US Equity Mutual Funds Research Articles

The Predictive Power of Portfolio Characteristics

In order to predict future relative results within a universe of equity portfolios, the authors hypothesize that it is possible to use selected portfolio characteristics as opposed to relying on past performance. This research uses Active Share and Concentration Coefficient data for universes of US, international, and global equity mutual fund portfolios to develop a method of predicting the future relative ranking of the portfolios’ information ratios. The predictive power of this approach appears statistically significant for the five-year period of 2009-2013, but not during the financial crisis years of 2007-2008. The authors believe these results are indicative of the usefulness of this approach, but not conclusive due to the limited time frame (seven years of data) and universe (174 funds). The authors invite collaboration for further research.

Do mutual fund managers manipulate?

This is the first study to document the evidence for performance manipulation in the US equity mutual fund industry based on the performance manipulation-proof measure. Characteristics of the funds likely to be manipulated are identified.

Towards a Holistic Approach for Mutual Fund Performance Appraisal

There is a growing literature that employs nonparametric frontier methods in order to evaluate the performance of investment funds. This paper proposes an integrated approach for analyzing the efficiency and performance of mutual funds. The methodology combines data envelopment analysis (DEA) with a multicriteria decision aid methodology. DEA is employed to assess the relative efficiency of mutual funds in terms of their return, capital flow, gross expense ratio, turnover rate, and risk. In a second stage, a multicriteria approach is employed to develop an overall performance measure on the basis of the DEA efficiency results. The resulting model evaluates all mutual funds in a common basis and enables comparisons over time. The methodology is applied to a sample of more than 500 US equity mutual funds over the period 2003---2010. The analysis is implemented under three different time-window periods (one, three, and five year evaluations). The results obtained for portfolios constructed on the basis of our global performance measure, Sharpe ratio and Morningstar rating system are useful since they provide significant economic evidence in favor of our global performance measure. Our results entail practical implications for both investors and fund managers in terms of fund selection and efficient portfolio management respectively.

Components of Portfolio Variance: R2, SelectionShare and TimingShare

An investment portfolio’s return variance is the sum of variance generated by passive systematic risk factor exposure, active security selection and active systematic risk factor timing. We show that the components of active risk can be estimated without knowledge of portfolio holdings. In a broad sample of US equity mutual funds classified as actively managed by Lipper in years 2000-2013, Carhart (1997) risk factors on average account for 94 %, security selection for 5 % and risk factor timing for 1 % of total variance. Security selection is positively associated to future performance, while systematic risk factor timing correlates negatively with future performance. Our new active variance measures – SelectionShare and TimingShare – complement ActiveShare and TrackingError in predicting future performance.

Capacity effects and winner fund performance: the relevance and interactions of fund size and family characteristics

This study analyzes the existence of capacity effects and performance persistence for US equity mutual funds for the period from 1992 to 2007. We focus on winner funds and distinguish between capacity effects from both size and inflows and explore their interactions with two measures of family size, i.e. family total net assets under management (family TNA) and the number of funds at the family level (family breadth). The differentiation of family size allows us to analyze competing effects at the family level such as economies of scale as well as organizational complexity costs and conflicts of interest. Our empirical results confirm diseconomies of scale at the winner fund level and indicate that only small winner funds with low inflows significantly outperform the four-factor benchmark on a net return basis. There are no universal benefits from economies of scale at the family level, but our findings suggest the existence of conflicts of interest in families offering a relatively large number of funds. Small winner funds in families offering a small number of funds significantly outperform while economies of scale only materialize among extremely small winner funds. We provide detailed robustness checks for our empirical results. Overall, simply conditioning on fund size is not sufficient for selecting future outperforming funds. The results indicate that fund investors may earn positive abnormal returns when combining information on fund size with information on fund flows or fund family affiliations in their asset allocation decisions.

