Smith Faculty Opinion Article	March 2008
By Dr. John A. Haslem, Professor Emeritus                                                                       E-MAIL       WEB SITE

Another Look At S&P 500 Retail Index Funds

Written by John A. Haslem, H. Kent Baker and David M. Smith
Monday, 24 March 2008 23:05

A long-standing debate exists about whether a mutual fund’s performance is due to the quality of management, other fund attributes or just luck. Although some portfolio managers of actively managed funds may have stock-picking talent, actively managed funds, on average, underperform benchmark portfolios with equivalent risk.

An implication of the underperformance of most actively managed mutual funds is that investors should be better off in low-cost index funds. The often-presumed commoditylike nature of index funds suggests that price competition should be stronger than for actively managed funds. Managers operate index funds not to beat their benchmarks or actively managed funds, but to mimic benchmark portfolios and performance before expenses. This “passive management” requires skill, but of a different sort than in actively managed funds.

These skills include minimizing transaction costs in matching the composition of the benchmark index, and using futures to compensate for the effects of “cash drag.”

If strong price competition exists among index mutual funds, only nominal size-adjusted differences in the expense ratios of S&P 500 Index funds should be present. But are all of these funds equally adept at tracking the “returns” of the S&P 500 Index? The answer is “no.” S&P 500 Index funds should not be viewed as financial commodities. Thus, examining the size of their expense ratios, attributes related to them and fund performance results is important.

Data And Method

We examine 136 retail S&P 500 Index funds identified by Morningstar at year-end 2006 and use expense ratios as a percent to measure mutual fund costs.1 Expenses are particularly relevant because they tend to be stable. Because fund expenses are one of the few predictable aspects of investing, investors selecting a fund could benefit by considering these expenses.

The expense ratio is total expenses divided by fund average net assets.2 Total expenses consist of three components: (1) management fees, (2) Rule 12b-1 fees, and (3) other expenses including transfer agent fees, securities custodian fees, shareholder accounting expenses, legal fees, auditor fees and independent director fees. The regulatory definition of total expenses is not an all-inclusive measure. It excludes sales charges and fees directly charged to shareholder accounts and portfolio transaction costs (brokerage fees, bid/ ask spreads, and market impact and other trading costs) that reduce portfolio and shareholder returns.

Univariate Analysis

We begin by classifying the 136 index mutual funds into quartiles based on their expense ratios. Funds in Quartiles 1 and 4 have the lowest and highest expense ratios, respectively. Next, we examine the relation between expense ratio class and selected performance measures. We use three well-known performance measures: three-year Sharpe ratios, three-year Jensen’s alphas and annualized total returns for multiple periods (one, three and five years). The Sharpe ratio assesses risk-adjusted portfolio returns using standard deviation as the measure of total risk, and Jensen’s alpha assesses risk-adjusted portfolio returns using systematic risk.

We use the Wilcoxon two-sample test to determine whether the values in Quartile 1 and Quartile 4 differ significantly. Using this univariate test, we expect that performance, as measured by each median Sharpe ratio, Jensen’s alpha and annualized total return is statistically greater in the low-expense ratio class (Quartile 1) than in the high-expense ratio class (Quartile 4). Thus, we expect a negative relation between expense ratio class and each performance measure.

Mutual fund expenses are known to be an important determinant of returns. Front loads and deferred charges reduce investor returns but are not included in the regulatory expense ratio. Thus, funds with low (high) loads are also likely to have low (high) expense ratios. Unlike front loads and deferred charges, 12b-1 fees are a component of the regulatory expense ratio. Marketing expenses paid for by the fees allowed under Rule 12b-1 could increase or decrease a fund’s expense ratio.

Proponents of the 12b-1 fee argue that imposing the fee could allow funds to decrease other loads, especially front-end loads, which would in turn attract investors and reduce the expense ratio due to increased economies of scale.

