Reverse Survivorship Bias

Mutual funds often disappear following poor performance. When this poor performance is partly attributable to negative idiosyncratic shocks, funds' estimated alphas understate their true alphas. This paper estimates a structural model to correct for this bias. Although most funds still have negative alphas, they are not nearly as low as those suggested by the fund‐by‐fund regressions. Approximately 12% of funds have net four‐factor model alphas greater than 2% per year. All studies that run fund‐by‐fund regressions to draw inferences about the prevalence of skill among mutual fund managers are subject to reverse survivorship bias.     

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.     

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.     

Mutual Fund Flows and Cross‐Fund Learning within Families

We develop a model of performance evaluation and fund flows for mutual funds in a family. Family performance has two effects on a member fund's estimated skill and inflows: a positive common‐skill effect, and a negative correlated‐noise effect. The overall spillover can be either positive or negative, depending on the weight of common skill and correlation of noise in returns. Its absolute value increases with family size, and declines over time. The sensitivity of flows to a fund's own performance is affected accordingly. Empirical estimates of fund flow sensitivities show patterns consistent with rational cross‐fund learning within families.     

Informed trading around earnings and mutual fund alphas

We examine whether informed trading around earnings announcements drives mutual fund performance. The measure is motivated by prior studies arguing that a mutual fund is skilled if it buys stocks with subsequent high earnings announcement returns. We find that this measure predicts future mutual fund returns. On average, after adjusting for Carhart’s four risk factors, the top decile of mutual funds outperforms the bottom decile by 44 basis points per quarter. By decomposing fund alphas into two components in their relations to earnings, we find that this measure is only associated with earnings-related fund alphas. This measure can also be used to predict stock returns at future earnings announcements.     

Hedge fund performance attribution under various market conditions

We investigate US hedge funds' performance. Our proposed model contains exogenous and endogenous break points, based on business cycles and on a regime switching process conditional on different states of the market. During difficult market conditions most hedge fund strategies do not provide significant alphas. At such times hedge funds reduce both the number of their exposures to different asset classes and their portfolio allocations, while some strategies even reverse their exposures. Directional strategies share more common exposures under all market conditions compared to non-directional strategies. Factors related to commodity asset classes are more common during these difficult conditions whereas factors related to equity asset classes are most common during good market conditions. Falling stock markets are harsher than recessions for hedge funds.     

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.     

Mutual funds as monitors: Evidence from mutual fund voting

We address how mutual funds vote on shareholder proposals and identify factors that help determine support of wealth-increasing shareholder proposals. We examine 213,579 voting decisions made by 1799 mutual funds from 94 fund families for 1047 shareholder proposals voted on between July 2003 and June 2005. In an analysis of voting across funds within the same fund family, we find significant divergence in voting within families, emphasizing the importance of focusing on voting by individual funds. We also find that, in general, mutual funds vote more affirmatively for potentially wealth-increasing proposals and funds' voting approval rates for these beneficial resolutions are significantly higher than those of other investors. Our results suggest that funds tend to support proposals targeting firms with weaker governance. We also find that funds with lower turnover ratios and social funds are more likely to support shareholder proposals. Finally, fund voting approval rates significantly impact whether a proposal passes and whether one is implemented.     

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.     

Why mutual funds “underperform”

I propose a parsimonious model that reproduces the negative risk-adjusted performance of actively managed equity mutual funds. In the model, a fund manager can generate state-dependent active returns at a disutility. Negative expected performance and mutual fund investing simultaneously arise in equilibrium because the active return the fund manager generates covaries positively with a component of the pricing kernel that the performance measure omits, consistent with recent empirical evidence. Using data on U.S. funds, I also document new empirical evidence consistent with the model's cross-sectional implications.     

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.     

Information Pricing: The Evidence From Equity Mutual Funds

The theory of information pricing implies that the benefits from obtaining costly information should be offset by the costs. In the case of mutual funds, this theory suggests that trades by fund managers should take place at prices that compensate their clients for the managers' costs of becoming informed. This paper controls for risk, fund size, and age to assess the relationship of a fund's information costs to its performance. The findings show that stock funds charging the highest expenses generally earn returns insignificantly different from funds charging the lowest expenses. This lends support to the theory of information pricing. The findings are also indicative of an efficient market, given that information is costly.     

