UK equity mutual fund alphas make a comeback

In this study, we re-visit the performance of 887 active UK equity mutual funds using a new approach proposed by Angelidis, Giamouridis, and Tessaromatis. The authors argue that mutual funds stock selection is driven by the benchmark index, so if the benchmark generates alpha, there will be a bias in interpretation of manager's stock-picking ability. In their model, the alpha of a fund is adjusted by the benchmark's alpha. By applying this method, we eliminate bias inflicted by the persistently negative alphas of FTSE 100 Index in the period 1992–2013. We find that adjusted Fama–French and Carhat alphas of UK equity mutual funds are higher than those implied by the standard three- and four-factor models and are overall positive, contrary to most of the existing literature on UK fund performance. This result is consistent across funds' investment styles and robust to the use of FTSE Small Cap as benchmark for a sub-sample of small cap funds.     

Do hedge funds deliver alpha? A Bayesian and bootstrap analysis

Using a robust bootstrap procedure, we find that top hedge fund performance cannot be explained by luck, and hedge fund performance persists at annual horizons. Moreover, we show that Bayesian measures, which help overcome the short-sample problem inherent in hedge fund returns, lead to superior performance predictability. Sorting on Bayesian alphas, relative to OLS alphas, yields a 5.5% per year increase in the alpha of the spread between the top and bottom hedge fund deciles. Our results are robust and relevant to investors as they are neither confined to small funds, nor driven by incubation bias, backfill bias, or serial correlation.     

European Mutual Fund Performance

This paper presents an overview of the European mutual fund industry and investigates mutual fund performance using a survivorship bias controlled sample of 506 funds from the five most important mutual fund countries. The latter is done using the Carhart (1997) 4-factor asset-pricing model. In addition we investigate whether European fund managers exhibit 'hot hands', persistence in performance. Finally the influence of fund characteristics on risk-adjusted performance is considered. Our overall results suggest that European mutual funds, and especially small cap funds are able to add value, as indicated by their positive after cost alphas. If we add back management fees, four out of five countries exhibit significant out-performance at an aggregate level. Finally, we detect strong persistence in mean returns for funds investing in the UK. Our results deviate from most US studies that argue mutual funds under-perform the market by the amount of expenses they charge.     

Reassessing False Discoveries in Mutual Fund Performance: Skill,Luck, or Lack of Power?

Barras, Scaillet, and Wermers propose the false discovery rate (FDR) to separate skill (alpha) from luck in fund performance. Using simulations with parameters informed by the data, we find that this methodology is conservative and underestimates the proportion of nonzero‐alpha funds. For example, 65% of funds with economically large alphas of $\pm 2\%$ are misclassified as zero alpha. This bias arises from the low signal‐to‐noise ratio in fund returns and the resulting low statistical power. Our results question FDR's applicability in performance evaluation and other domains with low power, and can materially change the conclusion that most funds have zero alpha.     

Investor learning and mutual fund family

In this paper we revisit the cross-fund learning method suggested by Jones and Shanken (2005) and construct a linear hierarchical model to consider the learning across funds within the fund family during the performance evaluation. We provide a full Bayesian treatment on all the factors of the pricing model and allow both the fund family and the individual manager to have dependent prior information regarding funds' alphas. The simulation results suggest that returns from peer funds within the family significantly affect investors' updating on fund alphas since the posterior distribution on fund alphas experiences a faster shrinkage than those reported in the previous literature. The model can also be simulated with specific prior belief on different factors of the pricing model, i.e. fund alphas, betas and factor loadings of each pricing benchmark, to better address the learning issue.     

The Cross‐Section of Managerial Ability,Incentives, and Risk Preferences

I estimate a dynamic investment model for mutual managers to study the cross‐sectional distribution of ability, incentives, and risk preferences. The manager's compensation depends on the size of the fund, which fluctuates due to fund returns and due to fund flows that respond to the fund's relative performance. The model provides an economic interpretation of time‐varying coefficients in performance regressions in terms of the structural parameters. I document that the estimates of fund alphas are precise and virtually unbiased. I find substantial heterogeneity in ability, risk preferences, and pay‐for‐performance sensitivities that relates to observable fund characteristics.     

