下行风险、符号跳跃风险与行业组合资产定价

发布时间：2018-08-05 11:48

【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。
[Abstract]:Based on the capital asset pricing model (CAPM), this paper constructs a new asset pricing model, which includes market risk premium, downlink risk and symbolic jump risk, and uses high-frequency trading data to calculate the risk factors in the model. This paper studies the current and intertemporal industry portfolio pricing problems. The results show that the market risk premium, downlink risk and symbolic jump risk factor can explain the excess return of the industry portfolio. And the ability to explain the cyclical industry portfolio, such as energy, is stronger than that of the non-cyclical industry portfolio, such as Shanghai consumption; and the market risk premium, which lags behind, The downside risk and symbolic jump risk factor have very limited effect on the forecast of excess return of industry portfolio. At the same time, we also find that the prediction value of market risk premium is obtained by using the time series prediction models such as AR (1) Lar (1) ar (3) Lar (3) Har and LHAR. The new cross-period pricing model has better pricing ability for industry portfolio. The cross-period pricing model corresponding to Har and LHAR performs best, and they are especially outstanding in the combination of Shanghai Stock Exchange and Shanghai Public Exchange.
【作者单位】：厦门大学经济学院;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;中南大学商学院;长沙理工大学数学与计算科学学院;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;
【基金】：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)
【分类号】：F832.51

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