Judge Me on My Losers: Does Adaptive Robo-Advisors Outperform Human Investors during the COVID-19 Financial Market Crash?

45 Pages Posted: 30 Nov 2020 Last revised: 4 May 2021

See all articles by Che-Wei Liu

Che-Wei Liu

Indiana University Bloomington - Kelley School of Business

Mochen Yang

University of Minnesota - Twin Cities - Carlson School of Management

Ming-Hui Wen

National Taipei University of Business - College of Innovative Design and Management

Date Written: May 4, 2021

Abstract

Despite the increasing popularity of robo-advisors (RAs), empirical evidence on their performance, especially during market downturns, is highly limited. We study the impact of using RAs on investment performance during the 2020 financial crisis caused by the COVID-19 global pandemic. We obtain daily portfolio and transaction data of investors on an online investment platform. Besides making investment decisions by themselves, investors can also leverage an RA system offered by the platform. We match RA users with other investors who did not use the RA with similar characteristics before the market crash, then compare their portfolio returns within four weeks after the crash. We find that RA users experienced significantly fewer losses during the market downturn. Moreover, our analyses of trading strategies show that RA users held less risky portfolios, whereas other investors stayed with their status quo and did not reduce the risk of their portfolios, which partly accounted for the performance discrepancy. During the subsequent period of market recovery, we observe that RA users were able to maintain their performance advantage. Overall, by trading adaptively to adjust the portfolio risk levels in response to market movements, the RA system mitigated losses and benefited its users. Further analyses of effect heterogeneity show that younger users or users with less investment experience benefited more from the RA, because they delegated a larger proportion of their assets to be managed by the RA. Our work offers a direct empirical assessment of RAs’ performance during a severe market downturn, and advances the understanding of algorithmic decision-making in the financial markets.

Keywords: financial crisis, robo-advisor, investment, adaptivity, status-quo bias, algorithmic decision-making

Suggested Citation

Liu, Che-Wei and Yang, Mochen and Wen, Ming-Hui, Judge Me on My Losers: Does Adaptive Robo-Advisors Outperform Human Investors during the COVID-19 Financial Market Crash? (May 4, 2021). Available at SSRN: https://ssrn.com/abstract=3737821 or http://dx.doi.org/10.2139/ssrn.3737821

Che-Wei Liu (Contact Author)

Indiana University Bloomington - Kelley School of Business ( email )

1309 E 10th Street, Hodge Hall 4100
Bloomington, IN 47405
United States

Mochen Yang

University of Minnesota - Twin Cities - Carlson School of Management ( email )

19th Avenue South
Minneapolis, MN 55455
United States

Ming-Hui Wen

National Taipei University of Business - College of Innovative Design and Management ( email )

No.321, Sec. 1,
Jinan Rd.
Taipei
Taiwan

HOME PAGE: http://https://profwen.com

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