Tracking the Market
Passive Investing and the Rise of Mega-Firms
Hao Jiang, Dimitri Vayanos & Lu Zheng
Review of Financial Studies, forthcoming
Abstract:
We study how passive investing affects asset prices. Flows into passive funds disproportionately raise the stock prices of the economy's largest firms, especially those large firms in high demand by noise traders. Because of this effect, the aggregate market can rise even when flows are entirely due to investors switching from active to passive funds. Intuitively, passive flows increase the idiosyncratic risk of large firms in high demand, which discourages investors from correcting the flows' effects on prices. Consistent with our theory, prices and idiosyncratic volatilities of the largest S&P500 firms rise the most following flows into that index.
Transmission of Information from Private to Public Markets
Shrijata Chattopadhyay et al.
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
We report evidence consistent with institutional investors using industry-level information that they obtain from their investments in venture capital (VC) funds to earn excess returns in publicly-traded stocks. We use court rulings regarding the Freedom of Information Act as an exogenous shock affecting the information flow between VC funds and institutional investors to show that the excess returns are explained by information received via this channel. Thus, institutional investors serve as conduits of information from private to public markets. In the process, institutional investors earn higher returns from their VC investments than implied by the cash flows received therefrom.
The Shadow Value of "Public" Information: Evidence from Mutual Fund Managers
Ed deHaan et al.
Stanford Working Paper, July 2025
Abstract:
A standard assumption in the stock-picking literature is that alpha comes from private information, while public information is freely available and priced. We challenge this view by showing that skilled usage of public data, such as accounting and market reports, can also generate consistent alpha among mutual fund managers. Using an "AI analyst" that processes public information at an unusually low cost, we simulate the behavior of an especially skilled public information user. The AI analyst selectively modifies each mutual fund's portfolio each quarter to create counterfactuals that better incorporate public information while preserving funds' styles and risks. Actual fund managers generate $2.8 million in quarterly alpha from 1990 - 2020. Our AI analyst generates an incremental $15.1 million per quarter, outperforms 91% of managers over their careers, and easily dominates managers using non-standard objective functions. These findings demonstrate that skillful use of public information can be a first-order determinant of investment performance, and they provide a point estimate of its value in realistic settings.
The Prestakes of Stock Market Investing
Francesco Bianchi et al.
NBER Working Paper, October 2025
Abstract:
How rational is the stock market and how efficiently does it process information? We use machine learning to establish a practical measure of rational and efficient expectation formation while identifying distortions and inefficiencies in the subjective beliefs of market participants. The algorithm independently learns, stays attentive to fundamentals, credit risk, and sentiment, and makes abrupt course-corrections at critical junctures. By contrast, the subjective beliefs of investors, professionals, and equity analysts do little of this and instead contain predictable mistakes -- prestakes -- that are especially prevalent in times of market turbulence. Trading schemes that bet against prestakes deliver defensive strategies with large CAPM and Fama-French 5-factor alphas.
Stock market participation and macro-financial trends
Francesco Saverio Gaudio
Journal of Monetary Economics, December 2025
Abstract:
The U.S. stock market participation rate has risen substantially since the 1980s. This paper studies the macro-financial implications of such structural change in a production-based asset-pricing model with external habits, which make investors' effective risk aversion time-varying and decreasing with consumption. In this setup, higher participation generates a fall in the risk-free rate and an increase in the equity premium, consistent with recent U.S. trends. These novel results stem from a decline in the average participant's risk tolerance, due to the entry of lower-consumption households relative to incumbents. Micro-level evidence from the U.S. Consumer Expenditure Survey supports the main model mechanism.
