The Impact of Behavioral Biases on Portfolio Optimization among Investors in the Tehran Stock Exchange: A Behavioral Finance Approach

Abstract

This study aims to examine the impact of major behavioral biases—including overconfidence, herding, anchoring, adjustment, and loss aversion—on portfolio optimization among investors in the Tehran Stock Exchange. The research employed a mixed-method exploratory–explanatory design. In the qualitative phase, grounded theory was used to identify behavioral factors influencing financial decision-making through semi-structured interviews with 15 behavioral finance experts. In the quantitative phase, a questionnaire developed from the qualitative findings was distributed among 384 investors. Data were analyzed using SPSS-27 and AMOS-24 through confirmatory factor analysis and structural equation modeling (SEM). Results revealed that all behavioral biases had significant negative effects on portfolio optimization. The strongest negative impacts were observed for loss aversion (β = -0.35, p = 0.001) and herding (β = -0.34, p = 0.001). Overconfidence (β = -0.28), anchoring (β = -0.21), and adjustment bias (β = -0.19) also demonstrated significant negative effects. The model fit indices indicated acceptable adequacy for the extended model (CFI = 0.93, RMSEA = 0.058, χ²/df = 2.41). Behavioral biases significantly hinder rational decision-making and reduce portfolio optimization efficiency. Integrating behavioral variables into financial models enhances predictive accuracy and provides a more realistic understanding of investor behavior. Behavioral finance education and the adoption of intelligent analytical technologies are recommended to mitigate the negative effects of cognitive and emotional distortions.