This study aims to investigate the financial sentiments reflected in the Initial Public Offering (IPO) prospectus and studies its connection with the listing performance and short-term returns. This study is among the few works that use sentiment analysis for IPO prospectuses. This study focuses on the Indian market, a major emerging economy.
The authors compute sentiment scores for uncertainty and positivity using the Loughran–McDonald (LM) dictionary and text analysis modules in Python. In total, 662 Indian IPOs listed from 2007 to 2025 are taken for the study. The relation between sentiment scores and IPO returns is calculated using regression models.
The analysis indicates a positive correlation between uncertainty sentiments and IPO returns. The impact of prospectus sentiment decreases after the listing day and becomes insignificant after 15 days.
This research provides empirical insights into the nexus between prospectus disclosures and IPO listing performance, offering stakeholders a robust framework for informed market participation. The findings validate the theoretical underpinnings of Signaling and Market Microstructure theories in the current primary market.
This study contributes to the scarce literature on prospectus sentiment analysis of IPOs in the Indian market. By bridging qualitative and quantitative determinants, the study provides additional insights to the various stakeholders involved.
