Investing Opportunities
No Exit
Brian Broughman, Matthew Wansley & Samuel Weinstein
NYU Law Review, forthcoming
Abstract:
Fast-growing startups in search of capital and liquidity have traditionally sought to exit the private capital market through M&A or IPO. Until recently, antitrust enforcers rarely challenged startup acquisitions. But under the Biden administration, enforcers worried about the growing dominance of Big Tech sued to block more startup deals. Since antitrust restricts M&A but not IPOs, one might expect that greater antitrust enforcement would cause startups to substitute one kind of exit for another, leading to more IPOs. That did not happen. While M&A and IPOs both provide liquidity, they are not perfect substitutes. We model heterogeneity in IPO and M&A pricing to explore how increased antitrust enforcement impacts venture capital. Economies of scale and scope, synergies, regulatory costs, market power, and market cyclicality can cause IPO valuations to fall significantly below M&A prices. And heightened antitrust scrutiny can reduce the value of an IPO by undermining one of its main advantages: access to publicly traded equity that can be used as currency for future acquisitions. In this Article, we show how startups have responded to the antitrust crackdown not by choosing a different exit but by choosing no exit. Startups are easing liquidity pressure by letting employees cash out their shares in tender offers. Venture capitalists are extending their exit horizons by forming continuation funds. Would-be acquirers have developed new structures to evade antitrust law, such as the centaur -- a private company funded by public company cash flows -- and the reverse acquihire -- a mass employee exodus from a startup to a public tech company, coupled with a cloaked payoff to the startup’s investors. We explain the implications of these changes for competition policy, capital formation, and the continuing erosion of transparency into socially important businesses.
The Role of Taxes in the Rise of ETFs
Rabih Moussawi, Ke Shen & Raisa Velthuis
Review of Financial Studies, forthcoming
Abstract:
This paper argues that a lesser known yet economically significant tax-deferral feature of ETFs’ security design is crucial to their success. By relying on the in-kind redemption exemption, authorized participants help ETFs avoid distributing capital gains and reduce their tax overhang, partly by deploying heartbeat trades. We estimate that the ETF tax efficiency has increased long-term investors’ after-tax returns by 1.05% per year relative to mutual funds in recent years. Exploiting cross-sectional and time-series variations in investors’ tax burden, we show that tax efficiency is a significant driver of capital migration by high-net-worth investors from mutual funds into ETFs.
AI-Powered Trading, Algorithmic Collusion, and Price Efficiency
Winston Wei Dou, Itay Goldstein & Yan Ji
NBER Working Paper, July 2025
Abstract:
The integration of algorithmic trading with reinforcement learning, termed AI-powered trading, is transforming financial markets. Alongside the benefits, it raises concerns for collusion. This study first develops a model to explore the possibility of collusion among informed speculators in a theoretical environment. We then conduct simulation experiments, replacing the speculators in the model with informed AI speculators who trade based on reinforcement-learning algorithms. We show that they autonomously sustain collusive supra-competitive profits without agreement, communication, or intent. Such collusion undermines competition and market efficiency. We demonstrate that two separate mechanisms are underlying this collusion and characterize when each one arises.
Wealth Inequality, Labor Market Arrangements and the Secular Decline in the Real Interest Rate
John Donaldson, Hyung Seok Kim & Rajnish Mehra
NBER Working Paper, July 2025
Abstract:
We develop a dynamic macroeconomic model in which the secular decline in real interest rates arises endogenously from rising wealth inequality. Challenging the standard “safe asset shortage” hypothesis, the model shows how falling real rates can coexist with a stable safe asset ratio -- closely matching U.S. empirical patterns. The mechanism combines limited financial market participation, which concentrates capital ownership among a shrinking class of stockholders, with egalitarian wage bargaining, which generates time-varying labor income shares under incomplete markets. As inequality increases, stockholders face higher financial and operating leverage, increasing their consumption volatility and precautionary demand for bonds. At the same time, greater wage instability raises workers’ demand for safe assets. The resulting surge in precautionary savings from both groups depresses real returns and creates the appearance of a safe asset shortage, despite an unchanged supply. This outcome reflects a pecuniary externality: agents fail to internalize the aggregate constraint on safe assets, especially over the business cycle. Our calibrated model reproduces key macro-financial patterns and offers new insights into the joint dynamics of wealth distribution, labor market arrangements, and asset pricing.
