We find a significant discontinuity in the pooled distribution of reported hedge fund returns: the number of small gains far exceeds the number of small losses. The discontinuity is present in live funds, defunct funds, and funds of all ages, suggesting that it is not caused by database biases. The discontinuity is absent in the three months culminating in an audit, funds that invest in liquid assets, and hedge fund risk factors, suggesting that it is generated neither by the skill of managers to avoid losses nor by nonlinearities in hedge fund asset returns. A remaining explanation is that hedge fund managers avoid reporting losses to attract and retain investors.Hedge funds are currently attracting a great deal of attention from investors, academics, and regulators for a number of reasons, but primarily due to the returns that hedge fund managers report. Investors want to share in the riches, academics want to understand the underlying risk factors, and regulators are concerned about the potential for fraud. Some members of the SEC support additional regulation of hedge funds, and championed an amendment to the Investment Advisors Act to force more hedge fund managers to register.1 Others argue that the low number of hedge fund fraud cases indicates that there is no need for greater oversight. 2 Though the number of fraud cases is modest, violations of the law may be widespread but undetected. In particular, the discretion with which managers voluntarily submit returns to databases may permit purposeful misreporting to attract and retain investors. We conduct a simple test for misreporting that measures discontinuities in the pooled cross-sectional, time series distribution of monthly hedge fund returns. In particular, we examine the histogram of returns to determine whether certain categories, e.g. those just below zero, appear systematically underrepresented. Our analytical framework has been used in prior research linking asymmetric incentives around a fixed hurdle with breakpoints in the empirical distribution of an outcome. Examples include the frequency of corporate earnings just below and just above zero (Burgstahler and Dichev (1997)), the winning percentage of sumo wrestlers in critical bouts (Duggan and Levitt (2002)), and the ability of management to sponsor shareholder resolutions that receive just enough votes for approval (Listokin (2007)). Our test is also related to Abdulali's (2006) bias ratio, which compares the number of positive returns to the number of negative returns within one standard deviation of zero. 4 An unusually high bias ratio is suggestive of manipulated returns, although it is unclear what levels are expected under the null hypothesis of distortion-free returns. In contrast, the null hypothesis for our test is based on the simple assumption that the distribution of returns is smooth. returns. The interpretation in both papers that incentives lead to performance relies on the assumption that some managers are skillful. The classic method of distinguishing luck from ski...

We find that socially connected fund managers have more similar holdings and trades. The overlap of funds whose managers reside in the same neighborhood is considerably higher than that of funds whose managers live in the same city but in different neighborhoods. These effects are larger when managers share a similar ethnic background, and are not explained by preferences. Valuable information is transmitted through these peer networks: a long-short strategy composed of stocks purchased minus sold by neighboring managers delivers positive risk-adjusted returns. Unlike prior empirical work, our tests disentangle the effects of social interactions from community effects.DESPITE THE IMPORTANT ROLE professional money managers play in financial markets, and decades of academic study, relatively little is known about how they generate investment ideas. Research shows that managers invest in companies headquartered nearby Moskowitz (1999, 2001)), and in companies to which they are linked through school networks (Cohen, Frazzini, and Malloy (2009)). They also choose stocks based on their political ideology (Hong and Kostovetsky (2012)) and stocks with which they are merely familiar (Pool, Stoffman, and Yonker (2012)).But, as Aristotle famously noted, humans are social animals, so perhaps fund managers also trade stocks that they learn about from other managers. While numerous papers examine the effects of social interaction on choices in other domains, 1 there is little empirical evidence on how word-of-mouth communica- * Pool and Stoffman are at the Kelley School of Business, Indiana University. Kubik, and Stein (2005) take an important first step in answering this question by studying a broad sample of mutual funds. They show that the holdings and trades of fund managers who work in the same city are correlated. 2Although these results are consistent with the hypothesis that professional money managers transmit investment ideas socially, 3 the authors point to several alternative hypotheses that are difficult to rule out with their data. Specifically, the correlation in portfolios could be due to fund managers in the same city being exposed to the same local media outlets, being visited by the same corporate executives during investor-relations road shows, or herding with local managers, which could be induced by geographic segmentation of the job market combined with career concerns (Scharfstein and Stein (1990) and Chevalier and Ellison (1999)). These alternative "community effects" would imply that news travels through formal information channels, whereas the social hypothesis implies that information travels through informal person-toperson relationships. Of course, both channels can operate simultaneously. In this paper we implement a test that allows us to disentangle the two effects.If we could observe whether any two managers know and communicate with each other, constructing an empirical test would be straightforward. In the absence of such data, however, we rely on a unique identification strategy t...

We show that if true returns are independently distributed and a manager fully reports gains but delays reporting losses, then reported returns will feature conditional serial correlation. We use conditional serial correlation as a measure of conditional return smoothing. We estimate conditional serial correlation in a large sample of hedge funds. We find that the probability of observing conditional serial correlation is related to the volatility and magnitude of investor cash flows, consistent with conditional return smoothing in response to the risk of capital flight. We also present evidence that conditional serial correlation is a leading indicator of fraud.

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