Investor attention and reaction in COVID-19 crisis: sentiment analysis in the Indian stock market

ABSTRACT

Purpose This paper aims to investigate the influence of attention and sentiment in the Indian stock market during the unusual COVID-19 crisis in the first and second waves of the pandemic. Design/methodology/approach In this study, the capital asset pricing model (CAPM) is used to estimate the expected return. The autoregressive distributed lag (ARDL) model with optimal lag value selection and Granger causality using the vector autoregressive (VAR) estimation model were applied to find out whether there is a causal relationship between investors' attention and sentiment that influence stock returns across 14 sectors. Findings The results show that increased attention to COVID-19 substantially varied in the first wave and second wave market reactions. The upsurge attention of COVID-19 shows a negative influence with lower expected returns in the second wave. The sentiment of investors contrasts from the lower expected return in the first wave to the higher expected return in the second wave of the pandemic. Moreover, investors' sentiment in a state of fear is associated with lower returns. Originality/value The authors capture sentiment based on attention and investors mood using novel data set during the COVID-19 pandemic shock. The study is among a few which take a comprehensive stock market response during initial and subsequent waves across sector returns.