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The Growth and Performance of Artificial Intelligence in Asset Management, with Clemens Sialm and David X. Xu [Slides]

This paper examines AI adoption in asset management and its investment implications. We document that AI-driven investing is concentrated among hedge funds, particularly those employing macro strategies. AI funds exhibit greater alpha comovement and are launched by investment advisers facing stronger performance incentives. These funds significantly outperformed non-AI hedge funds on a risk-adjusted basis, but their outperformance declined over time and disappeared with the growth of AI-driven investing. Nevertheless, AI funds continued to outperform sibling funds managed by the same advisers. Our findings highlight both the alpha-generating potential and the limitations of AI as a source of investment performance.

Green Investors and Green Transition Efforts: Talk the Talk or Walk the Walk?  [Slides]

This paper develops a method to separately measure a company's efforts in substantive environmental improvements ("walk") and mere promotion of a green image ("talk") by analyzing online job postings. Walk efforts positively predict future environmental performance and data disclosure, while talk efforts do not. Applying this method reveals that sustainable mutual funds in the EU and US hold higher ownership stakes in companies with higher talk efforts, and three major ESG rating agencies award greener scores to these companies, controlling for walk efforts. Evidence suggests sustainable mutual funds invest in companies with higher talk efforts to attract higher fund flows.

Climate Human Capital, Labor Market Frictions, and Corporate Decarbonization, with Zhanbing Xiao and Xin Zheng

Quantitative Investing and Stock Market Price Elasticity, with Francesco Franzoni, Laurent Frésard, and Augustin Landier

We evaluate the impact of quantitative investing on stock market price elasticity by examining portfolio holdings of U.S. equity mutual funds that follow quantitative or other investment strategies. Using the demand estimation approach of  Koijen and Yogo (2019), we find that, at the fund level, stock demand is less elastic for quantitative funds, as one would expect given their fixed investment rules. However, the stock demand of the whole sector of quantitative funds is more elastic to price than for the fundamental sector, suggesting that quantitative funds collectively span a sufficiently wide variety of trading strategies so that their demand reacts sensitively to price moves. This finding is reassuring that the growth of quantitative funds would not make the market more fragile and less able to self-correct.

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