Behavioral Finance and Predictive Analytics: Understanding Investment Choices of Gen Z Investors

Abstract

Generation Z (Gen Z) investors are increasingly participating in financial markets through digital platforms, mobile applications, and FinTech services. Their investment decisions are influenced not only by financial knowledge but also by behavioral factors such as overconfidence, herd behavior, loss aversion, and Fear of Missing Out (FOMO). This review paper examines the existing literature on behavioral finance and predictive analytics to understand the factors influencing Gen Z investment behavior. The study explores the role of financial literacy, social media influence, and digital investment platforms in shaping investment decisions. It also highlights the growing importance of predictive analytics in identifying behavioral patterns and forecasting investor preferences. Through a thematic review of the literature, the study identifies key trends, research gaps, and future research opportunities in the field. The findings suggest that Gen Z investment behavior is shaped by a combination of psychological, social, financial, and technological factors. Furthermore, predictive analytics provides valuable insights for understanding investor behavior and supporting data-driven investment decisions. The review contributes to the growing literature on behavioral finance and offers implications for investors, financial institutions, educators, policymakers, and researchers.

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