Abstract
We evaluate the performance of 51 mutual fund families based on a study of their diversified US managed mutual funds over an 11-year-period and explore the determinants of performance gross of published expenses. We find that mutual fund families which charge loads, high expenses to their most favored investors and have high turnover tend to perform badly, even gross of these fees. However, gross of published expenses, managed mutual fund portfolios of those families without loads, with low expenses in their least expensive class, and with low average turnover beat the corresponding indexes.
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Notes
Fidelity’s advisor funds are similar to their regular funds but not identical, which makes price discrimination seem more legitimate. Both types of funds have similar minimum investment requirements. AIM’s R class funds are identical to their advisor funds, except for the loads and expenses, and both have similar minimum investment requirements. It could be argued that loads and high expenses are ways that mutual fund families recoup the costs of serving small accounts and clients who need advice. But no load, low expense funds are available from some firms, sometimes even from the same firm, even for small accounts. Moreover, free and sensible advice is available on line from various sources, including Paul Merriman, GMO, and the Vanguard Diehards web discussion group.
Sharpe (1992) uses a similar technique. He does not suppress the constant term, and interprets the constant as the outperformance of the portfolio in question. His approach answers a slightly different question. It finds the tracking index whose return, apart from the constant term, has the smallest mean square deviation from that of the portfolio. The technique used here finds the tracking index whose return has the smallest mean square deviation from that of the portfolio. In practice, there is unlikely to be much difference between the two alternatives. In retrospect, though, we believe that Sharpe’s approach is better.
There is one exception. In constructing the tracking index portfolio, one needs to work with returns compounded monthly, not continuously.
We wanted a method of style adjustment that would show how much a portfolio of actively managed funds outperformed a basket of indexed mutual funds with the same style. Work by Eugene Fama and Ken French, available on French’s web site, shows that investment style explains fund returns. Their company, DFA, and popular pieces by Arnott et al. (2008), Hebner (2007), and Siegel (2005) have advised investors to disproportionately weight particular styles, especially small and value. Consequently, we wanted to show by how much the portfolio considered would beat the portfolio of indexes with the most similar style; hence, our style adjustment.
We wanted our method of risk adjustment to compare two portfolios with the same risk. The way many mutual fund investors reduce the riskiness of their portfolio is to increase the proportion of short-term bonds in their portfolio, and we wanted our method to reflect that. Since most investors cannot sell bonds short, we made the two portfolios comparable in risk by increasing the bond share in the riskier portfolio. We decided not to use the Sharpe or Treynor methods of risk adjustment, because we felt that comparing the returns of portfolios of comparable risk, as M2 does, was intuitively appealing, a view apparently shared by Bogle (2002b), who uses this technique in his comparison of indexed and actively managed funds. The Sharpe criterion is the gain in return per unit of risk undertaken, but this is of limited use to investors unless the amount of risk undertaken in the two funds is known. Suppose the diluting asset is truly riskless. Then the Sharpe criterion is the rate of return premium above the risk-free rate of a portfolio that combines the asset with the riskless asset in proportions that cause the standard deviation of return of the portfolio to equal one. Thus, if the diluting portfolio is truly riskless, the M2 criterion is a linear function of the Sharpe criterion. Consequently, ranking of a collection of mutual funds according to either criterion would be identical. In the real world, it is impossible to find an asset with a good return that generates a constant real rate of return over all periods within a time span, e.g., an inflation-protected treasury bill that offers a 1%/year real return over the next 10 years, regardless of when one cashes it in. Thus, our view is that M2 is a practical and intuitive method of risk adjustment.
We are interested in the risk associated with investing our entire wealth in a portfolio, not just adding a little bit of the portfolio to an indexed portfolio. Thus, we are interested in both systematic and unsystematic risk, which rules out the Treynor method. The M2 method is one of the mainstream ways of risk adjustment. For example, Bodie et al. 2008, pp. 591-2, give it a whole section, whereas Sharpe, Treynor and Jenson share one section.
With continuous compounding, the nominal return differential equals the real return differential when we do not risk adjust. But risk averse investors are more likely to pay attention to stable real returns than stable nominal returns, so for calculating the risk adjusted return differential, it is important to work with real returns.
The minimums for institutional funds refer to the minimum that an entire institution must invest with the company. So, for example, the employees of an institution may hold institutional class mutual funds with the same fund family and the aggregate of their holdings must be greater than the recorded minimum.
