It’s a Peoples Game, Isn’t It?! A Comparison Between the Investment Returns of Business Angels and Machine Learning Algorithms

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 algori...

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Bibliographic Details
Published in:Entrepreneurship theory and practice 2022-07, Vol.46 (4), p.1054-1091
Main Authors: Blohm, Ivo, Antretter, Torben, Sirén, Charlotta, Grichnik, Dietmar, Wincent, Joakim
Format: Article
Language:English
Subjects:
Algorithms
Cognitive bias
Decision analysis
Investments
Machine learning
Return on investment
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Summary: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.
ISSN:1042-2587
1540-6520
DOI:10.1177/1042258720945206