, Changsha University of Science and Technology, Hunan 410114, China;
    5. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2016-12-25 Revised:2017-05-25 Online:2017-10-20 Published:2017-12-15

摘要: 本文在资本资产定价模型(CAPM)的基础上,构建包含市场风险溢价、下行风险和符号跳跃风险的新资产定价模型,并使用高频交易数据计算模型中各风险因子,研究当期和跨期的行业组合定价问题。研究表明:当期的市场风险溢价、下行风险和符号跳跃风险因子对行业组合的超额收益率有很好的解释作用,且对上证能源等周期性行业组合的解释能力强于上证消费等非周期性行业组合;而滞后一期的市场风险溢价、下行风险和符号跳跃风险因子对行业组合超额收益率的预测作用非常有限。同时,我们的研究还发现,通过AR(1)、LAR(1)、AR(3)、LAR(3)、HAR和LHAR等时间序列预测模型,运用样本外滚动窗预测技术得到市场风险溢价等因子的预测值后,构建的新跨期定价模型对行业组合有较好的定价能力。其中,HAR和LHAR对应的跨期定价模型表现最好,且它们在上证材料组合和上证公用组合中表现尤为突出。

关键词: 下行风险, 符号跳跃, 已实现半方差, 资产定价

Abstract: In this paper, whether downside risk and signed jump risk have effects on pricing industry portfolios is examined. Assets pricing models with market risk premium, downside risk and signed jump risk are proposed firstly. Then, the new models are applied to study the contemporaneous/intertemporal pricing problem of industry portfolios. The results indicate that the contemporaneous market risk premium, downside risk and signed jump risk factors perform important interpretative functions for the excess return of industry portfolios. And the functions for cyclical industries are stronger than that of non-cyclical industries. However, the first-lagged market risk premium, downside risk and signed jump risk are limited in forecasting the contemporaneous excess return of industry portfolios. Furthermore, the first-order autoregressive model (AR(1) model), first-order autoregressive model with leverages (LAR(1) model), third-order autoregressive model (AR(1) model), first-order autoregressive model with leverages (LAR(3) model), heterogeneous autoregressive model (HAR model) and heterogeneous autoregressive model with leverages (LHAR model) are employed to obtain the predictive values of all risk factors, and intertemporal assets pricing models are constructed. It is found that new models show good pricing power for industry portfolios. Among them, HAR and LHAR models outperform other models, and their performances are particularly prominent for pricing the Shanghai material and public industry portfolios. The above results mean that the effects of downside risk and signed jump risk should not be ignored when pricing industry portfolios in shock market.

Key words: downside risk, signed jump, realized semivariance, asset pricing

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