An Empirical Investigation of the Impact of Retail Investors' Sentiment on their Investment Decisions

The current study aims to investigate the impact of retail investors' sentiment by taking overconfidence, self-attribution, overreaction, and underreaction as antecedents of investor sentiment on their investment decisions. The study uses a cross-sectional research design, and a structured questionnaire was designed to obtain responses using a snowball sampling technique. A total of 125 usable responses were collected via an online survey for data analysis. The study applied a two-staged "Partial Least Square-Structural Equation Modeling (PLSSEM)" and "Artificial Neural Network (ANN) approach" for data analysis and hypothesis testing. The study outcomes demonstrate that overconfidence, self-attribution, overreaction, and under-reaction significantly impact investors' decisions. Further, the study found that overreaction is the most influencing and overconfidence is the least influencing behavioral bias that affects investors' investment decisions. The insights of the study are relevant for retail investors and financial advisors. The study results provide evidence that retail investors are predisposed to different behavioral biases. So, understanding the influence of these biases will help them make profitable investment decisions. Similarly, financial advisors can take the study's insight and guide their clients regarding financial matters by considering the potential impact of different behavioral biases.