论文标题
股票市场崩溃余震的统计属性重新审视:基于1987年崩溃,金融危机2008和COVID-19的分析
Statistical properties of the aftershocks of stock market crashes revisited: Analysis based on the 1987 crash, financial-crisis-2008 and COVID-19 pandemic
论文作者
论文摘要
在任何独特的危机中,恐慌抛售都会导致大规模的股市崩溃,可能持续一天以上,称为Mainshock。在股票价格的整个恢复阶段,可以感觉到主震以余震形式的影响。由于市场在恢复过程中保持压力,任何小的扰动都会导致相对较小的余震。使用结构断裂分析估算了恢复阶段的持续时间。考虑到主震动和余震的实际崩溃时间,我们已经对1987年股市崩溃,2008年金融危机和2020年Covid-19的统计分析进行了统计分析。早些时候,考虑了绝对的一日回报,进行了此类分析,无法正确捕获崩溃。结果表明,股票市场的主震动和余震遵循Gutenberg-Richter(GR)Power Law。此外,与GR Law的Financial-Crisisis-2008相比,我们获得了Covid-19崩溃的$β$值更高的$β$价值。这意味着Covid-19期间股票价格的收回可能比2008年的金融危机更快。结果与目前从共同19-19大流行中恢复市场的回收率是一致的。分析表明,高幅度的余震很少,并且在恢复阶段频繁发生余震量。分析还表明,分布$ p(τ_i)$遵循广义的帕托分布,即$ \ displayStyle〜p(τ_i)\ propto \ propto \ frac {1} {\ {\ {1+λ(q-1(q-1)τ_i\ \ \ \ \ \ \ \ \} $τ_i$是互联时间。这种分析可能会帮助投资者在市场崩溃期间重组其投资组合。
During any unique crisis, panic sell-off leads to a massive stock market crash that may continue for more than a day, termed as mainshock. The effect of a mainshock in the form of aftershocks can be felt throughout the recovery phase of stock price. As the market remains in stress during recovery, any small perturbation leads to a relatively smaller aftershock. The duration of the recovery phase has been estimated using structural break analysis. We have carried out statistical analyses of the 1987 stock market crash, 2008 financial crisis and 2020 COVID-19 pandemic considering the actual crash-times of the mainshock and aftershocks. Earlier, such analyses were done considering an absolute one-day return, which cannot capture a crash properly. The results show that the mainshock and aftershock in the stock market follow the Gutenberg-Richter (GR) power law. Further, we obtained a higher $β$ value for the COVID-19 crash compared to the financial-crisis-2008 from the GR law. This implies that the recovery of stock price during COVID-19 may be faster than the financial-crisis-2008. The result is consistent with the present recovery of the market from the COVID-19 pandemic. The analysis shows that the high magnitude aftershocks are rare, and low magnitude aftershocks are frequent during the recovery phase. The analysis also shows that the distribution $P(τ_i)$ follows the generalized Pareto distribution, i.e., $\displaystyle~P(τ_i)\propto\frac{1}{\{1+λ(q-1)τ_i\}^{\frac{1}{(q-1)}}}$, where $λ$ and $q$ are constants and $τ_i$ is the inter-occurrence time. This analysis may help investors to restructure their portfolios during a market crash.