Behavioral Finance Experiments: A Systematic Review of Recent Literature

Abstract

This study presents a systematic review of experimental research in behavioral finance published between 2020 and 2023, focusing on cognitive biases, decision-making processes, and market dynamics. By analyzing laboratory and field-based experiments, as well as hybrid approaches integrating real-world trading data, the review identifies loss aversion, overconfidence, and herding behavior as the most consistently observed biases affecting investor decisions. The findings reveal that these biases persist across various experimental designs, influencing trading activity, risk perception, and collective market behavior, particularly under conditions of uncertainty such as the COVID-19 pandemic. Methodological diversification, including the use of online platforms, has enhanced participant diversity and improved the external validity of results. The review also underscores the practical implications of experimental insights for policy, investor education, and market regulation, highlighting the role of framing effects, feedback frequency, and transparency measures in mitigating irrational decision-making. These results demonstrate that experimental designs grounded in robust theoretical frameworks remain crucial for advancing the predictive and prescriptive capabilities of behavioral finance.