Digital Finance and Investor Welfare: Identification Based on Mutual Fund Livestreaming
NING Wei, ZHUANG Yuan, JIANG Fuwei
School of Finance, Southwestern University of Finance and Economics;China School of Banking and Finance, University of International Business and Economics;Center for Macroeconomic Research/School of Economics/ The Wang Yanan Institute for Studies in Economics, Xiamen University
Summary:
Digital finance is transforming the production and delivery of wealth management services, but its consequences for household investors remain ambiguous. Digital platforms may lower information and communication frictions, broaden access to professional financial knowledge, and improve investment decisions. Yet platform traffic allocation and scale-oriented sales incentives may also intensify persuasion, attention capture, and conflicts of interest. This paper studies mutual fund livestreaming, a rapidly expanding digital-finance application that combines product promotion, market commentary, risk disclosure, and real-time communication. We examine whether livestreaming merely digitizes conventional fund distribution or also improves investor welfare through information provision and financial education. We combine proprietary livestreaming records from Alipay with anonymized account-level viewing, holdings, transactions, investment gains and losses, and demographic information for a random sample of 50,000 active mutual fund investors. The underlying fund-level data cover actively managed equity-oriented funds from November 2020 to October 2022 and are supplemented with fund characteristics, net asset values, and portfolio data from Wind. We identify the effect of investors’ first exposure to a fund livestream using a staggered difference-in-differences design. Treated investors are matched to investors who never watch a livestream on the basis of pre-treatment wealth, portfolio holdings, returns, net flows, age, and city characteristics. The regressions include investor and time fixed effects, with two-way clustered standard errors. Event-study tests, alternative variable definitions, sample restrictions, subsample analyses, and an instrumental-variable strategy exploiting within-family crowding-out of livestream resources further address selection and endogeneity concerns. The evidence first reveals a significant sales-reach effect: after viewing livestreams, investors subscribe more, redeem less, and record higher net purchases. More importantly, the increase in purchases is accompanied by better investment outcomes rather than greater risk-taking. Relative to matched non-viewers, viewers earn higher portfolio returns and excess returns, experience lower return volatility, and achieve higher Sharpe ratios. In the baseline difference-in-differences estimates, next-month portfolio returns rise by 0.80 percentage points, excess returns rise by 0.40 percentage points, volatility declines by 0.69 percentage points, and the Sharpe ratio increases by 0.13. The effect is not confined to the funds whose livestreams investors actually watch. Funds held but not viewed also exhibit improved returns, lower volatility, and better risk-adjusted performance, indicating a within-portfolio spillover. The benefits are persistent: over three-, six-, and twelve-month horizons, viewers’ cumulative returns increase by 0.72, 3.65, and 8.59 percentage points, while corresponding return volatility declines by 0.31, 4.13, and 5.21 percentage points respectively. Mechanism tests support an investor-education interpretation. Livestream exposure weakens investors’ tendency to chase historical performance, high rankings, lottery-like returns, and salient payoff signals. It also reduces portfolio turnover, the fraction and number of funds traded, and purchases of new funds. In addition, viewing lowers overconfidence and mitigates the disposition effect by reducing premature sales of winning funds and increasing the realization of losing positions. Taken together, these findings suggest that livestreams improve investors’ information processing, risk understanding, and trading discipline across fund selection, trading, belief formation, and portfolio management. The evidence therefore indicates a systematic improvement in decision quality rather than a temporary response to platform attention or promotional content. This paper contributes to the literature by providing direct account-level evidence on the welfare effects of a specific digital wealth-management service, distinguishing investor service from digital persuasion, and linking portfolio outcomes to four canonical behavioral biases within a unified framework. The findings imply that regulatory framework should integrate digital technologies, information presentation, recommendation algorithms, and realized investor welfare; require balanced disclosure of returns and risks; and discourage traffic-driven promotion and excessive transaction inducement. Digital platforms can also be incorporated into public investor-education systems, while wealth-management institutions should shift from seller-driven distribution toward buyer-oriented advisory services centered on investors’ long-term interests. Future research may combine account data with livestream transcripts, video features, presenter characteristics, and real-time interactions to identify which content elements generate the observed welfare gains and whether the results generalize across platforms, products, and market cycles.
宁炜, 庄园, 姜富伟. 数字金融的投资者福利效应——基于基金直播数据的识别[J]. 金融研究, 2026, 554(8): 170-187.
NING Wei, ZHUANG Yuan, JIANG Fuwei. Digital Finance and Investor Welfare: Identification Based on Mutual Fund Livestreaming. Journal of Financial Research, 2026, 554(8): 170-187.
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