Xu Weijia, Li Aihua, Wei Lu
School of Management Science and Engineering, Central University of Finance and Economics, Beijing, 102206, China.
Procedia Comput Sci. 2022;199:87-94. doi: 10.1016/j.procs.2022.01.011. Epub 2022 Feb 3.
This paper studied the impact of COVID-19 on China's capital market and major industry sectors via an improved ICSS algorithm, a time series model with the exogenous variable and a non-parametric conditional probability estimation. Through the empirical analysis, it is found that the epidemic has no significant impact on the return of the stock and bond markets, but it has increased the market volatility and the impact on the stock market volatility is gradual and more obvious. There are significant differences in the significance, direction and duration of the epidemic on different sectors. In addition, the impact of COVID-19 has been gradual in some industries and rapid in others. Different industries show different sensitivities in their response to COVID-19. Based on the analysis of the impact, this paper put forward the corresponding suggestions for investment strategies and macro-control decisions.
本文通过改进的ICSS算法、含外生变量的时间序列模型和非参数条件概率估计，研究了新冠疫情对中国资本市场和主要行业部门的影响。通过实证分析发现，疫情对股票和债券市场的回报率没有显著影响，但增加了市场波动性，且对股票市场波动性的影响是渐进且更明显的。疫情对不同行业的影响在显著性、方向和持续时间上存在显著差异。此外，新冠疫情的影响在一些行业是渐进的，而在另一些行业则是迅速的。不同行业在应对新冠疫情时表现出不同的敏感性。基于对影响的分析，本文提出了投资策略和宏观调控决策的相应建议。
