US Mutual Funds Research Articles

The wisdom of crowds: Mutual fund investors’ aggregate asset allocation decisions

We find that the aggregate asset allocation decisions of US mutual fund investors depend on economic conditions. Both anticipated economic downturns and periods of turmoil lead investors to direct flow away from risky equity funds and towards lower-risk money market funds. These patterns are markedly stronger for investors in low cost and low turnover funds relative to investors in high cost and high turnover funds, consistent with sophisticated investors being more sensitive to changing conditions. Benchmarked against a buy-and-hold strategy, these asset allocation strategies reduce risk without degrading the risk-return trade-off. Our evidence suggests that individual investors, often dismissed as noise traders, collectively react to economic signals in a sensible manner when determining asset allocations.

On the informativeness of persistence for evaluating mutual fund performance using partial frontiers

The last few years have witnessed a rapid evolution in the literature evaluating mutual fund performance using frontier techniques. The instruments applied, mostly DEA (Data Envelopment Analysis) and, to a lesser extent, FDH (Free Disposal Hull), are able to encompass several dimensions of performance, but they also have some disadvantages that might be preventing a wider acceptance. The recently developed order-mand order-αpartial frontiers overcome some of the disadvantages (they are robust with respect to extreme values and noise, and do not suffer from the well-known curse of dimensionality) while keeping the main virtues of DEA and FDH (they are fully nonparametric). In this article we apply not only the non-convex counterpart of DEA (FDH) but also order-mand order-αpartial frontiers to a sample of US mutual funds. The results obtained for both order-mand order-αare useful, since a full ranking of the mutual funds' performance can be obtained. We merge these methods with the literature on mutual fund performance persistence. By combining the two literatures we derive an algorithm which establishes how the choice of m and α parameters intrinsic to order-mand order-α(respectively) relate to the existence of performance persistence and the contrarian effect.

Excess Autocorrelation and Mutual Fund Performance

We develop a new measure to predict mutual fund performance based on the microstructure evidence on stealth trading. We exploit the intuition that strategic stealth trading induces positive autocorrelation in the portfolios of informed investors. The degree of portfolio return autocorrelation of the funds therefore carries information to gauge their skills. We propose an autocorrelation-based measure of mutual fund portfolio returns, termed the excess autocorrelation – the difference between the autocorrelation of actual fund portfolio return and that of the return on a portfolio that invests in the previously disclosed fund holdings. We test our measure using the US mutual fund industry between October, 1998 and December, 2010. The results show that funds with high excess autocorrelation persistently display a net-of-risk performance that ranges between 2 and 3 percent per year. Such performance is predictable up to 12 months ahead. This suggests that the excess autocorrelation predicts fund performance.

Mutual Fund Performance and Families

Using a large and long sample of US and European mutual funds we examine the impact that the membership of a fund family has on performance. We test for strategic and competitive behaviour among family funds and whether this affects performance persistence and risk taking behaviour. We find no conclusive evidence of stronger performance persistence among family funds versus non-family funds, although we do find some significant differences in the future performance of portfolios of family and non-family funds formed on the basis of past performance. However, we do provide strong evidence to suggest that a fund’s mid-year ranking within its family affects its risk over the remainder of the year and, most interestingly, that family mid-year rankings have a different impact in the US mutual fund industry than it does in its European equivalent. Among US funds, the results point to intra-family competition where mid-year losers increase risk by more than mid-year winners in an attempt to catch up. The opposite is found to be true for European family funds. Our results therefore highlight significant differences in the ways in which the US and European fund management industries operate.

Panel Data Models with Grouped Factor Structure Under Unknown Group Membership

This paper studies panel data models with unobserved group factor structures. The group membership of each unit and the number of groups are left unspecified. We estimate the model by minimizing the sum of least squared errors with a shrinkage penalty. The regressions coefficients can be homogeneous or group specific. The consistency and asymptotic normality of the estimator are established. We also introduce new Cp-type criteria for selecting the number of groups, the numbers of group-specific common factors and relevant regressors. Monte Carlo results show that the proposed method works well. We apply the method to the study of US mutual fund returns under homogeneous regression coefficients, and the China mainland stock market under group-specific regression coefficients.

Market Transparency and the Marking Precision of Bond Mutual Fund Managers

We analyze the dispersion of month-end prices simultaneously placed on identical corporate bonds by different US mutual fund managers before and after initiations of TRACE and introductions of issuers into Markit’s CDS database. Disseminated bonds show large and statistically significant decreases in mark dispersion around three key TRACE system rollout events, including important spillover effects for non-disseminated bonds. Dispersion for large, investment grade bonds fell 20% to 83% after the start of TRACE reporting. A difference-in-differences regression analysis of the two-stage rollout of BBB-rated bonds provides clearer evidence suggesting that TRACE led to a decrease in mark dispersion for all bonds via a matrix pricing channel in addition to any direct dissemination impact. TRACE-associated improvement in bond valuation precision provides indirect support for Bessembinder, Maxwell, and Venkataraman’s (2006) information-based channel relating transparency and pricing. During the pre-TRACE period, we also find some evidence that mark dispersion fell for investment grade issuers after introductions into Markit’s database.

