Abstract
The COVID-19 pandemic has resulted in significant financial losses globally, increasing the volatility of financial assets. Thus, this study models the stock market volatility of developed economies during the COVID-19 pandemic. For this purpose, we used the GJR-GARCH (Albulescu, 2020; Albulescu, 2020) [1,1] econometric model on the daily time series returns data ranging from 01st-July-2019 to 18th-November-2020. The entire dataset was equally divided into two subsets; before COVID-19, and after the COVID-19. The empirical results of this study showed the presence of volatility clustering, leverage effect, and excess kurtosis indicating leptokurtic phenomena in all stock indices returns. In addition to this, it can be noted that compared to before COVID-19, the stock markets showed negative returns, and increased volatility during the COVID-19. Hence, based on these findings, this study provides significant insights for global stock market investors and economic policymakers regarding financial portfolio construction particularly during crises times.
| Original language | English |
|---|---|
| Article number | e25202 |
| Number of pages | 9 |
| Journal | Heliyon |
| Volume | 10 |
| Issue number | 4 |
| Early online date | 28 Jan 2024 |
| DOIs | |
| Publication status | Published - 29 Feb 2024 |
Bibliographical note
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