ABSTRACT
Purpose: The present paper tries to probe the COVID-19 breakout effect on the stock markets by drawing shreds of evidence from India. Design/methodology/approach: Secondary data has been used and retrieved from the BSE and NSE portal in this study. The study covered the period July 1, 2019, to March 11, 2020, as "pre-COVID period" and March 12, 2020, to July 9, 2020, as "post-COVID period" Welch's t-test, popularly known as unequal variance t-test, and non parametric Mann-Whitney U test are used to compare the opening, highest, lowest, and closing prices across the two periods of the major stock indices;Nifty 50, Nifty 500, Nifty 100, Nifty Midcap 150, S&P BSE Sensex, S&P BSE 500, S&P BSE Midcap, and S&P BSE All Cap. We further extended our study by employing a multiple regression model for the post-COVID period to identify the repercussions of the spread of the virus and lockdown on the stock indices' prices. Findings: Both Welch's t-test and Mann-Whitney U-test indicated a significant (I% significance level) negative impact of the Covid-19 pandemic on the Indian stock market. Multiple regression model confirmed a significant (significant at I%) positive effect of a rise in the COVID-19 cases on the stock market, and COVID-19 related deaths do not significantly impact even at 10% level. Furthermore, the results revealed a significant (at I% level of significance) fall in the prices due to an increase in the lockdown days. Originality/value: These outcomes contribute to the literature by looking at Coronavirus's economic consequences by drawing evidence from the Indian stock market. This study provides insights into the policymakers and corporates into the economic repercussions of COVID-19.