Not Fooled by Randomness: Using Random Portfolios to Analyze Investment Funds

The biggest challenge in testing mutual funds for manager skill is the lack of a probability distribution of returns under the null hypothesis of no skill. A methodology based on randomly trading portfolios and non parametric statistical tests is explored, and a test of skill is proposed. Simulation is used to perform an in-depth study of the properties of this test, and to compare its power against that of other tests of skill based on factor model alphas. Empirical tests performed on a sample of US equity mutual funds find evidence of skill in a reduced number of managers, but that the value added by this skill is charged away from the investors in the form of fund fees and expenses. Overall, random portfolio based measures are found to be more powerful and easier to interpret than tests based on traditional and bootstrapped factor model alphas.

Measurement of U.S. Equity Mutual Funds’ Environmental Responsibility Attractiveness for an Individual Investor

Socially responsible mutual funds, also known as socially responsible invested funds, are one of the main instruments of Socially Responsible Investment (SRI). The term “fund” is used to refer to a ready-made financial product where investor’s money is pooled into a portfolio and a fund/investment manager decides which shares to buy. Therefore, this financial product is attractive for passive investors without a high degree of financial knowledge. Nevertheless, investment tools aimed at assisting the investors in their selection of socially responsible companies which serve best their social and environmental values are rather scare and this lack of tools assisting investors in SRI is even more important when we refer to socially responsible mutual funds. The aim of this paper is to assist individual passive investors in their investment decisions providing them with a ranking of mutual funds adjusted to their social, environmental and ethical particular preferences. The proposed approach is illustrated with a real US equity mutual funds’ ranking example.

Not fooled by randomness: Using random portfolios to analyse investment funds

ABSTRACTThe biggest challenge in testing mutual funds for manager skill is the lack of a probability distribution of returns under the null hypothesis of no skill. A methodology based on randomly trading portfolios and non parametric statistical tests is explored, and a test of skill is proposed. Empirical tests performed on a sample of US equity mutual funds find evidence of skill in a reduced number of managers, but the value added by this skill is charged away from the investors in the form of fund fees and expenses. Overall, random portfolio based measures are found to be more powerful and easier to interpret than tests based on traditional and bootstrapped factor model alphas.

Jensen Alpha and Market Climate

This paper studies the impact of market climate on the classic Jensen alpha (JA) of funds. We show analytically that the one-factor JA of a fund consists of i) the fund’s alpha based on the assumed multi-factor model and ii) further components that are subject to market phases of factor realization. To account for this impact of market phases in the performance evaluation of funds, we apply a time period-adjusted JA. In our empirical study, we analyze JAs and respective fund rankings for a survivorship bias-free data set of 3.102 US equity mutual funds. Our results show that factor realizations during the specific lifetime of a fund clearly affect its rank position. This impact is particularly strong for funds with shorter lifetimes. Using the time period-adjusted JA clearly reduces this impact. Our main results are robust when applying alternative multi-factor models as a return generating process.

Mutual fund performance and management location

In this article we develop and explore the most comprehensive database of fund manager performance delineated by location. We use this database and four performance evaluation techniques to determine whether a fund manager’s location relative to the location of the securities they manage are listed and traded has any impact on fund performance. The main results of our article are very positive for the US fund management industry. Any investor wishing to invest in a US equity mutual fund would be well advised to have this portfolio managed by a manager based in the United States. Compared with European managers of US equity mutual funds, US managers produce higher mean alpha and display a far greater tendency for positive performance persistence.

Market timing ability and mutual funds: a heterogeneous agent approach

This paper proposes a novel approach to determine whether mutual funds time the market. The proposed approach builds on a heterogeneous agent model, where investors switch between cash and stocks depending on a certain switching rule. This approach is more flexible, intuitive, and parsimonious than the traditional convexity approach. Applying this model to a sample of 400 US equity mutual funds, we find that 41.5% of the funds in our sample have negative market timing skills and only 3.25% positive skills. Twenty percent of funds apply a forward-looking approach in deciding on market timing, and 13.75% a backward-looking approach. We find that growth funds tend to be more backward-looking and income funds tend to be more forward-looking.

