Abstract
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.
Original language | English |
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Peer-reviewed scientific journal | Entrepreneurship Theory and Practice |
ISSN | 1042-2587 |
DOIs | |
Publication status | Published - 14.09.2020 |
MoE publication type | A1 Journal article - refereed |
Keywords
- 512 Business and Management
- business angels
- artificial intelligence
- machine learning
- biases
- investment experience
- decision making