Objective

In the complex and ever-changing world of financial markets, behavioral finance theory, as a novel approach, examines the impact of psychological factors on investor behavior. Sentiment is one of the factors that can significantly influence investors' financial decision-making and consequently affect stock returns. Investors make decisions based on various sentiments, which can lead to irrational behavior and unexpected fluctuations in the market. These sentimental behaviors can sometimes cause significant changes in stock prices. Therefore, understanding the impact of sentiment on stock returns is particularly important for investors, analysts, and financial policymakers. In this regard, this study examines the effect of investor sentiment on stock returns in the Tehran Stock Exchange using a panel quantile regression approach. This research aims to identify behavioral patterns of investors and gain a deeper understanding of how sentiment affects their financial performance. Given the importance of this topic, the results of this study can assist investors and financial policymakers in making optimal decisions.



Methods

The statistical population of the present study consists of active companies in the Tehran Stock Exchange. To conduct this research, 175 companies were selected from the active companies on the Tehran Stock Exchange using screening and systematic elimination. The research data were collected monthly over a period of 4.5 years, from March 2019 to September 2023, using library research methods for these 175 active companies. The variables used in this study include stock returns, sentiment index, firm characteristics, and macroeconomic variables. To perform the analysis, the panel quantile regression method was employed, allowing for the examination of the effect of variables on stock returns at different return levels. This method enables researchers to accurately assess the impact of investor sentiment under varying market conditions.



Results

Results from the model estimation using the panel quantile method indicate that, in the 0.2 to 0.9 quantiles, investor sentiment has a positive and significant effect on stock returns. Additionally, as the quantiles increase, the coefficient of sentiment on stock returns rises significantly. In this study, to reveal the dynamic effect of investor sentiment on stock returns, sentiment effects were examined and compared across one-month, three-month, and six-month forecast horizons. These results demonstrate the significance of sentiment's impact on stock returns over different time horizons. Therefore, investor sentiment significantly affects stock returns across all timeframes. Moreover, the increasing trend of the sentiment coefficient, along with rising quantiles, was observed in all three time horizons. According to the results, the intensity of sentiment's impact on stock returns varies across different quantiles, with a significant increase in sentiment's effect at higher return levels. These findings suggest that investors are more influenced by sentiment when stock returns are high and may exhibit biases in their evaluations of stock value. Additionally, the results show that dollar price growth, the book-to-market ratio, and beta have a positive and significant impact on stock returns. In contrast, variables such as inflation, oil price growth, gold price growth, and market value negatively and significantly impact stock returns. These findings emphasize the importance of considering investor sentiment alongside firm characteristics and macroeconomic factors.



Conclusion

This study demonstrates that investor sentiment plays a significant role in determining stock returns and should be considered in trading and investment strategies. Particularly when stock returns are high, investors should be more cautious in evaluating stock values to avoid biases caused by sentiment. Therefore, it is suggested that, in addition to considering factors such as systematic risk, company size, and macroeconomic variables, investor sentiment should also be an integral part of investment strategies. This approach can help improve investment decisions and enhance the efficiency of financial markets.