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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。
Based on the capital asset pricing model (CAPM), this paper builds a new asset pricing model that includes market risk premium, downside risk and symbolic jump risk, and uses high-frequency transaction data to calculate risk factors in the model to study the current and intertemporal Industry portfolio pricing issues. The research shows that the market risk premiums, downside risks and symbolic jump risk factors of the current period can explain the excess return rate of the industry portfolio well, and the ability to explain the cyclical industry combinations such as Shanghai Energy is stronger than that of the non-cyclical However, the lagged market risk premium, downside risk and symbolic jump risk factors have very limited effect on the prediction of excess returns of the industry portfolio. At the same time, our research also finds that market risk premium and so on can be obtained by out-of-sample rolling window prediction using time series forecasting models such as AR (1), LAR (1), AR (3), LAR (3), HAR and LHAR After the predicted value of the factor, the new intertemporal pricing model constructed has better pricing ability for the industry portfolio. Among them, the inter-period pricing model corresponding to HAR and LHAR performed the best, and they performed particularly well in the SSE composite portfolio and SSE composite portfolio.