Behavioral biases

The publication of financial statements, a vital corporate communication tool, significantly influences behavioral biases in both individuals and organizations. While the importance of behavioral factors for investors is well recognized, the impact of financial statement releases on these biases in the Iranian capital market has yet to be thoroughly examined. This study investigates the effect of financial statement releases on two key biases: loss aversion and overconfidence among investors. By employing both quantitative and qualitative research methods, comprehensive data was collected from the Iranian stock market. For the analysis of loss aversion, a sample of 111 companies over six years (2017–2022) was selected using the systematic elimination method, while overconfidence bias was assessed at the market level. An event study method was used to measure the impact of financial statement releases on these biases. To analyze loss aversion, a regression model using the Dynamic Panel Data (GMM) method was applied, and for overconfidence, a Vector Autoregression (VAR) model was estimated during the financial statement release period at the market level. The findings show that investor’s exhibit heightened loss aversion during financial statement releases, and overconfidence bias was also evident, with investors attributing positive market outcomes to themselves and acting more aggressively in subsequent transactions. Based on the results, investors should consider behavioral bias patterns in their decision-making and incorporate technical analysis. Additionally, companies should ensure transparency and accuracy in their financial statements while remaining attentive to market behaviors and reacting promptly to changes.

The first and most important goal of investors in the stock market is to grow their investment portfolio. Meanwhile, behavioral factors emerge as one of the most important factors that prevent optimal decision-making. Many studies have identified and introduced these factors. However, prioritizing these factors and identifying causal relationships between these factors has been neglected. Therefore, this study was conducted to prioritize and explain causal relationships between the most important behavioral biases of retail investors in the Tehran Stock Exchange. Given the qualitative and quantitative nature of the data used in this study, a Fuzzy Cognitive Mapping Approach was used. Therefore, 30 behavioral biases were discussed and examined by 15 experts, and the causal relationships between them were explained and prioritized. Accordingly, the distribution effect biases, the Salience data Bias, and the Loss Aversion Bias were introduced as the most important, and the forgiveness biases, Evolutionary Bias, and Money Illusion Bias were introduced as the least important behavioral biases. Also, behavioral biases were grouped into four categories, which in order of importance are: perceptual, experiential/informational, personality, and emotional.