Who Buys the Worst Mutual Funds? Fund Performance and Investor Characteristics

The abundant empirical evidence on the persistence of mutual fund underperformance raises the question of who buys those funds that are expected to underperform. Although this question has attracted the interest of researchers, extant studies are limited to a few small markets or to a subset of the US market and specific sample periods. In order to study the behavior of investors in the universe of US mutual funds, we use the sociodemographic characteristics of visitors to mutual fund websites to proxy for investor characteristics. We find that differences in sociodemographic characteristics are systematically associated with predicted fund performance in the US market: Funds with a higher fraction of female, older or low-income investors are associated with worse predicted performance. We also find that differences in the optimality of investor choices across investor sociodemographic groups can be explained by differences in sensitivity to past performance and fund fees. Finally, there is limited evidence that fund marketing can explain why some groups of investors buy the underperforming funds. Although some of our findings confirm those of previous studies, others are in clear contradiction, which further supports the need to explore new data sets.

Rating Mutual Funds Through an Integrated DEA-Based Multicriteria Performance Model: Design and Information Content

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 (MCDA) methodology. DEA is employed to assess the relative efficiency of mutual funds in terms of their return, size, 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 on a large sample of more than 500 US mutual funds over the period 2003-2010. The analysis is implemented under three different time-window periods (one, three, and five year evaluations) and the results are compared against the fund ratings provided by Morningstar.

Should Mutual Funds with High Flow Correlation Change Their Strategy?

I investigate the economic importance of correlation in mutual fund flows for funds with overlapping portfolio positions. I illustrate theoretically that systematically correlated trading patterns between funds have a negative impact on asset prices and should influence portfolio choice. Theoretically, I show that the expected return from an asset is conditional on the contemporaneous trading pattern of the asset holder, once trading needs are not i.i.d. Finally, I derive a theoretical upper bound of optimal flow correlation and make the conjecture that an optimal equilibrium portfolio outcome exists for any combination of pairwise fund flow correlations. Empirically, I construct a measure of portfolio adjusted flow correlation and find that co-movement in flows can significantly deteriorate fund performance in the long-run, by about 1.4% annually, measured adjusted for style between peer funds with high and low correlation. Finally, I find that around one third of US mutual funds holds non-optimal portfolios as far as dynamic liquidity from correlated trading patterns is concerned.

Do Equity Mutual Funds Really Perform Less Poorly in Bad Times? Evidence from US and Australia

We find that in Australia, Mid/Small-cap funds often have significantly positive net alphas and this is driven by their strong performance in down-markets. In contrast Large-cap funds often have significantly negative net alphas and this is driven by their relatively poor performance in up-markets which cannot be offset by their performance in down-markets. We also find that Australian Large-cap funds generally reduce their market betas in down-markets while Australian Mid/Small-cap funds generally increase their market betas in down-markets. In the US, funds in all categories generally perform strongly in up-markets but perform poorly in down-markets which leads to negative unconditional alphas being observed. We also find that many US mutual funds increase their beta in down-markets which contributes to their poor performance in down-markets. In the US, funds also tend to perform relatively strongly in non-recessions but poorly in recessions. Despite the fact that these funds reduce their market betas in recessions they still do not achieve positive alphas in those periods.

Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition

When analyzing relative performance, especially at the institutional level, the traditional data envelopment analysis (DEA) models do not recognize vastly different and important activities as separate functions and therefore cannot identify which function may be the main source of inefficiency. We propose a novel two-stage DEA model that decomposes the overall efficiency of a decision-making unit into two components and demonstrate its applicability by assessing the relative performance of 66 large mutual fund families in the US over the period 1993–2008. By decomposing the overall efficiency into operational management efficiency and portfolio management efficiency components, we reveal the best performers, the families that deteriorated in performance, and those that improved in their performance over the sample period. We also make frontier projections for poorly performing mutual fund families and highlight how the portfolio managers have managed their funds relative to the others during financial crisis periods.

Local Bias and Stock Market Conditions

When markets’ volatility surges, financial integration drops. This may reflect an increase in international barriers, wealth effects, or rather an increase in the preference for geographically close investments. Since such preference for local stocks also applies to portfolios of domestic stocks, we exploit the domestic portfolios of US mutual funds to provide microeconomic evidence that investors are more likely to liquidate geographically remote investments at times of high aggregate market volatility. This has important implications for asset prices. The valuations of stocks with ex ante less local ownership decline more when aggregate market volatility is high. Furthermore, the returns of stocks with geographically distant owners are more exposed to changes in aggregate market volatility. As a consequence, it appears that local ownership can mitigate the effects of market-wide shocks.

