Algorithm Aversion in Delegated Investing

Journal of Business Economics, forthcoming; this is the accepted version of doi: 10.1007/s11573-022-01121-9

63 Pages Posted: 6 Nov 2019 Last revised: 21 Nov 2022

Date Written: September 28, 2022


The tendency of humans to shy away from using algorithms—even when algorithms observably outperform their human counterpart—has been referred to as algorithm aversion. We conduct an experiment with young adults to test for algorithm aversion in financial decision making. Participants acting as investors can tie their incentives to either a human fund manager or an investment algorithm. We find no sign of algorithm aversion: participants care about returns, but do not have strong preferences which financial intermediary obtains these returns. Contrary to what has been suggested, participants are neither quicker to lose confidence in the algorithm after seeing it err. However, we find that participants’ inability to separate skill and luck when evaluating intermediaries slows down their migration to the algorithm.

Keywords: Algorithm Aversion, Financial Technology, Asset Management, Delegated Investment

JEL Classification: G11, G23, G41, O33

Suggested Citation

Germann, Maximilian and Merkle, Christoph, Algorithm Aversion in Delegated Investing (September 28, 2022). Journal of Business Economics, forthcoming; this is the accepted version of doi: 10.1007/s11573-022-01121-9, Available at SSRN: or

Maximilian Germann

European Central Bank ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314

Christoph Merkle (Contact Author)

Aarhus University ( email )

Nordre Ringgade 1
DK-8000 Aarhus C, 8000


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