Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use.

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 adjusting these returns by various performance benchmarks. We then explore a number of potential explanations for this relationship. We find that this relationship is most pronounced among funds that have to invest in small and illiquid stocks, which suggests that the adverse effects of scale are related to liquidity. Controlling for its size, a fund’s performance actually increases with the asset base of the other funds in the family that the fund belongs to. This suggests that scale need not be bad for fund returns depending on how the fund is organized. Finally, we explore the idea that scale erodes fund performance because of the interaction of liquidity and organizational diseconomies.

We build a model that helps explain why increases in liquidity⎯such as lower bid-ask spreads, a lower price impact of trade, or higher turnover⎯predict lower subsequent returns in both firm-level and aggregate data. The model features a class of irrational investors, who underreact to the information contained in order flow, thereby boosting liquidity. In the presence of short-sales constraints, high liquidity is a symptom of the fact that the market is dominated by these irrational investors, and hence is overvalued. This theory can also explain how managers might successfully time the market for seasoned equity offerings, by simply following a rule of thumb that involves issuing when the SEO market is particularly liquid. Empirically, we find that: i) aggregate measures of equity issuance and share turnover are highly correlated; yet ii) in a multiple regression, both have incremental predictive power for future equal-weighted market returns.

We model the relationship between asset float (tradeable shares) and speculative bubbles. Investors trade a stock with limited float because of insider lock-ups. They have heterogeneous beliefs due to overconfidence and face short-sales constraints. A bubble arises as price overweighs optimists’ beliefs and investors anticipate the option to resell to those with even higher valuations. The bubble’s size depends on float as investors anticipate an increase in float with lock-up expirations and speculate over the degree of insider selling. Consistent with the internet experience, the bubble, turnover and volatility decrease with float and prices drop on the lock-up expiration date.

, respectively. Over the last twenty years, the field of behavioral finance has grown from a startup operation into a mature enterprise, with well-developed bodies of both theory and empirical evidence. On the empirical side, the benchmark null hypothesis is that one should not be able to forecast a stock’s return with anything other than measures of its riskiness, such as its beta; this hypothesis embodies the familiar idea that any other form of predictability would represent a profitable trading rule and hence a free lunch to investors. Yet in a striking rejection of this null, a large catalog of variables with no apparent connection to risk have been shown to forecast stock returns, both in the time series and the cross-section. Many of these results have been replicated in a variety of samples and have stood up sufficiently well that they are generally considered to be established facts. One prominent set of patterns from the cross-section has to do with medium-term momentum and post-earnings drift in returns. These describe the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for

Abstract Using a comprehensive database of hedge funds, we examine the role of managerial incentives and discretion in the performance of hedge funds. We find that hedge funds with greater managerial incentives as proxied by delta of option-like incentive fee contract, managerial ownership, and high-water mark provision are associated with superior performance. Incentive fees have no explanatory power for future returns. We also find that funds with higher degree of managerial discretion, proxied by longer lockup, notice, and redemption periods, are associated with superior performance. Our results are robust to various alternate specifications including using alternative performance measures, allowing for nonlinearity for managerial discretion, using different econometric specifications, and controlling for different data-related biases. , and MSCI for providing us with the data on hedge funds. We are thankful to Burak Ciceksever, Otgontsetseg Erhemjamts, and Purnendu Nath for excellent research assistance. We are responsible for all errors. ____________________________________________ Role of managerial incentives and discretion in hedge fund performance Abstract Using a comprehensive database of hedge funds, we examine the role of managerial incentives and discretion in the performance of hedge funds. We find that hedge funds with greater managerial incentives as proxied by delta of option-like incentive fee contract, managerial ownership, and high-water mark provision are associated with superior performance. Incentive fees have no explanatory power for future returns. We also find that funds with higher degree of managerial discretion, proxied by longer lockup, notice, and redemption periods, are associated with superior performance. Our results are robust to various alternate specifications including using alternative performance measures, allowing for nonlinearity for managerial discretion, using different econometric specifications, and controlling for different data-related biases.

This paper develops a rational, liquidity-based model of closed-end funds (CEFs) that provides an economic motivation for the existence of this organizational form: They offer a means for investors to buy illiquid securities, without facing the potential costs associated with direct trading and without the externalities imposed by an open-end fund structure. Our theory predicts the patterns observed in CEF initial public offerings (IPOs) and the observed behavior of the CEF discount, which results from a trade-off between the liquidity benefits of investing in the CEF and the fees charged by the fund’s managers. In particular, the model explains why IPOs occur in waves in certain sectors at a time, why funds are issued at a premium to net asset value (NAV), and why they later usually trade at a discount. We also conduct an empirical investigation, which, overall, provides more support for a liquidity-based model than for an alternative sentiment-based explanation. (JEL G14). A closed-end fund (CEF) is a publicly traded firm that invests in securities. While investors can, in principle, trade either in the CEF’s shares or directly in the underlying securities, a CEF rarely trades at a price equal to the value

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We investigate the effect of fund size on performance among active mutual funds. We first document that fund returns, both before and after management fees, decline with fund size, even after adjusting performance by various benchmarks and controlling for other fund characteristics such as turnover and age. We then explore a number of potential explanations for this relationship. We find that the effect of fund size on fund returns is most pronounced among funds that play small cap stocks. Interestingly, performance only depends on fund size and does not decline with family size. Finally, small funds are better than large ones at investing in local companies. We argue that these findings are consistent with both liquidity and organizational diseconomies being important factors behind the documented diseconomies of scale in money management.

We show that the abnormal returns on high-default risk stocks documented by Vassalou and Xing (2004) are driven by short-term return reversals rather than systematic default risk. These abnormal returns occur only during the month after portfolio formation and are concentrated in a small subset of stocks that had recently experienced large negative returns. Empirical evidence supports the view that the short-term return reversal arises from a liquidity shock triggered by a clientele change.