We anticipate that median front-end loads, deferred charges and 12b-1 fees are statistically smaller in the lowexpense ratio class (Quartile 1) than in the high-expense ratio class (Quartile 4). Thus, we expect a positive relation between expense ratio class and each of these three attributes.

Other attributes may have a negative relation with mutual fund expense ratios. Fund size, with increasing economies of scale, provides reductions in fund expense ratios. This reduction in expense ratios is further encouraged by funds with stated reductions in management fees at increasingly large asset breakpoints. The extent to which these size-induced savings are passed along to shareholders remains an issue of debate.

Fund age and size are closely related. Older mutual funds tend to be larger than the younger ones and tend to benefit more from economies of scale. As such, fund age is generally considered to be negatively associated with expense ratios.

We expect that median fund size and age are statistically larger and older in the low-expense ratio class (Quartile 1) than in the high-expense ratio class (Quartile 4).

A relation could also exist between expense ratio class and other attributes. For example, cash holdings and turnover may help to explain variations in expenses of actively managed mutual funds. Funds with larger cash holdings may incur relatively smaller portfolio management expenses and transaction costs in anticipating and providing liquidity to meet shareholder redemptions. On the other hand, large cash holdings are likely to produce an unacceptable degree of “cash drag” in a generally rising market. Index fund portfolios are managed to match those of their index benchmarks, which suggests they have smaller cash holdings with less variance.

Further, index funds do not adjust their cash holdings in efforts to time the market. Thus, in this context, cash holdings of S&P 500 Index funds may well not differ significantly by expense ratio class.

Turnover serves as a proxy for the level of trading activity and associated transaction costs. These costs reduce fund and investor returns and are not included in the regulatory expense ratio. Portfolio turnover may have some small positive association with management fees and other expenses, which are included in the expense ratio. Unlike actively managed funds, the level of trading activity of S&P 500 Index funds is unlikely to differ significantly regardless of the expense ratio class. We expect that median cash holdings and turnover do not differ statistically between the low-expense ratio class (Quartile 1) and the high-expense ratio class (Quartile 4).

Multivariate Analysis

We use a multiple regression model to examine whether mutual fund descriptors, specifically expense ratios and related attributes, are useful in explaining fund performance.3 Both models of performance contain a dummy variable indicating the presence or absence of a 12b-1 plan. Our model includes this variable and five others from the latter study that control for fund size, cash holdings, turnover and the magnitude of front-end and deferred charges. For this portion of the analysis, we combine with our index fund sample all actively managed large-cap blend domestic equity funds (the same Morningstar equity-style box cell occupied by S&P 500 Index funds) to accompany the index fund sample. To facilitate pooling of disparate funds for the regression, our model includes a dummy variable indicating whether funds are passively or actively managed.

Empirical Results

We present our empirical results in Figures 1 through 4. Figure 1 shows the number of retail S&P 500 Index funds and their expense ratios for the period 1992–2006. Over the 15-year period, the number of these index funds increased from nine in 1992 to 136 in 2006. The median expense ratio also trended upward, from 0.350 percent in 1992 to 0.630 percent in 2006.

The unweighted mean has increased over time. The mean as weighted by each fund’s net assets remained between 23 and 26 basis points for many years, and recently it has fallen to about 20 basis points. The standard deviation suggests that the range of expense ratios is tightening. Finally, each year we sort funds by expense ratio and then identify the fund in which the median dollar is invested. We find that over time, the median dollar has been invested in a fund charging between 18 and 20 basis points per year. Clearly, the proliferation of new funds and fund classes has not resulted in additional low-cost choices for investors, as evidenced by the steady upward trend for the median and unweighted mean. On the other hand, the rightmost two columns suggest that most investors continue to pour money into the lowest-cost alternatives.

Figure 2 summarizes the median expense ratios for the 136 S&P 500 Index funds in each quartile for 2006. The expense ratios increase with each higher class from 0.27 percent in the low-expense ratio class (Quartile 1) to 1.29 percent in the high-expense ratio class (Quartile 4). As later shown in Figure 3, the median expense ratio in Quartile 1 is significantly lower than that in Quartile 4.

