Abstract
Although the robo-advisor has garnered significant attention, its impact on market performance remains a topic of exploration. This study focuses on Chinese ETF funds to examine the influence of robo-advisors on their returns and additionally assesses the significance of potential ETF features for robo-advisors. The empirical analysis, which encompassed 798 ETF funds in China, indicates that the robo-advisor can enhance ETF returns to a certain extent. According to the importance evaluation through a commonly-utilized machine learning model known as the random forest, this study reveals that the influence of a robot advisor on the average return of ETF funds is comparatively less significant than that of other risk and return indicators. Notably, for the robo-advisor, the most crucial factors are the risk attributes associated with the ETF funds.
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