Crypto minds at risk: ranking cognitive biases among Dutch retail and potential investors
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2025-07-03
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en
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This thesis investigates how five key behavioral biases: herding, overconfidence, loss aversion, regret aversion, and anchoring shape cryptocurrency investment decisions among Dutch retail and potential investors. A mixed-methods design, consisting of the Fuzzy AHP, Likert-scale averages, and regression models, is used to distinguish between what investors believe influences them and what actually drives their investment behavior. The findings show that potential investors perceive herding and regret aversion as more influential, although they show no significant effect on investment propensity. For retail investors, anchoring and overconfidence are perceived as most important, with overconfidence also significantly affecting investment behavior. These findings emphasize the discrepancy between perceived importance and actual behavioral influence and highlight the differences between investor types. These insights contribute to behavioral finance literature and bring practical implications for tailored education and regulatory developments.
Key words: behavioral biases, crypto investing, Fuzzy AHP, regression analysis
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Faculteit der Managementwetenschappen