Univariate Results

Figure 3 summarizes the median attributes of the retail S&P 500 Index funds by expense ratio class. We generally report the results using medians instead of means because the underlying variables tend to be non-normally distributed. Figure 3 also reports the results for a univariate analysis between expense ratio classes (Quartiles 1 and 4) and various fund attributes.

Panel A of Figure 3 shows the results of our univariate tests involving the implied impact of expense ratios on returns for the 136 retail S&P 500 Index funds. As expected, funds in the low-expense ratio class (Quartile 1) significantly outperform those in the high-expense ratio class (Quartile 4) based on the Sharpe ratio, Jensen’s alpha and annualized total returns over one-, three- and five-year periods. Each performance measure decreases monotonically when moving across expense ratio classes from Quartile 1 to Quartile 4. For example, three-year annual total returns decrease as follows: 10.16 percent (Quartile 1), 9.85 percent (Quartile 2), 9.71 percent (Quartile 3) and 9.03 percent (Quartile 4). These findings are consistently strong. Panel B of Figure 3 shows the relation of expense ratio class to other mutual fund attributes. As expected, funds in the low-expense ratio class (Quartile 1) have significantly smaller deferred charges and 12b-1 fees than those in the high-expense ratio class (Quartile 4). None of the 33 funds in Quartile 1 has deferred charges, but 32 of the 35 funds (91.4 percent) in Quartile 4 do. Only six of the 33 funds (18.2 percent) in Quartile 1 have 12b-1 fees, but all 35 funds in Quartile 4 do.

Front-end loads do not differ significantly between funds in the low- versus high-expense ratio classes. Only 24 of the 136 funds (17.6 percent) have front-end loads, possibly because informed investors recognize them as avoidable costs. The fact that only two of 33 funds (6.1 percent) in Quartile 1 and zero of 35 funds in Quartile 4 charge front-end loads helps to explain the lack of a significant difference between Quartiles 1 and 4.

The findings are also consistent with our expectations involving the relation between expense ratio class and other attributes. The median net assets in the low-expense ratio class ($459.50 million) are significantly larger than those in the high-expense ratio class ($17.30 million). Funds are significantly older in the low-expense ratio class (10.67 years) than those in the high-expense ratio class (6.96 years). Thus, a negative relation exists between expense ratio class and both fund size and age. Although median cash holdings are larger in the high- versus low-expense ratio class (1.90 percent and 1.50 percent, respectively), no significant difference exists in cash holdings between Quartiles 1 and 4. Findings of no significant difference also apply to turnover. As expected, the median turnover is only 6 percent in both Quartiles 1 and 4.

Sorting our sample of 136 retail S&P 500 Index mutual funds by expense ratio class and aggregating net fund assets, we find that some 15 percent of assets are in funds in expense ratio classes above the group median (Quartiles 3 and 4). Thus, retail investors have placed about 85 percent of their assets in low-expense S&P 500 Index funds (Quartiles 1 and 2). These findings are consistent with a degree of price competition among the higher-performing funds.

Note: Sharpe ratios and Jensen’s alphas are three-year. Returns are annualized for the period ending December 31, 2006. Loads are one-year front-end loads. The rightmost column indicates whether the values in Quartile 1 and Quartile 4 differ significantly, according to Wilcoxon two-sample tests. The number of funds is 136 unless otherwise indicated.
* and ** indicate significance at the 0.05 and 0.01 levels, respectively.

What may explain the sizable expense dispersion among retail S&P 500 Index mutual funds despite the relative homogeneity of their portfolios? One explanation is that for retail S&P 500 Index funds, expense dispersions are not explained by portfolio performance alone, but also by nonportfolio differentiation and information-search frictions.4 As for nonportfolio differentiation, our evidence may help to explain why high-priced index funds exist. High-expense funds, on average, have lower minimum initial purchase amounts. As Panel B of Figure 3 shows, the median minimum initial purchase for funds is $1,000 in Quartiles 2, 3 and 4 but $3,000 in Quartile 1. Thus, some retail investors may be unable to buy funds in the low-expense category because they cannot meet the minimum initial purchase requirement.

