Cryptocurrency Investment Behavior: A Machine Learning Perspective

Abstract

Cryptocurrency is a form of digital currency that is increasingly chosen by individuals as an investment option. It is based on blockchain technology, which removes the need for banks or other financial intermediaries in transactions. This study focuses on Millennials, defined as individuals aged 25 to 45, who manage their own finances and are familiar with digital technologies, making them more inclined to explore cryptocurrency investments.The research investigates the factors that influence Millennials’ decisions to invest in or avoid cryptocurrencies by using the Technology Readiness Index (TRI) and the UTAUT model. Data was collected through an online survey using a five-point Likert scale to assess levels of optimism, innovativeness, discomfort, and insecurity toward technology.The findings indicate that optimism and innovativeness act as motivating factors encouraging investment, while discomfort and insecurity serve as barriers due to concerns about complexity, safety, and market volatility. Among the factors, performance expectancy emerges as the strongest predictor of investment intention, followed by effort expectancy and facilitating conditions. Social influence has only a minimal impact.To support these findings, machine learning techniques were applied, where both Logistic Regression and Support Vector Machine (SVM) models achieved a high accuracy rate of 96%. Based on the results, the study recommends simplifying cryptocurrency platforms, increasing transparency, strengthening user education, and enhancing technical support to encourage a safer and more informed approach to cryptocurrency investment among Millennials.