A study of China’s financial market risks in the context of Covid-19, based on a rolling generalized autoregressive score model using the asymmetric Laplace distribution

自回归模型 拉普拉斯变换 背景(考古学) 拉普拉斯分布 中国 计量经济学 2019年冠状病毒病(COVID-19) 分布(数学) 金融市场 经济 数学 业务 医学 财务 内科学 地理 数学分析 考古 传染病(医学专业) 疾病
作者
Guanghui Han,Panpan Liu,Yueqiang Zhang,Xiaobo Li
出处
期刊:The Journal of Risk Model Validation
标识
DOI:10.21314/jrmv.2024.001
摘要

In order to fully capture the degree of risk in the financial market, we use the asymmetric Laplace distribution (ALD) to describe the distribution characteristics of the financial rate of return in combination with a generalized autoregressive score (GAS) model. We apply the GAS-ALD model to time-varying-parameter rolling estimation of the risk measures value-at-risk (VaR) and expected shortfall (ES), with the aim of building a dynamic risk measurement model for the financial market during the Covid-19 pandemic. Data for representative industry indexes of the Shanghai Stock Exchange are selected for empirical analysis, and parametric and nonparametric methods are used for comparison and backtesting. The results show, first, that the GAS-ALD model has obvious advantages over other tested methods in estimating VaR and ES and predicting the volatility risk of the rate of return, with ES being more accurate at predicting risk in extreme cases than VaR. Second, the pandemic had a big impact on the raw materials and energy industries, but a smaller impact on the financial industry. Based on the research conclusions, recommendations are put forward for three areas: government, regulators and enterprises.

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