Mirrored Matching: Facial Similarity and the Allocation of Venture Capital
Emmanuel Yimfor
Columbia University Working Paper, July 2025
Abstract:
Do subtle visual cues influence high-stakes economic decisions? Using venture capital as a laboratory, this paper shows that facial similarity between investors and entrepreneurs predicts positive funding decisions but negative investment outcomes. Analyzing early-stage deals from 2010-2020, we find that greater facial resemblance increases match probability by 3.2 percentage points even after controlling for same race, gender, and age, yet funded companies with similar-looking investor-founder pairs have 7 percent lower exit rates. However, when deal sourcing is externally curated, facial similarity effects disappear while demographic homophily persists, indicating facial resemblance primarily operates as an initial screening heuristic. These findings reveal a novel form of homophily that systematically shapes capital allocation, suggesting that interventions targeting deal sourcing may eliminate the negative influence of visual cues on investment decisions.
Busy Venture Capitalists and Investment Performance
Rustam Abuzov
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
This paper studies the impact of limited attention on investment decisions by venture capitalists (VCs). I find that startups funded by VCs during VCs’ IPO engagements tend to underperform: These startups are 9% less likely to go public or become acquired and have lower exit multiples. The effects of VCs’ busyness cluster around the active phase of the IPO engagement and are more pronounced in cases of higher workload intensity or higher information asymmetry. Overall, this performance gap induced by attention constraints provides new evidence on VCs’ ability to identify investment opportunities at the initial screening stage.
Due Diligence and the Allocation of Venture Capital
Xiaoyong (Jack) Fu & Lucian Taylor
NBER Working Paper, July 2025
Abstract:
How do investors choose the intensity of their due diligence, and how does that choice affect investment outcomes? Using cell phone signal data, we measure the duration of pre-investment meetings between venture capitalists (VCs) and startup employees. This measure captures one important component of VC due diligence. Less due diligence is associated with hotter deals and markets, busier investors, and greater distance, consistent with a theory of costly learning. Also consistent with that theory, less due diligence is associated with more volatile investment performance, as VCs allocate capital under greater uncertainty. Overall, VCs appear to trade off the costs of due diligence with its improvements to capital allocation.
Extreme Categories and Overreaction to News
Spencer Kwon & Johnny Tang
Review of Economic Studies, forthcoming
Abstract:
What characteristics of news generate over-or-underreaction? We study the asset-pricing consequences of diagnostic expectations, a model of belief formation based on the representativeness heuristic, in a setting where news events are drawn from categories with extreme distributions of fundamentals. Our model predicts greater over-reaction to news belonging to categories with more extreme outliers, or tail events. We test our theory on a comprehensive database of corporate news that includes news from 24 different categories, including earnings announcements, product launches, M&A, business expansions, and client-related news. We find theory-consistent heterogeneity in investor reaction to news, with more overreaction in the form of greater post-announcement return reversals and trading volume for news categories with more extreme distributions of fundamentals.
Who Wins and Loses in a Bubble? Evidence from the British Bicycle Mania
William Quinn & John Turner
Journal of Economic History, June 2025, Pages 475-504
Abstract:
How do different types of investors perform during financial bubbles? Using a rich archival source, we explore investor performance during the British bicycle mania of the 1890s. We find that directors and employees of cycle companies reduced their holdings substantially during the crash. Those holding shares after the crash were generally not from groups stereotypically thought of as naïve, but gentlemen living near a stock exchange, who had sufficient time, money, and opportunity to engage in speculation. Our findings suggest that the investors most at risk of losing during a bubble are those prone to familiarity and overconfidence biases.