William Sharpe, Jack Treynor, John Lintner and Jan Mossin are typically given most of the credit for introducing the first formal asset pricing model — the capital asset pricing model (CAPM). It was important because it provided the first precise definition of risk and how it drives expected returns.
Fama & French Take It Further
The CAPM looks at returns through a “one actor” lens, meaning the risk and return of a portfolio is determined only by its exposure to market beta. In the 1993 publication of the study “Common Risk Factors in the Returns on Stocks and Bonds,” Eugene Fama and Kenneth French proposed a new asset pricing model, which became known as the “Fama-French three-factor model.” This model proposes that, in addition to the market beta factor, exposure to the factors of size and value further explain the cross section of expected stock returns.
The authors demonstrated that we live not in a one-factor world but in a three-factor world. They showed how the risk and expected return of a portfolio is explained by not only its exposure to market beta but by its exposure to the size (small stocks) and price (stocks with low prices relative to book value, or value stocks) factors.
Fama and French hypothesized that, while small-cap and value stocks have higher market betas (more equity-type risk), they also contain additional unique risks (they are not free lunches) unrelated to market beta. The Fama-French three-factor model improved the explanatory power from about two-thirds of the differences in returns between diversified portfolios to more than 90%.
The Fama-French model became the workhorse model for financial economists. The fund family Dimensional Fund Advisors (Fama and French led their research efforts) led the way in introducing factor-based funds based on the Fama-French research. Today, while hundreds of factors have been identified in the literature, only a few are generally accepted as adding incremental explanatory power. And while there is some competition as to which is the best model, the most accepted four- and five-factor models include some combination of market beta, size, value, momentum, profitability and investment.
With that background, we’ll now examine a common concern that is often raised about factor-based investing.
Factor-Based Strategies Are Pricier
While the statement is true in a relative sense, factor-based strategies do not have to come with high expense ratios. For example, the expense ratios of the DFA core strategies range from 0.19% to 0.23% for the domestic funds (DFEOX and DFQTX, respectively), and 0.39% for their international core fund (DFWIX).
Vanguard’s U.S. Multifactor Fund Admiral Shares (VFMFX) has an expense ratio of just 0.18%. And today there are many low-cost, factor-based ETFs from which individuals can choose. Factor-based investing needn’t be expensive.
That said, expense ratios should not be the only consideration when choosing a fund, except if choosing between two index funds based on the same index.
To demonstrate this point, we’ll examine the live returns of the factor-based funds with the longest track record, those of Dimensional, and compare their returns with those of the marketlike portfolios of the premier provider of index-based strategies, Vanguard.
We’ll look at data for the longest period that both the factor-based fund of Dimensional and the total market fund of Vanguard have been available. Using live funds allows us to account for fund expenses and trading costs. Data is from Portfolio Visualizer.
In each of the nine cases, the factor-based fund run by Dimensional outperformed the Vanguard total market fund, with the outperformance ranging from 0.6 percentage point to as much as 4.8 percentage points.
Despite the higher fund expenses, both in terms of expense ratios and trading costs (due to higher turnover and trading in less liquid small stocks), the nine Dimensional funds produced an average outperformance of 2.6 percentage points. Even if factor-based investing were to add a small amount of complexity, it’s safe to conclude most investors would find the complexity more than compensated for by the added return as well as the demonstrated diversification benefits.
One other point to consider is that, by increasing exposures to factors that have expected premiums, investors can lower their exposure to market beta because the equities they hold have higher expected returns than the market. That allows them to hold more safe bonds.
You have to consider the total portfolio’s implementation costs and not look at the expense ratios of the funds used in isolation.
Summary
As you have seen, well-designed factor-based strategies, which focus on the factors that have provided evidence of persistence, pervasiveness, robustness to various definitions and survive transactions costs, while also having intuitive explanations for why their premiums should persist, have historically provided higher returns than market-based strategies. In addition, they have provided significant diversification benefits.
Factor-based strategies do not require a great increase in complexity, as we now have many multifactor funds that can be used to develop globally diversified portfolios. And while they tend to be somewhat more expensive, they are not necessarily dramatically higher than those of marketlike portfolios.
By Larry Swedroe
