Drawing upon prior research on the Indian stock market, they examine whether the Bombay Stock Exchange (BSE) exhibits herding behaviour, and whether herding behaviour differs when the market recovers (up or down).Data from January 1, 2017 to December 31, 2020 was investigated for herding. The paper presents an alternative approach to testing herding behavior in the Indian stock market using the measure of cross-sectional absolute deviation and a semi-parametric estimator of quantile regression. Data analysis shows that tthroughout the whole span, herding behaviour is clearly evident. When the market is volatile, there is little evidence of herding. Another study found herding behaviour in fluctuation markets in India, though it is more pronounced in up markets, which is steady with the overall results. The study has limitations because we used monthly traded stock values of five IT businesses and the SENSEX to compare market performance. Herding behaviour is analysed using market returns solely. This study applies to real-world financiers, regulators, and lawmakers. The COVID-19 pandemic has created a "new set of normalcy" for merchants. Any behavioural bias might cause asset valuation inefficiencies. Herding behaviour hinders rational asset pricing theories under exogenous events. Thus, scholars must create new value models. Disruption and information asymmetry damage the market. Instead of following the crowd, investors should have a "investment vision" that guides their decisions. The study investigate herding behaviour in Bombay Stock Exchange (BSE) and fluctuation markets in India