Sharkansky (2002) finds higher cost of turnover; he finds that each 100% age points increase in turnover reduces the annual return of large cap domestic funds by 1.24%/year, small cap domestic funds by 2.55%/year, and international funds by 1.54%/year. This is in addition to any impact on gross returns.
New York State Attorney General Elliot Spitzer has investigated nine fund families. We call them “bad boys”; they include Van Kampen, Goldman Sachs, Morgan Stanley, Putnam, Janus, Federated, AIM, Strong, and MFS. Those fund families have been charged, probed or fined by Spitzer Attorney Office. We looked through the reports online from various sources such as Wall Street Journal, CNN/Money, Business Week and Fortune to get this list of nine fund families.
Tables 1, 2 and 3, show that “bad boy” fund families did not perform well over the past 11 years. Their average expense ratio and turnover ratio are higher than those of the other 42 fund families. The average performance of the “bad boy” fund families, for both net return and gross return, regardless of risk adjustment, for both equally weighted return and historic return, trailed the average performance of the other 42 fund families. For example, the average gross return differential of their equally weighted portfolios, style adjusted, was 0.41% age points per year less than that of the other fund families. Therefore, those “bad boy” fund families are bad boys based on objective measures of performance as well as on the basis of attracting Spitzer’s attention. All these families have at least some load funds. Thus, loads are a marker for alleged bad behavior.
The late trading scandal is one of the focuses of Spitzer’s concern. The cost of turnover multiplies the cost of the late trading scandal. Not only do late traders deprive long-term investors of return directly, but they deprive them also by forcing up turnover. For more on this see Donnelly and Tower (2008).
Bernstein (2000) uses single independent variable regressions to calculate the impact of expense and turnover on net annualized return for different styles of mutual fund. He finds the impact of expense to be −2.15% age points/year for each 1% age point increase in the expense ratio. He finds turnover has a smaller effect on return than we do. He points out (1999) that Bogle (1999) finds a similar return/expense slope for large funds, −1.80. Our corresponding numbers from the multiple Eq. 4 are −1.29−1 = 2.29% age points/year for the impact of the minimum expense ratio on fund net continuously compounded return, and 0.713%/year for turnover. Our coefficient for expense is similar, but the absolute value of our coefficient for turnover is larger than Bernstein’s.
Bernstein treats different classes of the same mutual fund as different funds. If the average expense ratio over multiple classes of the same fund shrinks gross performance of the fund, we would expect that his regression would yield a lower impact of expense on gross return than explaining net return of each fund portfolio by a function of expense ratios for the various classes of the fund, although the fact that he uses annualized returns rather than continuously compounded returns should increase the coefficient.
The prediction is the 11-year gross return differential, SA, NRA, minus the expense ratio. These predictions are: Royce, 1.05% age points/year; Lord Abbett, 0.34% age points/year; American, 0.37% points/year; and Merrill Lynch, 0.15% points/year. They compare with the prediction for the Vanguard index portfolio of 0.07% age points/year. Of course in reality we would expect regression to the mean, so that fund families that have gross return differentials that deviate most substantially from the mean, will be closer to the mean in the future.
Bogle (2005b) argues that a conservative approach to selecting mutual fund families is to select those with low expense and turnover. We regressed gross return differential, SA, NRA on maximum loads, minimum expense, and turnover to predict gross return. Adding back in expense of the minimum class to predict net return of the minimum expense class, we find the only families to have positive predicted net return differentials are: DFA, 0.66% per year; GMO, 0.32%/year; T Rowe Price, 0.40% per year; and Vanguard Managed Funds, 0.77%/year. Thus, there are only four mutual fund families out of 51, whose predicted returns beat the indexes. Moreover, DFA funds are available only through advisors, and GMO has a minimum account size of $ 5 million.
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Acknowledgments
Thanks for help with the paper go to the referees, Charles Becker, William Bernstein, John Bogle, Hongleng Chua, Michael Connolly, James Dean, Simon Gervais, Omer Gokcekus, John Haslem, Susan Iddings, Nick Kaiser, Burton Malkiel, Michael Munger, Doug Pearce, Allan Sleeman, Thomas Willett, Cheng-Ying Yang and Pavel Zhelyazkov as well as seminar participants at the Claremont Graduate School, Wake Forest University and Western Washington University. Their approval of the final product is not implied. This paper is based on Zheng (2006).
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Tower, E., Zheng, W. Ranking mutual fund families: minimum expenses and maximum loads as markers for moral turpitude. Int Rev Econ 55, 315–350 (2008). https://doi.org/10.1007/s12232-008-0052-7
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DOI: https://doi.org/10.1007/s12232-008-0052-7