The Sharpe ratio's market climate bias: Theoretical and empirical evidence from US equity mutual funds

This article analyses the impact of market climates on the Sharpe ratios (SRs) of funds. On the basis of a common factor model, we derive analytically how market climates impact the SR – taking into account the abilities of fund managers. This applies especially to the mean of the market returns during the evaluation period: The performance of funds with relatively high unsystematic risk is biased upwards in outstandingly negative market climates, and vice versa. Our empirical study of US equity mutual funds supports these theoretical insights. We show that the SR of poorly diversified funds is biased upwards in bear markets, and vice versa. Subsequently, we confirm that actual fund SRs depend on especially the mean excess returns of the market. Thus, the SR does not provide a meaningful assessment of fund performance, especially in extraordinary times. We therefore suggest using the ‘normalised’ Sharpe ratio in future empirical research, in order to avoid the bias of SRs and rankings due to market climate.

Dynamic Style Analysis and Applications

We analyze the shortcomings of existing multi-factor models based on portfolio performance data in detecting investment portfolio dynamics such as gradual style drift or rapid changes in strategy. We then lay the groundwork for a new approach, which we call Dynamic Style Analysis (DSA), representing a time-series multi-factor portfolio analysis model. The major concepts of the new methodology are gradually introduced and applied to analyses of both model portfolios and well-known US equity mutual funds. By comparing publicly available holdings data with results obtained with DSA, we demonstrate both the superiority of the new model and its remarkable accuracy in detecting portfolio dynamics. We also address issues such as the computational complexity of DSA and its practical applications in the areas of risk management, performance measurement and investment research. One of the major applications of the new methodology lies in hedge fund due diligence and risk monitoring, where the importance of uncovering and controlling hidden factor dynamics is especially valuable given the limited transparency of hedge funds.

Market Timing Ability and Mutual Funds: A Heterogeneous Agent Approach

This paper proposes a novel approach to determine whether mutual funds time the market. The proposed approach builds on a heterogeneous agent model, where investors switch between cash and stocks depending on a certain switching rule. This represents a more flexible, intuitive, and parsimonious approach. The traditional market timing models are essentially a special case of our model with contemporaneous switching rule. Applying this model to a sample of 400 US equity mutual funds, we find that 41.5% of the funds in our sample have negative market timing skills and only 3.25% positive skills. 20% of funds apply a forward-looking approach in deciding on market timing, and 13.75% a backward looking approach. We also note that market timing differs considerably over fund styles.

Capacity Effects and Winner Fund Performance: The Relevance and Interactions of Fund and Family Characteristics

In this paper, we investigate the profitability of characteristics-based mutual fund investment strategies. We analyze the existence of capacity effects on the individual fund level and its interactions with fund flows, family TNA, and family size. Recent studies suggest the existence of diseconomies of scale on the individual fund level while assets under management on the family level may not have detrimental effects for fund performance per se. By analyzing a sample of US equity mutual funds between 1992 and 2007 we provide evidence for performance persistence among recent winner funds. After controlling for fund size, we are able to document positive yet insignificant four-factor alphas for the sub-group of small winner funds. When net inflows into these funds are additionally considered, an investment strategy buying small winner funds with below median inflows yields significantly positive four-factor alphas of 2.76 percent per year. Moreover, if the fund family manages few other funds in the same segment, small winner funds weakly outperform the four-factor benchmark by 2.40 percent per year. In contrast, family TNA only provides sufficient information for selecting persistent outperformers among the subset of extremely small winner funds. Overall, the results are rather consistent with the divergence of scale effects on the fund and family level, respectively, and suggest the presence of organizational complexity costs and agency conflicts in large fund families.

