Standard testing approaches designed to identify funds with non-zero alphas do not account for the presence of lucky funds. Lucky funds have a significant estimated alpha, while their true alpha is equal to zero. This paper quantifies the impact of luck with new measures built on the False Discovery Rate (FDR). These FDR measures provide a simple way to compute the number and the proportion of funds with truly positive and negative performance in any portion of the tails of the cross-sectional alpha distribution. Using a large cross-section of U.S. domestic-equity funds, we find that 76.6% of them have zero alphas. 21.3% yield negative performance and are dispersed in the left tail of the alpha distribution. The remaining 2.1% with positive alphas are located at the extreme right tail. The same analysis is run on three investment categories (growth, aggressive growth, growth and income funds), as well as groups formed according to lagged fund characteristics (turnover, expense ratio, total net asset value).

This paper develops a unified approach to comprehensively analyze individual hedge fund return predictability, both in and out of sample. In sample, we find that variation in hedge fund performance across changing market conditions is widespread and economically significant. The predictability pattern is consistent with economic rationale, and largely reflects differences in key hedge fund characteristics, such as leverage or capacity constraints. Out of sample, we show that a simple strategy that combines the funds’ return forecasts obtained from individual predictors delivers superior performance. We exploit this simplicity to highlight the drivers of this performance, and find that in- and out-of-sample predictability are closely related.

BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The papers are on subjects of topical interest and are technical in character. The views expressed in them are those of their authors and not necessarily the views of the BIS. This publication is available on the BIS website (www.bis.org).

We develop a flexible and bias-adjusted approach to jointly examine skill, scalability, and value-added across individual funds. We find that skill and scalability (i) vary substantially across funds, and (ii) are strongly related, as great investment ideas are difficult to scale up. The combination of skill and scalability produces a valueadded that (i) is positive for the majority of funds, and (ii) approaches its optimal level after an adjustment period (possibly due to investor learning). These results are consistent with theoretical models in which funds are skilled and able to extract economic rents from capital markets.THE ACADEMIC LITERATURE ON MUTUAL funds has focused largely on performance, that is, whether investors earn positive alphas when they

No abstract