This research empirically investigates the impact of investor sentiment on equity market volatility during periods of economic turbulence, with a focus on the Covid-19 pandemic. Daily data from the Bombay Stock Exchange Sensitive Index and proxies for investor sentiment from November 23, 2017 to March 31, 2022 is collected and split into pre- and post-Covid-19 periods. To quantify investor sentiment, a comprehensive sentiment index is developed using principal component analysis. The study employs generalized autoregressive conditional heteroscedasticity (GARCH), threshold GARCH and exponential GARCH models to evaluate the influence of sentiment on stock market volatility. These models enable the assessment of how positive news and negative news affect volatility differently, considering their asymmetric impacts. The results of the analysis highlight the significant influence of investor sentiment on volatility, particularly during the post-Covid-19 period. Post pandemic, volatility shocks are found to be more persistent and enduring, indicating heightened market instability. Negative news has a more pronounced impact on volatility than positive news of equivalent magnitude. This disparity can be attributed to the widespread concern, fear and uncertainty prevalent during the post-Covid-19 period, which contributed to the increase in market volatility.