Evaluating managed fund performance using conditional measures: Australian evidence

Most studies of managed fund performance use measures that are susceptible to bias caused by common time variation in risks and risk premia. We evaluate the performance of Australian managed funds 1983–1995 using lagged public information variables that have been shown to predict stock returns, such as interest rates and dividend yields, to control for the variation. The results indicate an improvement in performance relative to traditional measures and confirm the importance of using conditioning information, especially dividend yield, in performance evaluation. Jensen alphas are higher when estimated with the conditional model and the number of significant timing coefficients is greatly reduced.     

Performance attribution of mutual funds in India: outperformance or mis‐representation?

We conduct a novel holdings‐based performance attribution, particularly suited to emerging markets, for equity‐oriented active mutual funds in India. Although, we find significantly positive alphas for an average fund, the stated benchmarks are grossly mis‐specified. A style‐adjusted benchmark could beat the stated benchmarks by greater margins than the funds themselves. While funds’ trading activity consistently adds value, cash drag and market timing usually diminish value. Although, the best‐performing funds exhibit superior security selection abilities, their outperformance does not persist. However, despite the lack of persistence winner funds continue to generate significantly higher alphas than loser funds for quite some time.     

Performance and performance persistence of UK closed-end equity funds

Using a comprehensive data set of almost 300 UK closed-end equity funds over the period 1990 to 2013, we use the false discovery rate to assess the alpha-performance of individual funds with both domestic and other mandates, using self-declared benchmarks and additional risk factors. We find evidence to indicate that up to 16% of the funds have truly positive alphas while around 3% have truly negative alphas. Positive post-formation alphas using fund-price returns depend on the factor model used: there is some positive-alpha performance when post-formation returns are evaluated using a one-factor global model but substantial positive-alpha performance when using a four-factor global model.     

Asset management and investment banking

We find evidence that conflicts of interest are pervasive in the asset management business owned by investment banks. Using data from 1990 to 2008, we compare the alphas of mutual funds, hedge funds, and institutional funds operated by investment banks and non-bank conglomerates. We find that, while no difference exists in performance by fund type, being owned by an investment bank reduces alphas by 46 basis points per year in our baseline model. Making lead loans increases alphas, but the dispersion of fees across portfolios decreases alphas. The economic loss is $4.9 billion per year.     

Model uncertainty,performance persistence and flows

Model uncertainty makes it difficult to draw clear inference about mutual fund performance persistence. I propose a new performance measure, Bayesian model averaged (BMA) alpha, which explicitly accounts for model uncertainty. Using BMA alphas, I find evidence of performance persistence in a large sample of US funds. There is a positive and asymmetric relation between flows and past BMA alphas, suggesting that fund investors respond to the information in BMA alphas. My findings are robust to various sensitivity analyses, including alternative measures of post-ranking performance, flows and total net assets, and alternative econometric model specifications.     

Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis

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.     

Closed-End Fund Expenses and Investment Selection

Investment returns on closed‐end funds are highly volatile. Because expenses have a definite negative impact on closed‐end fund returns, investors should include the expense ratio as a criterion for fund selection in addition to performance, investment objective, and risk of the fund. This paper constructs a model of the expense ratio of closed‐end funds to explain cross‐sectional differences in the expense ratios for the period between 1989–1996. We relate closed‐end fund expenses to fund characteristics and identify the factors that can help investors choose low expense closed‐end funds.     

Mutual Fund Incubation

Incubation is a strategy for initiating new funds, where multiple funds are started privately, and, at the end of an evaluation period, some are opened to the public. Consistent with incubation being used by fund families to increase performance and attract flows, funds in incubation outperform nonincubated funds by 3.5% risk‐adjusted, and when they are opened to the public they attract higher flows. Postincubation, however, this outperformance disappears. This performance reversal imparts an upward bias to returns that is not removed by a fund size filter. Fund age and ticker creation date filters, however, eliminate the bias.     

