Man versus machine : on artificial intelligence and hedge funds performance
Grobys, Klaus; Kolari, James W.; Niang, Joachim (2022-04-22)
Grobys, Klaus
Kolari, James W.
Niang, Joachim
Taylor & Francis
22.04.2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe202301031337
https://urn.fi/URN:NBN:fi-fe202301031337
Kuvaus
vertaisarvioitu
© 2022 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Economics on 22 Apr 2022, available online: http://www.tandfonline.com/10.1080/00036846.2022.2032585
© 2022 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Economics on 22 Apr 2022, available online: http://www.tandfonline.com/10.1080/00036846.2022.2032585
Tiivistelmä
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.
Kokoelmat
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