Journal
ENTREPRENEURSHIP THEORY AND PRACTICE
Volume 46, Issue 4, Pages 1054-1091Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/1042258720945206
Keywords
business angels; artificial intelligence; machine learning; biases; investment experience; decision making
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This study compares the investment returns of a machine learning algorithm with those of angel investors, finding that only experienced investors who manage to suppress their cognitive biases outperform the algorithm.
Investors increasingly use machine learning (ML) algorithms to support their early stage investment decisions. However, it remains unclear if algorithms can make better investment decisions and if so, why. Building on behavioral decision theory, our study compares the investment returns of an algorithm with those of 255 business angels (BAs) investing via an angel investment platform. We explore the influence of human biases and experience on BAs' returns and find that investors only outperformed the algorithm when they had extensive investment experience and managed to suppress their cognitive biases. These results offer novel insights into the role of cognitive limitations, experience, and the use of algorithms in early stage investing.
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