We noted earlier that one of the benefits of mutual funds for the individual investor is the ability to delegate management of the portfolio to investment professionals. The investor retains control over the broad features of the overall portfolio through the asset allocation decision: Each individual chooses the percentages of the portfolio to invest in bond funds versus equity funds versus money market funds, and so forth, but can leave the specific security selection decisions within each investment class to the managers of each fund.
Shareholders hope that these portfolio managers can achieve better investment perfor- mance than they could obtain on their own.
What is the investment record of the mutual fund industry? This seemingly straightfor- ward question is deceptively difficult to answer because we need a standard against which to evaluate performance. For example, we clearly would not want to compare the invest- ment performance of an equity fund to the rate of return available in the money market.
The vast differences in the risk of these two markets dictate that year-by-year as well as
average performance will differ considerably. We would expect to find that equity funds outperform money market funds (on average) as compensation to investors for the extra risk incurred in equity markets. How then can we determine whether mutual fund portfolio managers are performing up to par given the level of risk they incur? In other words, what is the proper benchmark against which investment performance ought to be evaluated?
Measuring portfolio risk properly and using such measures to choose an appropriate benchmark is an extremely difficult task. We devote all of Parts Two and Three of the text to issues surrounding the proper measurement of portfolio risk and the trade-off between risk and return. In this chapter, therefore, we will satisfy ourselves with a first look at the question of fund performance by using only very simple performance benchmarks and ignoring the more subtle issues of risk differences across funds. However, we will return to this topic in Chapter 11, where we take a closer look at mutual fund performance after adjusting for differences in the exposure of portfolios to various sources of risk.
Here we use as a benchmark for the performance of equity fund managers the rate of return on the Wilshire 5000 index. Recall from Chapter 2 that this is a value-weighted index of essentially all actively traded U.S. stocks. The performance of the Wilshire 5000 is a useful benchmark with which to evaluate professional managers because it corresponds to a simple passive investment strategy: Buy all the shares in the index in proportion to their outstanding market value. Moreover, this is a feasible strategy for even small inves- tors, because the Vanguard Group offers an index fund (its Total Stock Market Portfolio) designed to replicate the performance of the Wilshire 5000 index. Using the Wilshire 5000 index as a benchmark, we may pose the problem of evaluating the performance of mutual fund portfolio managers this way: How does the typical performance of actively managed equity mutual funds compare to the performance of a passively managed portfolio that simply replicates the composition of a broad index of the stock market?
Casual comparisons of the performance of the Wilshire 5000 index versus that of professionally managed mutual funds reveal disappointing results for active managers.
Figure 4.3 shows that the average return on diversified equity funds was below the return on the Wilshire index in 23 of the 39 years from 1971 to 2009. The average annual return on the index was 11.9%, which was 1% greater than that of the average mutual fund. 5
This result may seem surprising. After all, it would not seem unreasonable to expect that professional money managers should be able to outperform a very simple rule such as
“hold an indexed portfolio.” As it turns out, however, there may be good reasons to expect such a result. We explore them in detail in Chapter 11, where we discuss the efficient mar- ket hypothesis.
Of course, one might argue that there are good managers and bad managers, and that good managers can, in fact, consistently outperform the index. To test this notion, we examine whether managers with good performance in one year are likely to repeat that per- formance in a following year. Is superior performance in any particular year due to luck, and therefore random, or due to skill, and therefore consistent from year to year?
To answer this question, we can examine the performance of a large sample of equity mutual fund portfolios, divide the funds into two groups based on total investment return, and ask: “Do funds with investment returns in the top half of the sample in one period con- tinue to perform well in a subsequent period?”
5 Of course, actual funds incur trading costs while indexes do not, so a fair comparison between the returns on actively managed funds versus those on a passive index would first reduce the return on the Wilshire 5000 by an estimate of such costs. Vanguard’s Total Stock Market Index portfolio, which tracks the Wilshire 5000, charges an expense ratio of .19%, and, because it engages in little trading, incurs low trading costs. Therefore, it would be reasonable to reduce the returns on the index by about .30%. This reduction would not erase the difference in average performance.
