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
Date Written: May 4, 2021
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
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