John Bogle: How Can We Compare Mutual Funds in an Effective Way?

Focusing on equity funds and index funds, within the context of lowest-cost investing

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Oct 23, 2018
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If you set out to buy a mutual fund, or if you are planning to build your own stock portfolio, you will face the issue of “styles.” For example, will you emphasize growth stocks or value stocks? What about large-cap stocks versus small-cap stocks? Or will you aim for a blend?

John Bogle offered answers to questions such as these in chapter six of “Common Sense on Mutual Funds: New Imperatives for the Intelligent Investor.” Overall, he observed that there is little, if any, evidence proving that some investment styles are more effective than others.

Regression to the mean inevitably arrives and levels individual fund returns with their appropriate market indexes, and equity styles level themselves with total stock market returns (all of this before costs).

While there is practically no evidence of persistence of returns among styles, there is a significant body of evidence that there is persistence of the relative risks assumed by individual funds. In other words, there is a “greater probability” of persistence in risk-adjusted returns than in total returns earned by individual funds.

So how can we compare mutual funds against each other in a systematic and effective way? Bogle reported that institutional investors formerly used a simple four-quadrant box, with capitalization on the vertical axis (large-cap/small-cap) and value/growth on the horizontal axis.

Then, Morningstar entered the arena, with its nine-box matrix, similar to a tick-tack-toe grid: three columns and three rows. Now capitalization could be further delineated, with large-, medium- and small-caps on the vertical axis. The same was true for the horizontal axis, which now showed value, blend and growth categories.

Bogle said, “The beauty of this system is that it immediately makes it possible to quantify the vital statistics of each fund’s performance relative to that of its peers, based on a combination of risk and return.”

For a five-year period ending in 1996, the returns were relatively similar: between 12% and 15%. At the same time, risks could be more sharply defined, where the variability of returns ranged from 9.8% for large-cap value funds to 18.7% for small-cap growth.

That leads to risk-adjusted returns, where there are large differences, reflecting the return that is earned for each unit of risk assumed by the fund.

Sharpening his argument further, Bogle argued there is no equal trade-off between risk and return:

“Here is the reality of investing, as I see it: An extra percentage point of standard deviation is meaningless, but an extra percentage point of return is priceless. Large differences in risk are extremely important—there is a difference between a stock portfolio and a bond portfolio—but the expedient of weighting risk and return equally, in a simple formula, leaves much to be desired. In the final analysis, risk-adjusted returns, like beauty, may be in the eye of the beholder.”

His tool of preference for measuring risk-adjusted returns is the Sharpe Ratio, which measures the excess return per unit of deviation in an investment security.

To illustrate, Bogle offered this example: Assume there are two funds with an equal volatility of 10%. Further, one fund has 1.20 risk-return ratio with a return of 16% while the second fund has a 0.60 risk-return ratio and a return on 10% (both assume a risk-free rate of 4%). Thus, there is a difference of 6%.

The Morningstar nine-box matrix can help us put these returns into context. Significantly different variations in the risk-adjusted return ratios reflect different risk levels in the nine market segments. Bogle said, “Often, variations were attributed to differences in manager skill, rather than to the fact that one manager invested in small-cap growth stocks while another plied his trade among large-cap value stocks. Style analysis enables investors to appraise the ability of managers to use the tools they have chosen.”

Among equity funds, Bogle looked at data for large-cap blend funds for the five-year period between 1992 and 1996. He found wide variations among total returns, while risk was quite consistent. So what caused the variation among the returns if it was not risk? Could it be manager skill, luck or “something more tangible”?

To answer those questions, he turned to the costs borne by unitholders. By separating the funds into cost quartiles, he was able to see the funds with the lowest expense ratios ended up in the first quartile for returns, while the funds with the highest costs were found in the fourth quartile for returns. So, in conditions where risk is roughly equal, funds with the lowest costs will produce the highest returns.

Taking his analysis a step further, he performed a statistical reversion that showed each 1% of expense ratio reduced the net total return by 1.8%. He attributed this to the idea that high-cost funds have higher turnover, thus running up substantial costs.

Finally, Bogle wanted us to consider the relationship between consequences and probabilities. If you believe the market is efficient, your best strategy will be to buy an index fund. If your strategy is wrong, you will still earn a market rate of return and only a few actively managed funds will beat you. If you believe the market is not efficient and you are wrong, “the consequences of underperforming with an actively managed fund could be very painful.”

In summary, chapter six of “Common Sense on Mutual Funds: New Imperatives for the Intelligent Investor” began with a discussion of styles and how their risk-adjusted returns could be compared using the Morningstar nine-box matrix. From there, he explored how styles and fund costs interrelated and again concluded low-cost index funds were the best types of funds.

(This article is one in a series of chapter-by-chapter reviews. To read more, and reviews of other important investing books, go to this page.)

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