东北大学学报(社会科学版) ›› 2021, Vol. 23 ›› Issue (2): 21-28.DOI: 10.15936/j.cnki.1008-3758.2021.02.004

• 经济与管理研究 • 上一篇    下一篇

股票流动性对股市尾部风险的影响——基于POT模型的实证研究

张昱城,葛林洁,李延军   

  1. (河北工业大学经济管理学院,天津300401)
  • 出版日期:2021-05-12 发布日期:2021-03-23
  • 通讯作者: 张昱城
  • 作者简介:张昱城(1987-),男,陕西汉中人,河北工业大学教授,博士生导师,主要从事大数据、元分析、人力资源管理研究;葛林洁(1992-),女,河北石家庄人,河北工业大学博士研究生,主要从事人力资源管理、资产定价与投资分析研究;李延军(1978-),男,陕西延安人,河北工业大学教授,管理学博士,主要从事资产定价与投资分析研究。
  • 基金资助:
    国家自然科学基金资助项目(71972065);河北省自然科学基金资助项目(G2019202307)。

The Influence of Stock Liquidity on Tail Risk of Stock Market: An Empirical Research Based on POT Model

ZHANG Yucheng, GE Linjie, LI Yanjun   

  1. (School of Economics and Management, Hebei University of Technology, Tianjin 300401, China)
  • Online:2021-05-12 Published:2021-03-23
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摘要: 针对在险价值模型正态假设的不合理性,利用基于广义帕累托分布的POT模型对我国股票市场尾部风险进行了度量,并且通过对样本数据按照流动性分组探究股票流动性对我国股票市场尾部风险的影响。将统计理论中的斜率变点理论引入到传统阈值选取方法中,有效避免了最优阈值确定时的主观性问题。研究结果表明:对于股市尾部风险的度量,95%置信水平下的VaR值比90%置信水平下VaR值的估计结果更可信,且估计值显示尾部风险与流动性呈反向变化,即股票流动性越小,市场尾部风险越大。

关键词: 股票流动性; 尾部风险; ARMA-GARCH模型; POT模型

Abstract: In view of the irrationality of the normal hypothesis of the value-at-risk model, the POT model based on the generalized pareto distribution is used to measure the tail risk of China's stock market, and the influence of stock liquidity on the tail risk of China's stock market is explored by grouping the sample data according to liquidity. In the research, the slope change point theory in statistical theory is introduced into the traditional threshold selection method, which effectively avoids the subjectivity problem when determining the optimal threshold. The test results show that for the measurement of tail risk of the stock market, the VaR value at the 95% confidence level is more reliable than the estimated result of the VaR value at the 90% confidence level, and the estimated value shows that tail risk and liquidity change in the opposite direction, that is, the smaller the stock liquidity is, the greater the market tail risk.

Key words: stock liquidity; tail risk; ARMA-GARCH model; POT model

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