Man versus machine: on artificial intelligence and hedge funds performance

Klaus Grobys, James W. Kolari and Joachim Niang

Applied Economics, 2022, vol. 54, issue 40, 4632-4646

Abstract: Employing partially hand-collected data, sample hedge funds are formed into four categories depending on their level of automation. We find that hedge funds with the highest level of automation outperform other hedge funds with more reliance on human involvement. Also, we find that a man versus machine zero-cost strategy that is long hedge funds portfolio with highest level of automation and short those with highest level of human involvement yields a highly significant spread of at least 50 basis points per month. We conclude that automation plays an important role in the profitability of the hedge fund industry.

Date: 2022
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DOI: 10.1080/00036846.2022.2032585

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