Impact of Behavioral Biases on Wealth Management Decisions of Retail Investors in India

The increasing participation of retail investors in financial markets has highlighted the importance of understanding the psychological factors influencing investment decisions. This study examines the impact of behavioral biases on the wealth management decisions of retail investors in India, focusing on four key biases: overconfidence, herding behavior, loss aversion, and anchoring bias. The research is based on primary data collected from a sample of 320 respondents using a structured questionnaire measured on a five-point Likert scale. Descriptive statistics and multiple regression analysis were employed using IBM SPSS Statistics to analyze the data. The findings reveal that behavioral biases significantly influence wealth management decisions, indicating that investor behavior deviates from traditional rational models. Among the biases, loss aversion emerged as the most influential factor, negatively affecting decision-making by promoting overly conservative investment strategies. Overconfidence was found to positively influence decision-making, often leading to excessive reliance on personal judgment. Herding behavior and anchoring bias also showed significant impacts, reflecting the role of social influence and cognitive shortcuts in shaping investment choices. The results suggest that multiple biases operate simultaneously, leading to complex and often suboptimal financial decisions. The study contributes to the growing body of literature in Behavioral Finance by providing an empirical analysis of the combined effect of behavioral biases on wealth management decisions in the Indian context. It also offers practical implications for financial advisors, institutions, and policymakers by emphasizing the need to incorporate behavioral insights into financial planning and investor education. The study highlights the importance of improving investor awareness and developing strategies to mitigate the adverse effects of behavioral biases for more effective wealth management.