Table 4.4 presents such an analysis from a study by Malkiel. 6 The table shows the frac- tion of “winners” (i.e., top-half performers) in each year that turn out to be winners or los- ers in the following year. If performance were purely random from one period to the next, there would be entries of 50% in each cell of the table, as top- or bottom-half performers would be equally likely to perform in either the top or bottom half of the sample in the following period. On the other hand, if performance were due entirely to skill, with no randomness, we would expect to see entries of 100% on the diagonals and entries of 0%
on the off-diagonals: Top-half performers would all remain in the top half while bottom- half performers similarly would all remain in the bottom half. In fact, the table shows
6 Burton G. Malkiel, “Returns from Investing in Equity Mutual Funds 1971–1991,” Journal of Finance 50 (June 1995), pp. 549–72.
Figure 4.3 Diversified equity funds versus Wilshire 5000 index, 1971–2009
−40
−50
−30
−20
−10 0 10 20 30 40 50
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 20082006
Rate of Return (%)
Average equity fund Wilshire return
Table 4.4
Consistency of investment results
Successive Period Performance Initial Period Performance Top Half Bottom Half A. Malkiel study, 1970s
Top half 65.1% 34.9%
Bottom half 35.5 64.5
B. Malkiel study, 1980s
Top half 51.7 48.3
Bottom half 47.5 52.5
Source: Burton G. Malkiel, “Returns from Investing in Equity Mutual Funds 1971–1991,” Journal of Finance 50 (June 1995), pp. 549–72. Reprinted by permission of the publisher, Blackwell Publishing, Inc.
that 65.1% of initial top-half performers fall in the top half of the sample in the following period, while 64.5% of initial bottom-half performers fall in the bottom half in the follow- ing period. This evidence is consistent with the notion that at least part of a fund’s perfor- mance is a function of skill as opposed to luck, so that relative performance tends to persist from one period to the next. 7
On the other hand, this relationship does not seem stable across different sample periods.
While initial-year performance predicts subsequent-year performance in the 1970s (panel A), the pattern of persistence in performance virtually disappears in the 1980s (panel B).
To summarize, the evidence that performance is consistent from one period to the next is suggestive, but it is inconclusive.
Other studies suggest that bad performance is more likely to persist than good perfor- mance. This makes some sense: It is easy to identify fund characteristics that will result in consistently poor investment performance, notably high expense ratios, and high turnover ratios with associated trading costs. It is far harder to identify the secrets of successful stock picking. (If it were easy, we would all be rich!) Thus the consistency we do observe in fund performance may be due in large part to the poor performers. This suggests that the real value of past performance data is to avoid truly poor funds, even if identifying the future top performers is still a daunting task.
The first place to find information on a mutual fund is in its prospectus. The Securities and Exchange Commission requires that the prospectus describe the fund’s investment objec- tives and policies in a concise “Statement of Investment Objectives” as well as in lengthy discussions of investment policies and risks. The fund’s investment adviser and its port- folio manager are also described. The prospectus also presents the costs associated with purchasing shares in the fund in a fee table. Sales charges such as front-end and back-end loads as well as annual operating expenses such as management fees and 12b-1 fees are detailed in the fee table.
Funds provide information about themselves in two other sources. The Statement of Additional Information or SAI, also known as Part B of the prospectus, includes a list of the securities in the portfolio at the end of the fiscal year, audited financial statements, a list of the directors and officers of the fund—as well as their personal investments in the fund, and data on brokerage commissions paid by the fund. However, unlike the fund prospec- tus, investors do not receive the SAI unless they specifically request it; one industry joke is that SAI stands for “something always ignored.” The fund’s annual report also includes
7 Another possibility is that performance consistency is due to variation in fee structure across funds. We return to this possibility in Chapter 11.