Multivariate Results

In our final step, we test a multiple regression model that relates annualized returns to expense ratios, while holding constant for other fund characteristics such as fund size, cash holdings, turnover rate, load and whether the fund has a 12b-1 fee. By the normal measures of cross-sectional analysis such as adjusted R2 and the F-statistic, our model performed well in explaining fund returns.

As Figure 4 shows, we find a strong negative relation between the annualized return and the expense ratio. The magnitudes of our regression coefficients show that after controlling for other major mutual fund attributes, an increment of 1 percentage point in the expense ratio is associated with about a 1 percentage point lower annual return. This result holds for both three-year and five-year annualized returns. This apparent economic and statistical significance supports investor use of the expense ratio as an indicator of relative investment merit.

Conclusions

We analyze the expense ratio and attributes affecting the performance of 136 retail S&P 500 Index funds. These funds are among the simplest of financial vehicles. Nonetheless, the expense ratios and performance of these benchmark trackers differ significantly.

Our univariate analysis shows that mutual fund performance, as measured by the median Sharpe ratios, Jensen’s alphas and annualized total returns, increases as expense ratios decrease.

In addition, a positive relation exists between expense ratios, deferred charges and 12b-1 fees. By contrast, fund size and age are negatively related to expense ratios. Thus, our analysis of mutual fund expenses suggests expense-conscious retail investors should look carefully at the deferred charges, 12b-1 fees, size and age of the S&P 500 Index fund before investing. Our multivariate model provides evidence that the expense ratios help to explain performance; that is, lower expense ratios are strongly related to higher returns.

What are the implications of our findings? Investors often view index mutual funds as financial commodities because of the often-held assumption that funds tracking the same benchmark index should not differ in any meaningful way. Our evidence of large differences in expense ratios across retail S&P 500 Index funds casts serious doubt on this term as a descriptor of these funds. One explanation for the presence and enduring popularity of high-priced index funds is that some uninformed investors are paying high costs without receiving commensurate benefits. Another explanation is that such funds tend to require significantly lower minimum initial purchase amounts. The evidence suggests that despite less-than-perfect price competition among the whole of S&P 500 Index funds, the S&P 500 Index funds with the lowest expense ratios (Quartile 1) attract the majority of retail investors’ funds.

Endnotes

1 Morningstar Principia Pro for Mutual Funds Advanced Module, January 2007 (CD).

2 U.S. Securities and Exchange Commission, “Report on Mutual Fund Fees and Expenses.” Washington, D.C.: Division of Investment Management, December 2000.

3 Our model follows those proposed by D. K. Malhotra and Robert W. McLeod, 1997, “An Empirical Analysis of Mutual Fund Expenses,” Journal of Financial Research 20 (2), 175–190; and Wilfred L. Dellva and Gerard T. Olson, 1998, “The Relationship between Mutual Fund Fees and Expenses and Their Effects on Performance,” Financial Review 33 (1), 85–104.

4 See Ali Hortaçsu and Chad Syverson, 2004, “Product Differentiation, Search Costs, and Competition in the Mutual Fund Industry: A Case Study of S&P 500 Index Funds,” Quarterly Journal of Economics 119 (2), 403–456.

This article is reprinted with the permission of the Journal of Indexes, which is the publication of record for the index industry. Any rebroadcast or distribution of this content requires the expressed permission of the Journal of Indexes. All Journal of Indexes content, including past columns by Professor Haslem can be accessed on www.indexuniverse.com/JOI . 
John A. Haslem, Professor Emeritus of Finance, University of Maryland.
H. Kent Baker, University Professor of Finance, American University, Washington, DC.
David M. Smith, Associate Professor of Finance, University at Albany, SUNY. Professor Baker is a doctoral graduate of the Smith School and Professor Haslem was his dissertation advisor.