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All Journal Jurnal Reviu Akuntansi dan Keuangan
Muhammad Fahmi Syardhana
Fakultas Ekonomi, Universitas Islam Negeri Maulana Malik Ibrahim, Kota Malang, Indonesia
Economics, Econometrics & Finance

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Behavioral Bias and Risk Perception in Cryptocurrency Investment Decisions of Generation Z Muhammad Fahmi Syardhana; Maretha Ika Prajawati
Jurnal Reviu Akuntansi dan Keuangan Vol. 15 No. 3 (2025): Jurnal Reviu Akuntansi dan Keuangan
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jrak.v15i3.40776

Abstract

Purpose: This research aims to examine the influence of herding and overconfidence bias, as well as gambler’s fallacy on investment decisions among Generation Z cryptocurrency investors in Malang City. Methodology: This quantitative research comprised 96 respondents selected using purposive sampling. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test direct and mediating relationships among variables. Findings: The results showed that overconfidence bias had a significant positive effect on investment decision, while herding bias and gambler’s fallacy did not directly affect the variable. However, herding and overconfidence bias significantly influenced risk perception. The relationship between cognitive bias and investment decisions was not influenced by risk perception. Practical implications: The results report the need for targeted behavioral-based financial education, specifically for young and inexperienced investors in high-risk asset classes such as cryptocurrency. Recognizing and managing cognitive bias particularly overconfidence is essential to improve investment decisions quality. Originality/value: This research contributes by integrating behavioral finance, heuristic theory, and risk perception into the context of Generation Z investors in cryptocurrency market. The segment of cryptocurrency market has been underexplored in previous research.
Co-Authors Maretha Ika Prajawati