Paper Details

Name: Kesu Singh
Country: India

Year: 2026
Volume: Volume-13, Issue-1 (January-June)
Page Number: 352-361
DOI: https://doi.org/10.5281/zenodo.20524078

Traditional financial prospects, like Capital Asset Pricing Model (CAPM), ignore how actual people really make decisions and instead place all investment decisions in the hands of rational individuals. However, in practice, investing behaviour varies. Examining behavioral biases in investing the factor influencing the decision making by the investors is the main agenda of this study. To gather the opinions of millennial investors, a questionnaire was created and distributed. To explain the process of selecting an investment, the terms loss aversion (LA), regret aversion (RA) effect, and overconfidence (OC) bias were employed. Artificial Intelligence (AI) has emerged as a powerful tool in managing these biases and improving investment decision-making processes. AI-driven algorithms are capable of analyzing vast amounts of financial data, market sentiment, and investor behavior to identify and understand various emotional biases such as overconfidence, loss aversion, and herd mentality. The findings demonstrated that all three biases—LA, RA, and OC bias—have a significant and beneficial impact on investment decisions. According to the findings, active
investors display more OC prejudice, whilst idle traders are more likely to be subject to RA and LA bias. In terms of educating customers and promoting improved decision-making, the study's findings may have significant policy implications for analysts and investment decision-makers.