The Role of Behavioral Economics in Shaping Investment Decisions in Emerging Financial Markets

Abstract

This study investigates the role of behavioral economics in shaping investment decision-making in emerging financial markets, with a particular focus on the interaction between behavioral biases, digital finance adoption, financial literacy, and machine learning applications. Using a mixed-methods experimental approach, the study integrates investor-level behavioral data, market performance indicators, sentiment measures, and computational modeling techniques. The results reveal that behavioral biases such as herding, loss aversion, and overconfidence significantly influence investment outcomes, contributing to return volatility and suboptimal portfolio decisions. Digital adoption is found to improve investment performance on average, yet it does not fully mitigate behavioral distortions, especially under heightened market sentiment. Financial literacy plays a crucial moderating role, reducing bias-driven inefficiencies and stabilizing returns. Furthermore, machine learning models augmented with behavioral and sentiment variables demonstrate superior predictive accuracy compared to traditional finance-based models, underscoring the value of behavior-aware computational frameworks. Despite these gains, the findings highlight persistent challenges related to data limitations and model interpretability in emerging markets. Overall, the study provides strong empirical support for integrating behavioral insights with advanced analytical techniques to improve investment prediction, policy design, and financial decision-making in emerging economies.