There can be large differences in passively managed funds, even those within the same asset class. Larry Swedroe looks at 3 small value funds and shows how their performance is explained by exposure to factors-asset pricing models.
Index funds and structured passive asset class funds are similar in the way that rectangles and squares are similar. All squares are rectangles, but not all rectangles are squares.
Similarly, while all index funds are passively managed, not all passively managed structured asset class (or factor-based) funds attempt to replicate the returns of popular retail indexes like the S&P 500 or the Russell 2000.
Structured portfolios tend to use academic definitions of asset classes, building portfolios that seek to minimize the weaknesses of indexing. Those weaknesses, which result from the desire to minimize what is called “tracking error,” include:
Another advantage of structured funds, in return for accepting tracking error risk, is that they can gain greater exposure to the factors for which there is persistent and pervasive evidence of a return premium (such as size, value, momentum, profitability, momentum, carry, term).
For example, a small value fund could be structured to own smaller and more “value-y” stocks than a small-cap value index fund. It can also be structured to have more exposure to highly profitable companies, and it can screen for the momentum effect (avoiding buying stocks that are exhibiting negative momentum, and delaying selling stocks with positive momentum).
Sizing Up The Numbers
The following table, using data from Bridgeway as of Dec. 31, 2018, shows the various metrics for three passively managed small value funds from three different fund families—the index fund of Vanguard and the structured funds of Dimensional Fund Advisors and Bridgeway.
The table provides the weighted average market capitalization to show each fund’s relative exposure to the size premium, and four different value metrics—price-to-earnings (P/E), price-to-book (P/B), price-to-sales (P/S) and price-to-cash flow (P/CF)—to show the relative exposure to the significant premium provided by value stocks. (Full disclosure: My firm, Buckingham Strategic Wealth, recommends Bridgeway and Dimensional funds in constructing client portfolios.)
The Vanguard fund has a much larger average market cap and significantly higher valuations relative to each metric than the Dimensional fund, and the Dimensional fund has a much larger market cap and higher P/E and P/CF valuations than the Bridgeway Fund (and the same P/B and P/S ratios).
Is Performance A Match?
With the data and concepts in mind, let’s now take a look at how the funds have performed—did we get what we expected? Since the first full year for Bridgeway’s fund was 2012, we will examine the returns for the last seven calendar years (2012–2018). To see if we got what we expected, we will also look at the returns of Vanguard 500 Index Fund (VFINX). The following returns data is from Morningstar.
Note that Vanguard’s small value fund includes about 12.5% of real estate investment trusts (REITs), while Dimensional’s and Bridgeway’s funds do not, because REITs are treated by those firms as separate asset classes. That can create/explain some of the differences in performance.
Note how well the exposure to the factors of size and value explain the relative performance of the three funds. There were just two outliers in the data—the underperformance of BOSVX in 2012 and its outperformance relative to DFSVX in 2015 (in both cases, the likely explanation is random tracking error).
There are a few important takeaways. The first is that all three passively managed funds were doing their jobs well. The differences in performance aren’t explained by good or bad management. Instead, they’re explained by the fund’s structure—how they’re designed, and the “laws of style purity.”
When an asset class does well, you should expect the fund with the most exposure to the factors explaining its outperformance to have the highest return. And when an asset class does poorly, you should expect the fund with the most exposure to the factors will underperform.
The second is that choosing a fund should be based on how much exposure you want to the factors, and also a fund’s expense ratio. When making the decision, you want to be sure you weigh both. It might be that the fund with a higher expense ratio is the better choice, as it might have more exposure to the factors that determine returns and carry premiums. In other words, it is not just cost, but cost per unit of expected return (and risk), that matters. The following example demonstrates the importance of understanding this issue.
While VISVX has an expense ratio of 0.19% (their Admiral shares version costs just 0.07%) and DFSVX has an expense ratio of 0.52%, the higher costs of the Dimensional fund have been more than offset by their greater exposure to the size and value factors and their focus on adding value by minimizing the negatives of pure indexing. For the full period that both have existed—June 1998 through December 2018—DFSVX returned 8.6%, outperforming the lower cost VISVX, which returned 7.9%.
In addition, despite its higher expense ratio, from inception in September 2011 through December 2018, BOSVX returned 9.7%, slightly outperforming DFSVX (despite the fact that small value significantly underperformed over the period, with VFINX returning 12.5%). With the underperformance, you should expect that VISVX would have outperformed both DFSVX and BOSVX (which it did), returning 10.9%. The returns data is from Portfolio Visualizer.
Another important point to cover is the psychological bias known as “recency.” Recency bias causes investors to allow recent returns to dominate decision-making while ignoring long-term evidence.
Over the most recent decade, small value stocks have underperformed the large stocks that make up the S&P 500 Index. That underperformance explains the relative performance of the three small value funds, with VISVX producing the strongest returns.
I’ve learned that one of the greatest problems preventing investors from achieving their financial goals is that, when it comes to judging the performance of an investment strategy, they believe that three years is a long time, five years is a very long time and 10 years is an eternity.
Even supposedly more sophisticated institutional investors—those who employ highly paid consultants—typically hire and fire managers based on the last three years’ performance. On the other hand, financial economists know that, when it comes to investment returns, 10 years can be nothing more than “noise,” a random outcome.
For example, we have had three periods of at least 13 years over which the S&P 500 underperformed riskless one-month Treasury bills:
Financial economists know that all risky assets go through long periods of poor performance, and it requires discipline to stay the course. Such long periods should not cause you to abandon your belief that riskier assets should have higher expected (but not guaranteed) returns.
The three periods of 13 years or longer of negative equity premiums demonstrate that this is just as true of large stocks as it is of small value stocks. The long-term evidence is that small value stocks have outperformed the S&P 500 Index. And that outperformance is intuitive, as small value stocks are much riskier.
For example, since 1927, while the standard deviation of the S&P 500 has been around 19%, it’s been about 28% for small value stocks, according to Fama-French data. Thus, we should not abandon our belief that small value stocks should outperform in the future, nor should we abandon our belief that DFSVX and BOSVX should have higher expected returns than VISVX because they have more exposure to the small and value factors.
The bottom line is that the returns of the three small value funds we examined are well-explained by their exposure to common factors (market beta, size, value and quality). And while VISVX has the lowest expense ratio, it’s cost per unit of exposure that matters, not just overall cost.
You should also consider the fund’s trading strategy—does it act as price-taker, or does it trade patiently?—as well as its fund construction rules, and its exposure to the common factors that explain returns.
The following table, with data from Portfolio Visualizer, provides the loadings (amount of exposure) for the three funds to various factors. The data covers the period September 2011 (inception of BOSVX) through December 2018.
Note that value exposure is measured by the price-to-book ratio. Also note how BOSVX has the highest exposure to the size and value factors, as well as the quality factor (because of its use of multiple value screens, including not just P/B but also P/CF and P/E and P/S).
Factor Loadings (September 2011-December 2018)
This commentary originally appeared January 31 on ETF.com
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