Regulatory Leakage Among Financial Advisors: Evidence From FINRA Regulation of "Bad" Brokers
Colleen Honigsberg, Edwin Hu & Robert Jackson
Stanford Working Paper, September 2025
Abstract:
The regulatory framework for financial advisors is fragmented, with multiple state and federal regulators. Prior empirical literature on financial advisors has largely focused on a single subset of financial advisors, but we create a database containing brokers regulated primarily by FINRA, investment advisers regulated by the SEC or state securities regulators, and insurance producers regulated by state insurance regulators. There is significant overlap across the regimes; more than 40% of the advisors in our data are registered with more than one regulator. This overlap has implications for labor allocation and market discipline. For example, of the individuals who exit FINRA's broker regime, 79% were jointly registered in insurance upon exiting FINRA's regime. This could be efficient if it reflects bad actors who transition to lower risk work, but our evidence shows that these advisors continue to engage in financial planning after they move to the insurance side, as over 90% maintain licenses to sell annuities. Moreover, those who committed misconduct when regulated by FINRA continue to have heightened levels of misconduct in insurance. Our findings have additional implications for regulatory discipline. In 2018 and 2019, FINRA proposed rules designed to nudge "bad" brokers out of the industry. We show that these proposals caused thousands of high-risk brokers to exit the FINRA broker regime, but that the majority of these individuals did not leave financial services — 98% are currently registered with state regulators as insurance producers.
Data-Driven Investors
Maxime Bonelli
Review of Financial Studies, forthcoming
Abstract:
How does the increased use of data technologies, like machine learning, by financial intermediaries affect the allocation of capital towards innovation? I study this question in the context of startup financing by venture capitalists (VCs). While VCs adopting data technologies become better at screening startups similar to those in historical data, they tilt their investments towards this pool and become concurrently less likely to finance innovative startups that achieve rare major success. Plausibly exogenous variations in VCs' screening automation suggest that these effects are causal. These findings highlight how investors' adoption of data technologies can have real effects through innovation financing.
Alumni Networks in Venture Capital Financing
Jon Garfinkel et al.
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
One-third of deals in the venture capital (VC) market involve a founder and investor from the same university. Venture capitalists are more likely to invest in, and place larger bets on, startups with founders from their alma mater. These deals are also more likely to lead to IPOs post-funding. Tests using VC partner turnover confirm a direct link between education ties and funding likelihood. Taken together, our results suggest that university connections facilitate improved deal-making and outcomes, rather than diverting funds toward lower-quality startups.
Invest Local or Remote? The Effects of COVID-19 Lockdowns on Venture Capital Investment Around the World
Pengfei Han et al.
Management Science, forthcoming
Abstract:
We find the "death of distance" in venture capital (VC) investment caused by the COVID-19 pandemic: VCs invest in more distant startups during the COVID-19 lockdowns, and such effects continue after the economy reopens. The death of distance is more pronounced when there is better internet infrastructure, lower information asymmetry between VCs and entrepreneurs, and smaller deal size. The pandemic-spurred advancement and adoption of remote communication technology contribute to the documented observations. The death of distance in VC investment implies more vibrant entry of outside VCs into geographically localized markets, intensified competition among VCs, and mitigated regional inequality of entrepreneurial access to VC financing.
The Accessibility of SEC Filings and Media Information Production
Xiaoli (Shaolee) Tian, Yifang Xie & Miaomiao Yu
Georgetown University Working Paper, June 2025
Abstract:
The implementation of EDGAR, which substantially enhanced public access to SEC filings, represents a significant increase in regulatory transparency. This study examines its impact on media information production. We find a significant rise in full-length corporate news articles in The Wall Street Journal following EDGAR's launch. This effect persists when we restrict the analysis to articles that are most indicative of information production or are more likely related to financial performance. Consistent with reduced access costs as the primary mechanism, the main effect is concentrated when journalists are located outside cities where hard copies were previously available and farther from firm headquarters. The effect is also concentrated among firms with higher expected reader demand. Additionally, media coverage following EDGAR implementation is associated with a greater likelihood of M&A withdrawal. Overall, these findings imply that EDGAR facilitates media information production, thereby enhancing the media's role as an external governance mechanism.