English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

During any unique crisis, panic sell-off leads to a massive stock marketcrash that may continue for more than a day, termed as mainshock. The effect ofa mainshock in the form of aftershocks can be felt throughout the recoveryphase of stock price. As the market remains in stress during recovery, anysmall perturbation leads to a relatively smaller aftershock. The duration ofthe recovery phase has been estimated using structural break analysis. We havecarried out statistical analyses of the 1987 stock market crash, 2008 financialcrisis and 2020 COVID-19 pandemic considering the actual crash-times of themainshock and aftershocks. Earlier, such analyses were done considering anabsolute one-day return, which cannot capture a crash properly. The resultsshow that the mainshock and aftershock in the stock market follow theGutenberg-Richter (GR) power law. Further, we obtained a higher $\beta$ valuefor 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 fasterthan the financial-crisis-2008. The result is consistent with the presentrecovery of the market from the COVID-19 pandemic. The analysis shows that thehigh magnitude aftershocks are rare, and low magnitude aftershocks are frequentduring the recovery phase. The analysis also shows that the distribution$P(\tau_i)$ follows the generalized Pareto distribution, i.e.,$\displaystyle~P(\tau_i)\propto\frac{1}{\{1+\lambda(q-1)\tau_i\}^{\frac{1}{(q-1)}}}$,where $\lambda$ and $q$ are constants and $\tau_i$ is the inter-occurrencetime. This analysis may help investors to restructure their portfolios during amarket crash.

international journal of modern physics c

Statistical properties of the aftershocks of stock market crashes  revisited: Analysis based on the 1987 crash, financial-crisis-2008 and  COVID-19 pandemic