Algorithm Aversion in Financial Investing

Published in Working Paper, 2019

Recommended citation: Germann, Maximilian and Christoph Merkle. (2019). "Algorithm Aversion in Delegated Investing." Working Paper.

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 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: Investors care about returns, but do not have strong preferences which intermediary obtains these returns. Contrary to what has been suggested, investors are also not quicker to lose confidence in the algorithm after seeing it err. However, we find that investors are unable to fully separate skill and luck when evaluating either intermediary.


JEL codes: G11, G23, G41, O33.

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