False discoveries in volatility timing of mutual funds

This paper examines the volatility timing of US mutual funds by controlling the false discovery rate to find out how many funds are truly countercyclical (procyclical) timing funds. Empirical results show that, given the whole universe of our sample funds, the percentages of countercyclical and procyclical volatility timing funds are about equal. We also find that while the standard approach, which simply counts the number of significant positive (negative) timing coefficients, does not incorporate false discoveries in volatility timing, it provides quite accurate volatility timing results. Finally, we find that the performance measures for an equally weighted portfolio of procyclical timing funds are greater than for an equally weighted portfolio of countercyclical timing funds in the in-sample test, consistent with our expectation that procyclical timers earn higher returns because they take on more risk. However, the countercyclical timing portfolio outperforms the procyclical timing portfolio in the out-of-sample test.

Performance Measurement with Market and Volatility Timing and Selectivity

To measure the investment performance of a portfolio manager who may engage in market timing, it is necessary to consider both market level and volatility timing behavior as well as security selection ability. We develop and implement measures that accommodate all three components. A well specified measure of performance is the sum of the three components of ability. Estimating the measures on active US mutual funds, we find that allowing for market level and volatility timing, there is no evidence of investment ability at the level of broad groups of mutual funds, or when funds are sorted by expense ratio, return gap, active share or turnover. However, sorting by factor model R-squares confirms results in Amihud and Goyenko (2011), where the low R-square funds have better performance.

Are performance measures equally stable?

Managed portfolio performance evaluation is an important issue from both academics’ and investors’ points of view. One important aspect concerns the choice of the measure used to assess performance, because each index offers a different perspective about the trade-off between return level and risk exposure. A related crucial issue is the stability of measures over time and, hence, their predictive power about future results. In this work, we address the problem of evaluating of the stability of a performance measure. First, we discuss the use of alternative criteria to measure stability and propose a stability index based on changes of ranks over several periods of time. We also propose a statistical test to evaluate the homogeneity of the stability of alternative performance measures. Second, we suggest a composite performance measure, built as a linear combination of various indexes, specifically conceived to be maximally stable over time while preserving information about risk-adjusted return behavior. An application to a set of US mutual funds belonging to the Large Blend category shows how these methods work.

The factor structure of mutual fund flows

Common factors in mutual fund flows explain significant fractions of annual and quarterly flows to individual US mutual funds. The factors are persistent and correlated with financial market conditions and macroeconomic variables. We find evidence that the common factors in investor flows are forward looking, although subject to frictions. The systematic components of flows differ substantially across funds according to funds’ ‘flow betas’. High-performing funds’ common factor flows bear an option-like relation to the aggregate sector flows, suggesting a new dimension in the incentives of fund managers. High flow beta funds offer low subsequent returns, consistent with adverse price pressure effects.

Investing in Tough Times: What Investors’ Behavior Across the Business Cycle Tells About the Mutual Fund Market

In academic literature mutual fund investment has been traditionally studied from the perspective of an optimal portfolio allocation problem. An increasing body of empirical and experimental evidence has suggested that the investors’ behavior share remarkable similarities with the behavior of buyers in consumer goods markets. In this study develop and test a number of hypotheses based on empirical evidence in marketing literature. Using data on US mutual funds from 1991 to 2011 I show that investors price awareness (sensitivity of investment flows to expense ratios) increases as the macroeconomic environment worsens. I also show that this effect is due to expectations of future economic hardship rather than to the current situation. These results are robust to alternative explanations based on time-varying risk aversion, informativeness of past performances and competition from low-cost passive funds. Finally, using a new dataset of advertising expenditures I show that advertising becomes more effective in tough times, also due to the fact that, contrary to common beliefs, high advertising budgets are paid through increased volumes rather than higher expense ratios.

Voting Decisions at US Mutual Funds: How Investors Really Use Proxy Advisers

Voting Decisions at US Mutual Funds: How Investors Really Use Proxy Advisers

What Drives Market Share in the Mutual Fund Industry?*

This article examines competition and investor behavior in the mutual fund industry for the universe of US mutual funds during 1976-2009. Over this period, industry assets increased by a factor of 200, the number of active fund families quadrupled, and the average market share of a fam- ily declined by four-fifths. We find that price competition and product differentiation are both effec- tive strategies in obtaining market share. Families that pass along economies of scale to investors and those that charge lower fees than the competition gain market share, but only if these fees are above average to begin with. Loads and 12b-1 fees, however, have a positive effect on market share, con- sistent with the use of these types of fees for marketing and distribution. Families that perform better, offer a wider range of products, and start more funds relative to the competition (a measure of in- novation) also have a higher market share. Innovation is rewarded more if the new fund is more differentiated from existing offerings. Overall, our evidence suggests that mutual fund families com- pete effectively along both price and non-price dimensions.

Disposition effect and mutual fund performance

This article finds strong evidence for the presence of the disposition effect among US mutual fund managers. The analysis can establish a link between the disposition effect and mutual fund characteristics as well as changes in the macroeconomic environment. Managers with a lower disposition effect are found to invest in larger equities with a higher trade volume, a higher past performance, lower idiosyncratic risk, and a higher risk-adjusted performance. However, fund characteristics and the economic environment can only explain a limited amount of the variation in the disposition effect across mutual funds. Using a new methodology to reduce the disposition effect exhibited by mutual fund investments, we find no increase in their profitability. Although statistically significant, the disposition effect has only a minor economic effect on fund performance.