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Does Fund Size Erode Mutual Fund Performance? The Role of Liquidity and Organization

American Economic Review 2004 94(5), 1276-1302
We investigate the effect of scale on performance in the active money management industry. We first document that fund returns, both before and after fees and expenses, decline with lagged fund size, even after accounting for various performance benchmarks. We then explore a number of potential explanations for this relationship. This association is most pronounced among funds that have to invest in small and illiquid stocks, suggesting that these adverse scale effects are related to liquidity. Controlling for its size, a fund's return does not deteriorate with the size of the family that it belongs to, indicating that scale need not be bad for performance depending on how the fund is organized. Finally, using data on whether funds are solo-managed or team-managed and the composition of fund investments, we explore the idea that scale erodes fund performance because of the interaction of liquidity and organizational diseconomies.

Outsourcing Mutual Fund Management: Firm Boundaries, Incentives, and Performance

Journal of Finance 2013 68(2), 523-558
ABSTRACT We investigate the effects of managerial outsourcing on the performance and incentives of mutual funds. Fund families outsource the management of a large fraction of their funds to advisory firms. These funds underperform those run internally by about 52 basis points per year. After instrumenting for a fund's outsourcing status, the estimated underperformance is three times larger. We hypothesize that contractual externalities due to firm boundaries make it difficult to extract performance from an outsourced relationship. Consistent with this view, outsourced funds face higher powered incentives; they are more likely to be closed after poor performance and excessive risk‐taking.

Effects of Credit Expansions on Stock Market Booms and Busts

Review of Financial Studies 2025 38(5), 1502-1544
Abstract There is causal evidence that mortgage credit expansions increase house prices. Does an expansion of margin lending increase stock prices? Because unconstrained arbitrageurs are more important for pricing stocks than homes, the impact is not obvious. Tests are limited because sizable shocks to margin lending are rare. We examine a major Chinese margin-lending expansion between 2010 and 2015. Institutional holding, regression discontinuity, and event study evidence—exploiting the rollout of margin lending across stocks—shows that arbitrageurs anticipated and bought in advance of a significant causal effect of credit. We develop a model to rationalize our findings. Our estimates suggest that margin debt contributes to stock market fluctuations.

Trading for Status

Review of Financial Studies 2014 27(11), 3171-3212
We show that Keeping-Up-with-the-Joneses preferences can explain several puzzling retail investor behaviors, including the excessive trading of small local stocks. Status concerns lead households, especially those living in affluent areas, to demand these stocks to track their neighbors' wealth. This demand varies procyclically with the stock market's value and generates household trading. Using Chinese data on local stock turnover, stock message boards, and brokerage account trading, we test and confirm this hypothesis by exploiting the uneven rise of affluence across Chinese cities between 1998 and 2012.

Robust Measures of Earnings Surprises

Journal of Finance 2019 74(2), 943-983
ABSTRACT Event studies of market efficiency measure earnings surprises using the consensus error ( CE ), given as actual earnings minus the average professional forecast. If a subset of forecasts can be biased, the ideal but difficult to estimate parameter‐dependent alternative to CE is a nonlinear filter of individual errors that adjusts for bias. We show that CE is a poor parameter‐free approximation of this ideal measure. The fraction of misses on the same side ( FOM ), which discards the magnitude of misses, offers a far better approximation. FOM performs particularly well against CE in predicting the returns of U.S. stocks, where bias is potentially large.