This paper develops a simple technique that controls for “false discoveries,” or mutual funds that exhibit significant alphas by luck alone. Our approach precisely separates funds into (1) unskilled, (2) zero‐alpha, and (3) skilled funds, even with dependencies in cross‐fund estimated alphas. We find that 75% of funds exhibit zero alpha (net of expenses), consistent with the Berk and Green equilibrium. Further, we find a significant proportion of skilled (positive alpha) funds prior to 1996, but almost none by 2006. We also show that controlling for false discoveries substantially improves the ability to find the few funds with persistent performance.

We present a new approach to selecting actively managed mutual funds that uses both portfolio holdings and fund return information to eliminate funds with predicted inferior performance through a sequence of pairwise fund comparisons. Our methodology determines both the number of skilled funds and their identities, and locates funds with substantially higher risk-adjusted returns than those identified by conventional alpha-ranking methods. We find strong evidence of time-series variation in both the number of funds identified as superior using our approach, as well as in their performance across different economic states.

We introduce an estimator that measures factor exposures and alphas of individual private equity funds, with minimal assumptions about the fund return data-generating process (DGP). Simulations using varying assumptions about the DGP indicate that our estimator exhibits lower mean-squared-error (bias plus variance) than competing time-series estimators. Applying our model to a newly available commercial dataset, PitchBook, we uncover new findings of economic importance: buyout managers have higher average skill levels than claimed by past studies; portfolios are marked with forward-looking and lagged multiples of factors; and skill and systematic exposures vary significantly over time.

We analyze the flow of money between mutual fund categories, finding strong evidence of seasonality in investor risk aversion. Aggregate investor flow data reveal an investor preference for safe mutual funds in autumn and risky funds in spring. During September alone, outflows from equity funds average $13 billion, controlling for previously documented flow determinants (e.g., capital-gains overhang). This movement of large amounts of money between fund categories is correlated with seasonality in investor risk aversion, consistent with investors preferring safer (riskier) investments in autumn (spring). We find consistent evidence in Canada and also in Australia, where seasons are offset by 6 months.

We apply a new bootstrap statistical technique to examine the performance of the U.S. open‐end, domestic equity mutual fund industry over the 1975 to 2002 period. A bootstrap approach is necessary because the cross section of mutual fund alphas has a complex nonnormal distribution due to heterogeneous risk‐taking by funds as well as nonnormalities in individual fund alpha distributions. Our bootstrap approach uncovers findings that differ from many past studies. Specifically, we find that a sizable minority of managers pick stocks well enough to more than cover their costs. Moreover, the superior alphas of these managers persist .

This article develops and applies new measures of portfolio performance which use benchmarks based on the characteristics of stocks held by the portfolios that are evaluated. Specifically, the benchmarks are constructed from the returns of 125 passive portfolios that are matched with stocks held in the evaluated portfolio on the basis of the market capitalization, book‐to‐market, and prior‐year return characteristics of those stocks. Based on these benchmarks, “Characteristic Timing” and “Characteristic Selectivity” measures are developed that detect, respectively, whether portfolio managers successfully time their portfolio weightings on these characteristics and whether managers can select stocks that outperform the average stock having the same characteristics. We apply these measures to a new database of mutual fund holdings covering over 2500 equity funds from 1975 to 1994. Our results show that mutual funds, particularly aggressive‐growth funds, exhibit some selectivity ability, but that funds exhibit no characteristic timing ability.

Kent Daniel, Mark Grinblatt, Sheridan Titman, Russ Wermers, Measuring Mutual Fund Performance with Characteristic-Based Benchmarks, The Journal of Finance, Vol. 52, No. 3, Papers and Proceedings Fifty-Seventh Annual Meeting, American Finance Association, New Orleans, Louisiana January 4-6, 1997 (Jul., 1997), pp. 1035-1058

We study investor redemptions and portfolio rebalancing decisions of prime money market mutual funds (MMFs) during the Eurozone crisis. We find that sophisticated investors selectively acquire information about MMFs’ risk exposures to Europe, which leads managers to withdraw funding from information-sensitive European issuers. That is, MMF managers, particularly those serving the most sophisticated investors, selectively adjust their portfolio risk exposures to avoid information-sensitive European risks, while maintaining or increasing risk exposures to other regions. This mechanism helps to explain the occurrence of selective “dry-ups” in debt markets where delegation is common and returns to information production are usually low.

We show a positive relation between network centrality and risk-adjusted performance in a delegated investment management setting. More connected managers take more portfolio risk and receive higher investor flows, consistent with these managers improving their ability to exploit investment opportunities through their network connections. Greater network connections are shown to be particularly important in reducing the diseconomies of scale for large managers who are well connected. We also use the exogenous merger of two investment consultants, which creates a sudden change in the network connections of the managers they oversee, to provide evidence that a greater number of connections translates into better portfolio performance.

Using a unique data set, we document two secular trends in the shift from centralized to decentralized pension fund management over the past few decades. First, across asset classes, sponsors replace generalist balanced managers with better‐performing specialists. Second, within asset classes, funds replace single managers with multiple competing managers following diverse strategies to reduce scale diseconomies as funds grow larger relative to capital markets. Consistent with a model of decentralized management, sponsors implement risk controls that trade off higher anticipated alphas of multiple specialists against the increased difficulty in coordinating their risk‐taking and the greater uncertainty concerning their true skills.