Abstract
COVID-19 has had significant impact on Indian stock market volatility. This study focuses on understanding the regime change from lower to higher volatility identified with a Markov Switching AR model. Utilizing machine learning feature selection methods, economic indicators are chosen to best explain changes in volatility. Results show that volatility is affected by specific economic indicators and is sensitive to COVID-19 news. Both negative and positive COVID-19 information is significant, though negative news is more impactful, suggesting a negativity bias. Significant increases in total and idiosyncratic risk are observed across all industries, while changes in systematic risk vary across industry. Hence, this paper made an attempt to study the impact of COVID-19 on stock market. This research study is an event study to analyze the stock price volatility of automobile sector. The outcome summary of the study revealed that there is a significant impact of automobile sector index price movements after the COVID –19 in India.
Keywords: COVID – 19, Automobile Sector, Volatility, NSE, Application Regression
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