The Impact of Robo-Advising on Individual Investors' Behavioral Biases: A Behavioral Finance Review
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Keywords
robo-advising, behavioral finance, individual investors, fintech, asset allocation
Abstract
With the penetration of financial technology, artificial intelligence and big data into wealth management, robo-advising has been one of the useful instruments for individual investors. This review discusses whether robo-advisors can mitigate behavioral biases of individual investors from a behavioral finance perspective. Through a review of relevant literature on robo-advising, modern portfolio theory, prospect theory, disposition effect, overtrading and limited attention, this paper finds that robo-advisors may enhance investor behavior via risk profiling, diversified asset allocation, automatic rebalancing and rule-based execution. These mechanisms could reduce overconfident trading, chasing returns, concentration of holdings and emotional decisions. Nevertheless, robo-advising is unable to completely eradicate irrational behavior. Its efficacy is subject to the validity of risk questionnaires, algorithmic transparency, platform incentives, investor financial literacy and regulatory scrutiny. Inspired by The Man Who Solved the Market and A Man for All Markets, this review also contends that the value of models does not reside in delivering returns, but in fostering probability thinking, discipline and risk control. Finally, this paper proposes enhancements in transparency, risk disclosure, investor education and conflict-of-interest regulation.
References
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