Combining a self-exciting point process with the truncated generalized Pareto distribution: An extreme risk analysis under price limits
Combining a self-exciting point process with the truncated generalized Pareto distribution: An extreme risk analysis under price limits
复制标题
将自激点过程与截断广义帕累托分布相结合：价格限制下的极端风险分析
DOI：
10.1016/j.jempfin.2020.03.003
复制
发表时间：
2020-06-01
影响因子：
2.6
通讯作者：
Xu, Chi
中科院分区：
文献类型：
--
作者：
Ji, Jingru;Wang, Donghua;Xu, Chi
本文提出了一个基于截断广义Pareto分布的自激点过程的一般框架来度量限价下股票市场的极端风险。我们将可预测的标记，定义为标记分布的方差取决于以前的事件通过强度，到模型设置。该方法能够很好地适应厚尾性、极端风险聚集性和价格限制等重要的经验特征。我们推导出一个封闭形式的解决方案的客观可能性，基于此，所提出的模型可以通过标准的最大似然估计算法估计。此外，还导出了风险价值和预期亏损的封闭形式度量。为了实证说明，我们使用中国证券指数300（+/- 10%的价格限制）的分析。总体而言，样本内拟合和样本外预测的结果表明，所提出的方法可以很好地解释经验数据。通过引入分支过程来区分内生风险和外生风险，我们还研究了中国股票市场的级联效应。
In this paper, we introduce a general framework of the self-exciting point process with the truncated generalized Pareto distribution to measure the extreme risks in the stock markets under price limits. We incorporate the predictable marks, defined as the variance of mark distribution depending on the previous events via the intensity, into the model setting. The proposed process can well accommodate many important empirical characteristics, such as the thick-tailness, extreme risk clustering and price limits. We derive a closed-form solution for the objective likelihood, based on which the proposed model can be estimated via the standard maximum likelihood estimation algorithm. Furthermore, the closed-form measures of the Value-at-Risk and Expected Shortfall are also derived. For empirical illustration, we use the China Securities Index 300 (with +/- 10% price restriction) in the analysis. In general, the results from both in-sample fitting and out-of-sample forecasting measures show that the proposed process can explain the empirical data well. We also investigate the cascade effect of the China stock market by introducing the branching process to distinguish the endogenous risks from the exogenous risks.