考虑期限特征的股票收益率高阶协矩建模与资产定价研究

近年来极端事件频发，资产收益率的偏度、峰度等高阶矩金融风险测度和定价成为研究热点。然而，股市投资的无期性使得学者对股票收益率测度期限的重视不如对债券、期权等，更是忽略期限特征对系统性高阶矩风险管理以及高阶协矩资产定价的影响。鉴于此，本项目拟1）利用投资者异质信念与信息扩散延迟，解释股票收益率高阶协矩期限特征的形成机制；2）利用跨期限特征模型，解决高阶协矩建模在不同期限间的演化问题；3）基于“均值-方差-高阶矩”框架，构建考虑期限特征的高阶协矩资产定价模型，并实证揭示该模型对我国股市资产定价影响。在理论上，本项目改进了常用的小波理论与混频数据等忽视跨期限演化机制的期限研究方法，优化了现有未考虑期限特征的高阶协矩资产定价研究；在应用上，本项目深度挖掘系统性高阶矩风险，有助于厘清极端风险发生后股市微观结构与定价机制的演变、理解不同投资期限下投资者行为的影响，符合我国防范系统性金融风险的战略意义。

In recent years, extreme events occur frequently. The skewness and kurtosis of assets' returns and pricing based on high-order moment risk have attracted great attention. However, due to the indefinite-horizon stock investment, the measurement horizon of stock return is not as important as those of bonds and options. The existing studies often ignore the horizon effect on systemic high-order moment risk and its impact on the high-order moment asset pricing. Therefore, this project intends to 1) explain the formation mechanism of the horizon effect of systemic higher-order moment risk by using investors' heterogeneous beliefs and information diffusion delay; 2) use the cross-horizon characteristic model to solve the evolution problem of each systemic higher moment risk in different horizons; 3) construct a high-order co-moment asset pricing model under the framework of "mean-variance-high order moment" by considering the horizon effect, and empirically studies the impact of the model on asset pricing in China's stock market. In theory, this project improves the research method on horizon dependence that ignores the relationship between estimators between different horizon lengths, such as wavelet theory and mixing data, which is different from the existing high-order moment asset pricing research that ignores the horizon dependence of the stock market. In practice, the deep mining of systemic higher-order moment risk is helpful to clarify the evolution of the stock market microstructure and pricing mechanism after the occurrence of extreme risk, understand the impact of investor behavior under different investment periods, and meet the strategic needs of China to prevent systemic financial risk.