Crypto Investment Psychology: Analysis of the Effect of Overconfidence and Financial Literacy with a Mental Budgeting Approach on Indonesian Retail Investors

Abstract

This study examines the psychological and cognitive mechanisms that drive cryptocurrency investment decisions among Indonesian retail investors by integrating overconfidence, financial literacy, investment interest, and mental budgeting within a serial mediation framework. As the adoption of digital assets accelerates in emerging markets, understanding the behavioral foundations of crypto participation becomes increasingly important. Using a cross-sectional survey of 350 active retail investors and Partial Least Squares Structural Equation Modeling (PLS-SEM), the study evaluates both direct and indirect effects across five key constructs. The findings reveal that overconfidence is the strongest predictor of investment interest and subsequent investment decisions, indicating that emotional overestimation of personal capability remains a dominant behavioral force in high-risk digital trading environments. Financial literacy also significantly influences investment interest and decision-making, although its effects are more rational and structured when compared to overconfidence. Investment interest and mental budgeting exhibit robust sequential mediation effects, demonstrating that investors’ decisions are shaped through a multi-stage psychological process involving affective activation followed by cognitive fund allocation. This suggests that crypto trading behavior is neither purely rational nor purely bias-driven, but rather a hybrid mechanism shaped by interacting behavioral and cognitive paths. The study extends behavioral finance theory by positioning mental budgeting as a central mediator within crypto investment models and highlights limitations of traditional TAM/TPB frameworks in explaining speculative digital asset behavior. Practical implications emphasize the need for financial education that targets cognitive biases, emotional regulation, and high-risk budgeting practices. Overall, the findings contribute to a deeper understanding of psychological decision pathways in rapidly evolving digital financial ecosystems.