Working Papers
Do Mutual Funds Benefit from the Adoption of AI Technology? with Jian Yuan
Presentations: 2025 ABFR Forum (Scheduled), NBER conference: Big Data, Artificial Intelligence, and Financial Economics, 2024 New Zealand Finance Meeting, Greater Bay Area Finance Workshop, Generative AI in Finance
Abstract: This paper examines the impact of AI technology adoption in the mutual fund industry by developing a new measure of AI adoption based on hiring practices. I find that this measure can predict fund performance. Funds with a high AI ratio outperform non-AI funds, after controlling for relevant variables. Further empirical evidence indicates that this outperformance is driven by improved stock picking skill rather than market timing skill. Mutual funds that adopt AI technology tend to tilt their portfolios toward stocks with voluminous information, and these stocks contribute to their superior performance. These findings suggest that AI is good at processing large amounts of data and providing a more comprehensive analysis of stocks.
The Implicit Government Guarantee as a Spillover Channel: Evidence from Chinese Local SOE Bond Market, with Kai Li
Presentations: CFRC 2024, CICF 2024, Asian Meeting of the Econometric Society 2024
Abstract: We demonstrate that the implicit government guarantee (IGG) can produce a spillover effect, transforming an idiosyncratic shock into a systemic shock. A model has been developed to illustrate the mechanism. The pivotal channel is that, when investors are unable to distinguish between an idiosyncratic default and a policy regime shift, they will revise their beliefs regarding the IGG for all default cases. We provide empirical evidence for the model by examining the unforeseen default event of Yongcheng Coal Group in November 2020. This event is regarded as an exogenous shock that eroded investors' confidence in the IGG, particularly that of local governments in precarious financial positions. Employing difference-in-differences regression analysis, we observe a 50-basis-point increase in the credit spread for SOE bonds in a weak financial condition relative to those in a strong financial condition, which represents a significant 30\% of the average credit spread. Further analysis indicates that the shifts in IGG-related beliefs prompted by the Yongcheng default are more pronounced for bonds with lower ratings, aligning with our model's predictions. Our results echo the great effort made by the Chinese central government to reduce the IGG provided by local governments.
Do Mutual Funds Perform Worse When They Get Larger? Anticipated Flow versus Unanticipated Flow
Presentations: FMA Annual Meeting 2024
Abstract: This paper studies the impact of AI technology on the mutual fund industry. I develop a new measure of AI adoption based on hiring practices and find that this measure can predict fund performance. The funds with high AI ratio outperform non-AI funds, after I controlling for standard factors and fund characteristics. Further empirical evidence shows that funds with a high AI ratio tilt their portfolios toward high information intensity stocks, indicating that mutual funds benefit from AI technology adoption by improving their information capacity. Consistent with this channel, I find that the outperformance of these mutual funds mainly comes from better stock picking skills. Finally, AI technology adoption has a negligible effect on fund manager turnover.
Publication
Compensation for Illiquidity in China: Evidence from an Alternative Measure, with Guanying Wang, North American Journal of Finance and Economics and Finance 53 (2020): 101187