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.     

Independent Directors and Favoritism: When Multiple Board Affiliations Prevail in Mutual Fund Families

I examine whether independent directors with multiple board affiliations (IDMAs) trade off the interests of one fund relative to another (fund favoritism) or whether they benefit fund shareholders by increasing the level of the board's expertise. Using a sample of mutual funds affiliated with the top 55 fund sponsors from 2002 to 2008, I find that the presence of IDMAs is negatively related to performance/resource shifting across funds within fund families. IDMAs appear to decrease fund fees, increase the return gap associated with the unobserved actions of fund managers, and facilitate the transfer of information across funds in a fund family.     

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.     

INVESTOR TAX-TRADING OPPORTUNITIES AND DISCOUNTS ON CLOSED-END MUTUAL FUNDS

Discounts on closed-end mutual funds are a puzzle to financial economists, because arbitrage activities should eliminate discounts in a perfect capital market. In this paper I develop a model that explains discounts, using Merton's option pricing theorem. By holding shares of a closed-end mutual fund, investors lose valuable tax-trading opportunities associated with the constituent securities of the closed-end mutual fund's portfolio. However, investors can take advantage of all tax-trading opportunities by directly holding the closed-end mutual fund's portfolio. I also show that both variances of individual securities and correlations among securities in the portfolio are important factors in determining the magnitude of discounts.     

Hedge fund pricing and model uncertainty

This article uses Bayesian model averaging to study model uncertainty in hedge fund pricing. We show how to incorporate heteroscedasticity, thus, we develop a framework that jointly accounts for model uncertainty and heteroscedasticity. Relevant risk factors are identified and compared with those selected through standard model selection techniques. The analysis reveals that a model selection strategy that accounts for model uncertainty in hedge fund pricing regressions can be superior in estimation/inference. We explore potential impacts of our approach by analysing individual funds and show that they can be economically important.     

The performance of enhanced-return index funds: evidence from bootstrap analysis

We apply the bootstrap technique proposed by Kosowski et al. [J. Finance, 2006, 61, 2551–2595] in conjunction with Carhart's [J. Finance, 1997, 52, 57–82] unconditional and Ferson and Schadt's [J. Finance, 1996, 51, 425–461] conditional four-factor models of performance to examine whether the performances of enhanced-return index funds over the 1996 to 2007 period are based on luck or superior ‘enhancing’ skills. The advantages of using the bootstrap to rank fund performance are many. It eliminates the need to specify the exact shape of the distribution from which returns are drawn and does not require estimating correlations between portfolio returns. It also eliminates the need to explicitly control for potential ‘data snooping’ biases that arise from an ex-post sort. Our results show evidence of enhanced-return index funds with positive and significant alphas after controlling for luck and sampling variability. The results are robust to both stock-only and derivative-enhanced index funds, although the spread of cross-sectional alphas for derivative-enhanced funds is slightly more pronounced. The study also examines various sub-periods within the sample horizon.     

Evaluating Government Bond Fund Performance with Stochastic Discount Factors

This article shows how to evaluate the performance of managedportfolios using stochastic discount factors (SDFs) from continuous-timeterm structure models. These models imply empirical factorsthat include time averages of the underlying state variables.The approach addresses a performance measurement bias, describedby Goetzmann, Ingersoll, and Ivkovic (2000) and Ferson and Khang(2002), arising because fund managers may trade within the returnmeasurement interval or hold positions in replicable options.The empirical factors contribute explanatory power in factormodel regressions and reduce model pricing errors. We illustratethe approach on US government bond funds during 1986–2000.     

AN ARBITRAGE PRICING APPROACH TO EVALUATING MUTUAL FUND PERFORMANCE

A test procedure, derived from arbitrage pricing theory, that permits the measurement of the security selection performance of professional portfolio managers is developed and applied to a sample of mutual funds over the period of the 1970's. The evidence indicates that more than one factor was present in the market during that interval as a systematic influence on the profile of securities returns. Consistent with prior studies, the evidence also suggests that mutual fund portfolios did not outperform a passive buy-and-hold investment strategy. A comparative analysis of the same data, using performance measures based on the single-factor market model, produces similar but less powerful results, both in the aggregate and at the individual fund level.