Conditional performance evaluation for German equity mutual funds

We investigate the conditional performance of a sample of German equity mutual funds over the period from 1994 to 2003 using both the beta-pricing approach and the stochastic discount factor (SDF) framework. On average, mutual funds cannot generate excess returns relative to their benchmark that are large enough to cover their total expenses. Compared to unconditional alphas, fund performance sharply deteriorates when we measure conditional alphas. Given that stock returns are to some extent predictable based on publicly available information, conditional performance evaluation raises the benchmark for active fund managers because it gives them no credit for exploiting readily available information. Underperformance is more pronounced in the SDF framework than in beta-pricing models. The fund performance measures derived from alternative model specifications differ depending on the number of primitive assets taken to calibrate the SDF as well as the number of instrument variables used to scale assets and/or factors.     

Fixed-income fund performance: Role of luck and ability in tail membership

The risk-adjusted performance (alphas) of a comprehensive and survivorship-free sample of Canadian bond funds after (before) management-related costs is negative (positive) and is weakly sensitive to the choice of the return-generating process. A conditional multi-factor model that captures maturity differences and default risk best describes the return-generating process of these funds. Examination of funds in the tails of the performance distribution using the block-bootstrap method suggests that “bad luck” causes the before costs underperformance of extreme left-tail funds and no fund possesses truly superior management skills.     

Mutual fund performance with learning across funds

The average level and cross-sectional variability of fund alphas are estimated from a large sample of mutual funds. This information is incorporated, along with the usual regression estimate of alpha, in a (roughly) precision-weighted average measure of individual fund performance. Substantial “learning across funds” is documented, with significant effects on investment decisions. In a Bayesian framework, this form of learning is inconsistent with the assumption, made in the past literature, of prior independence across funds. Independence can be viewed as an extreme scenario in which the true cross-sectional distribution of alphas is presumed to be known a priori.     

Jensen's alpha and the market‐timing puzzle

Theory predicts that market‐timing activities bias Jensen's alpha (JA). However, empirical studies have failed to find consistent evidence of this bias. We tackle this puzzle in a nested model analysis and show that the bias contains an exogenous market component that is unrelated to market‐timing skill. In a comprehensive empirical analysis of US mutual funds, we find that the timing‐induced bias in JA is mainly driven by this market component, which is uncorrelated with measured timing activities. Measures of total performance that allow for timing activities are virtually identical to JA, even if timing activities are present in the evaluated fund. Hence, we conclude that JA is a sufficient measure of total performance.     

New Zealand mutual funds: measuring performance and persistence in performance

The present study investigates the performance of New Zealand mutual funds using a survivorship‐bias controlled sample of 143 funds for the period of 1990–2003. Our overall results suggest that New Zealand mutual funds have not been able to provide out‐performance. Alphas for equity funds, both domestic and international, are insignificantly different from zero, whereas balanced funds underperform significantly. There is no evidence of timing abilities by the fund managers. In the short term, significant evidence of return persistence for all funds is observed. This persistence, however, is driven by ‘icy hands’ rather than ‘hot hands’. Finally, we find the risk‐adjusted performance for equity funds to be positively related to fund size and expense ratio and negatively related to load charges.     

Portfolio concentration and fund manager performance

This research examines the relationships among portfolio concentration, fund manager skills, and fund performance in Taiwan's equity mutual fund industry, yielding several empirical findings as follows. First, after controlling for other factors, concentrated equity funds tend to have smaller net asset values, larger fund flows, higher turnover rates, and a younger age and prevail in smaller fund families. Second, concentrated fund managers buy and sell stocks more smartly based on economic trends or market factors than do diversified fund managers, i.e., they have better market‐timing abilities. Third, only partial evidence supports the premise that concentrated equity funds have better next‐quarter risk‐adjusted performances than do diversified ones, as these fund managers' skills positively correlate to risk‐adjusted fund performance. Fourth, fund managers who have better stock‐picking abilities and intensively invest in certain industries generally exhibit better Carhart's alpha in the next quarter than do other fund managers. Fifth, fund managers' stock‐picking abilities more closely relate to long‐term performance than do their market‐timing abilities. Lastly, positive performance persistence is much stronger than negative performance persistence, but concentrated funds do not have stronger performance persistence than do diversified funds.