This paper documents that hedge funds did not exert a correcting force on stock prices during the technology bubble. Instead, they were heavily invested in technology stocks. This does not seem to be the result of unawareness of the bubble: Hedge funds captured the upturn, but, by reducing their positions in stocks that were about to decline, avoided much of the downturn. Our findings question the efficient markets notion that rational speculators always stabilize prices. They are consistent with models in which rational investors may prefer to ride bubbles because of predictable investor sentiment and limits to arbitrage.

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This paper investigates the efficiency of household investment decisions in a unique dataset containing the disaggregated wealth and income of the entire population of Sweden. The analysis focuses on two main sources of inefficiency in the financial portfolio: underdiversification of risky assets (“down”) and nonparticipation in risky asset markets (“out”). We find that while a few households are very poorly diversified, the cost of diversification mistakes is quite modest for most of the population. For instance, a majority of participating Swedish households are sufficiently diversified internationally to outperform the Sharpe ratio of their domestic stock market. We document that households with greater financial sophistication tend to invest more efficiently but also more aggressively, so the welfare cost of portfolio inefficiency tends to be greater for these households. The welfare cost of nonparticipation is smaller by almost one half when we take account of the fact that nonparticipants would be unlikely to invest efficientlyiftheyparticipatedinrisky asset markets.

Abstract: 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.

his support with the CDA/Spectrum database. We especially thank Russ Wermers for providing us with the characteristic-adjusted stock returns reported in DGTW (1997). We acknowledge the financial support from Mitsui Life Center in acquiring the CDA/Spectrum data. All errors are our own responsibility. On the Industry Concentration of Actively Managed Equity Mutual Funds The value of active fund management recently has become a central debate among researchers and practitioners. Mutual fund managers can deviate from the passive market portfolio by concentrating their holdings in specific industries. We investigate whether mutual fund managers are motivated to hold concentrated portfolios because they have investment skills that are linked to specific industries or whether they are motivated by agency problems that induce them to hold poorly diversified portfolios. Using U.S. mutual fund data from 1984-1999, we study the relationship between the industry concentration of mutual funds and their performance. Our analysis indicates that mutual funds differ substantially in their industry concentration, and that concentrated funds tend to follow distinct investment styles. Managers of more concentrated funds

This paper examines problems in the CRSP Survivor Bias Free U.S. Mutual Fund Database ~CRSP, 1998! and compares returns contained in it to those in Morningstar. The CRSP database has an omission bias that has the same effects as survivorship bias. Although all mutual funds are listed in CRSP, return data is missing for many and the characteristics of these funds differ from the populations. The CRSP return data is biased upward and merger months are inaccurately recorded about half the time. Differences in returns in Morningstar and CRSP are a problem for older data and small funds. IN RECENT YEARS, THERE HAS BEEN an enormous increase in the number of mutual fund studies. There is hardly a professional meeting without at least one session devoted to the topic. One of the major driving forces behind this increase in research is the availability of large computer-readable databases on fund characteristics and fund returns. The most widely used mutual fund databases in recent studies are those provided by the Center for Research in

Estimates of standard performance measures can be improved by using returns on assets not used to dene those measures. Alpha, the intercept in a regression of a fund's return on passive benchmark returns, can be estimated more precisely by using information in returns on non-benchmark passive assets, whether or not one believes those assets are priced by the benchmarks. A fund's Sharpe ratio can be estimated more precisely by using returns on other assets as well as the fund. New estimates of these performance measures for a large universe of equity mutual funds exhibit substantial differences from the usual estimates.

We construct optimal portfolios of equity funds by combining historical returns on funds and passive indexes with prior views about asset pricing and skill. By including both benchmark and nonbenchmark indexes, we distinguish pricing-model inaccuracy from managerial skill. Even modest condence in a pricing model helps construct portfolios with high Sharpe ratios. Investing in active mutual funds can be optimal even for investors who believe active managers cannot outperform passive indexes. Optimal portfolios exclude hot-hand funds even for investors who believe momentum is priced. Our large universe of funds oers no close substitutes for the Fama-French and momentum benchmarks. JEL Classications: G11, G12, C11 Keywords: mutual funds, portfolio selection * Graduate School of Business, University of Chicago (Pastor) and the Wharton School, University of Pennsylvania and the National Bureau of Economic Research (Stambaugh). Research support from the Center for Research in Security Prices and Dimensional Fund Advisors is gratefully acknowledged (Pastor). We are grateful to several anonymous referees, Eugene Fama, Wayne Ferson, Anthony Lynch, Andrew Metrick, Dean Paxson, Toby Moskowitz, and seminar participants at Emory University, the Federal Reserve Bank of New York, Northwestern University, Ohio State University, University of Chicago, University of Pennsylvania, University of Rochester, Vanderbilt University, the 2000 NBER Summer Institute, the 2000 Portuguese Finance Network Conference, and the 2001 AFA Meetings for helpful comments. This paper is based in part on the authors' earlier working paper, \Evaluating and Investing in Equity Mutual Funds." 1.

What are the equilibrium features of a Þnancial market where a sizeable proportion of traders face reputational concerns? This question is central to our understanding of Þnancial markets that are increasingly dominated by institutional investors. We construct a model of delegated portfolio management that captures key features of the US mutual fund industry and embed it in an asset pricing framework. We thus provide a formal model of Þnancial equilibrium with career concerned agents. Fund managers differ in their ability to understand market fundamentals, and in every period investors choose a fund. In equilibrium, the presence of career concerns induces uninformed fund managers to churn, i.e. to engage in trading even when they face a negative expected return. As churning plays the role of noise trading, the asset market displays non-fully informative prices and positive (and high) trading volume. The equilibrium relationship between fund return and net fund ßows displays a skewed shape that is consistent with stylized facts. The robustness of our core results is probed from several angles.

and SGF 2006 for their helpful comments. The first and second authors acknowledge