Brain activity in cryptocurrency investment

This study explores individual investor behaviors diverging from traditional finance theories, through a neurofinance lens. Focusing on dynamic cryptocurrency markets, it comprehensively compares cognitive, behavioral, and neurophysiological decision-making processes in cryptocurrency investors and non-investors. The research employed a four-stage, multi-faceted methodology. Demographic data and financial risk perceptions were collected via questionnaires in the initial and final stages. During the second and third stages, participants underwent a Modified Iowa Gambling Task (IGT) simulation with Electroencephalography (EEG) recordings to assess risky decision-making tendencies. Neurophysiological data, including event-related potentials (ERP) and frontal asymmetry, were analyzed. Results show cryptocurrency investors possess higher financial literacy and risk tolerance than non-investors, yet are also more acutely aware of the unique risks in crypto markets. Behaviorally, these investors demonstrated faster response times in the IGT task, indicating increased cognitive efficiency or automatization. Neurophysiological analyses revealed that the primary difference between groups stems not from motivational tendencies but from how financial outcomes are processed. Specifically, cryptocurrency investors exhibited a statistically significantly lower P300 response to financial losses. This suggests they perceive losses as less significant or surprising at a neural level, having cognitively adapted to highly volatile environments. This thesis contributes new insights to neurofinance by showing how experience shapes the neural basis of financial decision-making. The findings underscore the importance of considering not only personality traits but also neurocognitive adaptation mechanisms in understanding human behavior within risky financial markets.