Capacity Effects and Winner Fund Performance: The Relevance and Interactions of Fund and Family Characteristics

In this paper, we investigate the profitability of characteristics-based mutual fund investment strategies. We analyze the existence of capacity effects on the individual fund level and its interactions with fund flows, family TNA, and family size. Recent studies suggest the existence of diseconomies of scale on the individual fund level while assets under management on the family level may not have detrimental effects for fund performance per se. By analyzing a sample of US equity mutual funds between 1992 and 2007 we provide evidence for performance persistence among recent winner funds. After controlling for fund size, we are able to document positive yet insignificant four-factor alphas for the sub-group of small winner funds. When net inflows into these funds are additionally considered, an investment strategy buying small winner funds with below median inflows yields significantly positive four-factor alphas of 2.76 percent per year. Moreover, if the fund family manages few other funds in the same segment, small winner funds weakly outperform the four-factor benchmark by 2.40 percent per year. In contrast, family TNA only provides sufficient information for selecting persistent outperformers among the subset of extremely small winner funds. Overall, the results are rather consistent with the divergence of scale effects on the fund and family level, respectively, and suggest the presence of organizational complexity costs and agency conflicts in large fund families.

Selling winners, holding losers: Effect on fund flows and survival of disposition-prone mutual funds

Recent studies suggest that presence of a disposition effect in a large subset of investors can create stock mispricings, which has serious implications for market efficiency. We examine whether US equity mutual funds are disposition-prone, how that effect influences performance, investor flows and fund survival, and whether the disposition orientation of mutual funds affects stock prices in a sustained manner. We find that about 30% of all funds exhibit some degree of disposition behavior and that such funds underperform funds that are not disposition-prone by 4–6% per year. Moreover, after controlling for performance, tax overhang and other factors that potentially affect flows, disposition-prone funds attract significantly smaller flows than other funds. The results suggest that mutual fund investors are smart enough to minimize investment in disposition-prone funds. Consequently, disposition-prone funds have significantly higher rates of failure than other funds, thereby reducing the impact of such trading behavior on security prices.

On the Stability of Performance Measures Over Time

Performance persistence is a relevant issue when evaluating the predictability of future results of managed portfolios. A related crucial aspect is the stability over time of the measure used to assess the performance, defined as the degree of association between the rankings of financial assets induced by the performance measure throughout subsequents periods. In this work a general class of possible criteria to measure stability is proposed. Then, the attention is focused on a specific index, whose asymptotic expected value and variance are derived under the null hypothesis of absence of stability. Furthermore, two statistical tests for evaluating the significance of stability are discussed. An application to a large set of US equity mutual funds shows that stability may remarkably vary, as the performance measure or the time widow width where it is computed change.

Is a Team Different from the Sum of its Parts? Evidence from Mutual Fund Managers*

This paper provides the first empirical test of the diversification of opinions theory and the group shift theory using real business data. Our data set covers management teams and single managers of US equity mutual funds. Our results reject the group shift theory and support the diversification of opinions theory: teams follow less extreme investment styles, their portfolios are less industry concentrated, and they are eventually less likely to achieve extreme performance outcomes. These results hold after taking into account the impact of fund and family characteristics as well as manager characteristics. Copyright 2010, Oxford University Press.

Mutual Fund Performance: Measurement and Evidence1

The paper provides a critical review of empirical findings on the performance of mutual funds, mainly for the US and UK. Ex‐post, there are around 0‐5% of top performing UK and US equity mutual funds with truly positive‐alpha performance (after fees) and around 20% of funds that have truly poor alpha performance, with about 75% of active funds which are effectively zero‐alpha funds. Key drivers of relative performance are, load fees, expenses and turnover. There is little evidence of successful market timing. Evidence suggests past winner funds persist, when rebalancing is frequent (i.e., less than one year) and when using sophisticated sorting rules (e.g., Bayesian approaches) ‐ but transactions costs (load and advisory fees) imply that economic gains to investors from winner funds may be marginal. The US evidence clearly supports the view that past loser funds remain losers. Broadly speaking results for bond mutual funds are similar to those for equity funds. Sensible advice for most investors would be to hold low cost index funds and avoid holding past ‘active’ loser funds. Only sophisticated investors should pursue an active ex‐ante investment strategy of trying to pick winners ‐ and then with much caution.