Abstract

In the era of social media and internet, Twitter (presently ‘X’) has been recognized as the prominent factor for financial markets by multiple corporates and experts. The motivation of present research hinges on burgeoning popularity of Twitter in the financial community for sharing information and impact of their hidden sentiments on financial markets. Research on tweet-based sentiments and their influence on financial markets in India is still in the infancy stage. To cover this gap, the present study empirically investigates the predictive impact of financial tweet sentiments on the Indian stock Index’s returns over a short period. The paper scraped 22,816 tweets and Nifty 50 index’s intraday hour end values for January 2023. Using Natural Processing Technique, the overall sentiments of the financial community are found as highly positive for each trading hour. Next, it presents a low positive correlation between positive sentiments, sentiment polarity, and hourly returns. Lagged negative sentiments reflect the better ability to impact current period returns than positive sentiments and polarity. Additionally, sentiment polarity and returns reflect bi-directional causation for the future period impact. Investors, stock market traders, and other practitioners can employ the proven concept of linkage between tweet sentiments and returns for constructing effective investment and trading strategies. JEL Classifications: G41, D53, G17, G02, G19

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