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

Item Type Journal paper
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.

Authors Blohm, Ivo; Antretter, Torben; Siren, Charlotta; Wincent, Joakim & Grichnik, Dietmar
Journal or Publication Title Entrepreneurship Theory and Practice
Language English
Subjects economics
HSG Classification contribution to scientific community
HSG Profile Area Global Center for Entrepreneurship + Innovation
Refereed Yes
Date 14 September 2020
Publisher Wiley-Blackwell SSH
Place of Publication Entrepreneurship: Theory and Practice
Number of Pages 38
ISSN 1042-2587
Publisher DOI https://doi.org/10.1177/1042258720945206
Depositing User Corinne Metzger-Wyder
Date Deposited 06 Oct 2020 11:51
Last Modified 01 Nov 2020 01:24
URI: https://www.alexandria.unisg.ch/publications/261136

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Citation

Blohm, Ivo; Antretter, Torben; Siren, Charlotta; Wincent, Joakim & Grichnik, Dietmar (2020) It’s a Peoples Game, Isn’t It?! A Comparison between the Investment Returns of Business Angels and Machine Learning Algorithms. Entrepreneurship Theory and Practice, ISSN 1042-2587

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https://www.alexandria.unisg.ch/id/eprint/261136
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