Published Paper Details:

The increasing occurrence of abnormal phenomena in financial markets has challenged the assumptions of traditional finance, leading to the emergence of behavioural finance. This field, developed in the 1970s and 1980s, focuses on investor behaviour and explains market anomalies through the lens of sociology, incorporating psychology and behaviour into financial analysis (Baker & Wurgler, 2006). This shift in perspective has spurred extensive research into investor behaviour and sentiment. Several studies have focused on measuring and quantifying investor sentiment. Composite sentiment indexes, such as that developed by Baker and Wurgler (2007), utilize principal component analysis (PCA) to combine multiple sentiment indicators into a single index, capturing the collective sentiment of investors. In this paper, PCA is employed to construct an investor sentiment composite index using Indian stock market data, providing a nuanced understanding of investor sentiment in India. Secondly, the dynamic relationship between Investor Sentiment and Market Return is tested using multivariate time-series regression model. The model does succeed in reflecting the explanatory power of Investor Sentiment in predicting stock market return. Recognizing this phenomenon empowers investors to gain deeper insights into the market, enabling them to navigate their investment decisions more effectively. Moreover, this understanding opens avenues for additional research into refining methods of measuring investor sentiment, ultimately enhancing its utility in guiding investor behavior.