In this study, we have attempted to model the predictive value of google search volumes for stock returns and the trading volume for NSE Nifty 100 companies over a period of roughly 5 years. In contrast to the to the findings in prior research , we observe that ticker search volumes do not exhibit any predictive value for future excess stock returns. Further, we observe a weak but significant positive effect of ticker search volumes on trading volume with a 2-week lag. A battery of robustness checks supports our findings. These results confirm that the Indian financial market is fairly efficient. Our work warns the investors from possible misleading insights arising from search volume and stock returns-related studies. They should be aware that the predicting power of search volume is very limited in the equity markets (especially in major financial markets like India) unlike in cryptocurrency markets. The lack of predictability can possibly be explained by breaking down the composition and behaviour of stock market investors in India, analysing their risk-averse tendencies and accounting for noise traders. The results of this study could have important implications for the various stakeholders in the Indian financial markets. It serves as a caution to individual investors about potentially deceptive insights from stock ticker search analysis and the ensuing unanticipated losses in their portfolios. For institutional investors, it simply reinforces the value of proprietary non-public information available to them. For policymakers, it could aid in designing better monetary policies keeping in mind the implied efficiency of the Indian financial market. Lastly, in academia, it aims to encourage further study of the Indian market on the lines of informational efficiency and stock market behaviour in this unique economy.
