Behavioral finance challenges traditional market theories by demonstrating how cognitive biases and emotional factors systematically shape investment decisions. This study examines four key biases: overconfidence, loss aversion, herding, and anchoring, and their combined impact on investment performance among retail and institutional investors. A cross-sectional quantitative survey of 500 respondents from global financial markets was conducted using validated psychometric tools to assess bias levels and a composite performance index derived from self-reported and verified returns. Data analysis through descriptive statistics, Pearson correlations, and multiple regression in SPSS revealed that overconfidence was the strongest positive predictor of performance, suggesting that well-calibrated confidence can enhance returns, while loss aversion had the most substantial negative influence, reflecting tendencies to avoid profitable risks or retain underperforming assets too long. Herding showed a smaller but significant positive effect, indicating that trend-following can yield short-term gains under favorable conditions, whereas anchoring had a weak, statistically insignificant negative association. Institutional investors outperformed retail investors slightly, with less variability, likely due to greater resources, structured decision-making, and superior market access. These results underscore the importance of bias-aware investment strategies, targeted financial education to reduce loss aversion among retail investors, and safeguards against excessive herding in institutional contexts. Integrating behavioral finance insights into portfolio management and policy frameworks can improve market efficiency, resilience, and long-term investment performance.
Vijayakumar et al. (Mon,) studied this question.
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