Statistical properties of the aftershocks of stock market crashes revisited: Analysis based on the 1987 crash, financial-crisis-2008 and COVID-19 pandemic
arXiv:2012.03012 · doi:10.1142/S012918312250019X
Abstract
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 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 follows the generalized Pareto distribution, i.e., , where and are constants and is the inter-occurrence time. This analysis may help investors to restructure their portfolios during a market crash.
arXiv commentAccepted in International Journal of Modern Physics C (World Scientific)
References in corpus (16)
- Power-law distributions in empirical data
- The statistical properties of the volatility of price fluctuations
- Unified Scaling Law for Earthquakes
- Statistical Properties of Share Volume Traded in Financial Markets
- Large financial crashes
- Characterization of the frequency of extreme events by the Generalized Pareto Distribution
- A model for correlations in stock markets
- Market dynamics immediately before and after financial shocks: quantifying the Omori, productivity and Bath laws
- General theory of the modified Gutenberg-Richter law for large seismic moments
- Statistical Properties of Cross-Correlation in the Korean Stock Market
- Aging and scaling of aftershocks
- Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index
- Relevant Stylized Facts About Bitcoin: Fluctuations, First Return Probability, and Natural Phenomena
- Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery
- Identification of short-term and long-term time scales in stock markets and effect of structural break
- Dynamical analogy between economical crisis and earthquake dynamics within the nonextensive statistical mechanics framework