To Combine Factors or To Combine Portfolios? That Is the Question for the Smart Beta Investor…

The launch of the STOXX factor indices has enabled us to do more research into a variety of factor-related topics. One issue that has vexed us recently is whether a smart-beta investor seeking broad and diversified exposure to a number of style factors is better off combining a series of individual-factor indices, or using a single index that targets an alpha that comprises the same factors. To be sure, this is not a new area of research[1], and academically oriented researchers do not agree that one method is better than the other.

That said, based on a quick (and much less rigorous) evaluation of the STOXX single-factor indices, we conclude that for the investor seeking higher factor exposures the evidence leans toward the single index that targets a multi-factor alpha (“Multifactor”), although the differences have weakened in the past few years. In addition, if the investor’s goal is to minimize the magnitude of a drawdown, combining portfolios (“Combination”) may be a better course of action, since the investor is free to over-weight those single factor indices with lower betas. And, of course, if an investor wants to bet on one or two particular factors or themes instead of a broad combination, the single factor indices would be ideal choices.

To create our combination index, we equally weighted each of the five single factor indices: Value, Momentum, Quality, Low Risk and Size[2] (as a typical investor might do). Each single factor index maximizes its exposure to the appropriate factor. We then compared the exposures and returns of that combination to those of the STOXX Multifactor index, which uses an alpha formed as an average of each of the single factor alphas[3]. To keep things simple, we used the set of indices built from the STOXX Global 1800 index, although we expect the results would be similar if we used the ones from other regions.

Portfolio Exposures

First, we looked at the holdings of the combination index and compared them with those of the Multifactor index as of 31 December 2019. The active holdings are clearly correlated, although not perfectly, and a few stocks with 0% active weight in the Multifactor portfolio have substantial active weights in the combination. The Multifactor portfolio also holds a few stocks with much higher active weights than the combination (Figure 1).

It was also interesting to note how different the exposures are in the combination index, as compared with the Multifactor. The process of combining indices may effectively cancel out some exposures, whereas the Multifactor specifically targets all the exposures we see in Figure 4. Therefore, at least at this particular point in time, the Multifactor portfolio has higher exposures to Earnings Yield, Medium-Term Momentum and Profitability, and more negative exposures (as we want to see) in Leverage and Market Sensitivity. The differences in Size and Value are smaller, and the combination has a higher positive (undesired) exposure to Volatility. From this perspective, and assuming these differences in exposure would appear at other points in time, we would clearly favor the Multifactor portfolio.

Figure 1. Active Holding Correlations and Factor Exposures, 31 December 2019

Source: Qontigo

Performance

Over the full course of history, the Multifactor index produced about twice the active return of the Combination portfolio (Figure 2). However, the table shows the breakdown of active returns year-by-year, with the higher annual return highlighted in green and the lower return in pink. The table illustrates that the outperformance is not a foregone conclusion and, in fact, the combination beat the Multifactor in seven of the 16 years since the inception of the indices, including in each of the last four[4]. The magnitude of the average excess return in the years that the Multifactor index beat the combination was more than twice that in the years when the opposite happened, which accounts for the overall large difference.

The magnitude of 12-month rolling active-return drawdowns might also favor the combination, depending on the investor’s goals. There have been four periods of drawdown since 2004, and the drawdowns were not simultaneous (Figure 3). Although that does not tell us anything about the relative attractiveness, we also observe that the Multifactor index usually saw drawdowns that were larger in magnitude than the combination. An investor whose goal is to avoid drawdowns may find this tilts the argument in favor of the combination.

Figure 2. Cumulative and Year-by-Year Active Returns

Figure 3. Rolling 12-month Drawdowns

Source: Qontigo

Conclusion

Although we have not presented the evidence, we believe it is likely to be more expensive to trade and hold multiple single-factor portfolios, especially in a setting where a higher investment means lower fees. Multifactor portfolios, in contrast, offer better overall exposures and a higher chance of better performance, potentially offset by higher drawdowns.

This does not mean that single-factor indices are not desirable investments. In most cases they offer attractive risk premia, diversification benefits and the ability to time factors. However, for a broad, diversified exposure to a number of well-documented remunerative style factors in a portfolio that will be held as a core investment, we lean toward the Multifactor approach.


 

[1] See, for example, “Fundamentals of Efficient Factor Investing” by Clarke, de Silva and Thorley, Financial Analysts Journal November/December 2016, “Can the Whole Be More Than the Sum of the Parts? Bottom-Up versus Top-Down Multifactor Portfolio Construction” by Bender and Wang, Journal of Portfolio Management Special Issue 2016, “Long-Only Style Investing: Don’t Just Mix, Integrate:, by Fitzgibbons, Friedman, Pomorski and Serban, AQR June 2016, “Constructing Long-Only Multi-Factor Strategies: Portfolio Blending versus Signal Blending”, by Ghayur, Heaney and Platt, Financial Analysts Journal, July 2018, and “Alpha Construction in a Consistent Investment Process”, by Sivaramakrishnan, Stubbs and Ceria, Axioma, among others. (And thanks to Kartik Sivaramakrishnan for this bibliography.)

[2] The Size portfolio favors stocks with lower market capitalizations over their larger-cap counterparts.

[3] See our recent paper “STOXX Factor Indices: Targeted Factor Exposures With Managed Liquidity and Risk Profiles” for more detail.

[4] Given the bull market of the past few years, the lower exposure to Market Sensitivity mentioned earlier is likely a major reason the Multifactor index lagged the combination index.

Melissa R. Brown, CFA

As Managing Director of Applied Research, Melissa Brown generates unique insights into risk trends by consolidating and analyzing the vast amount of data on market and portfolio risk maintained by Axioma. Brown’s perspectives help both clients and prospects to better understand and adapt to the constantly changing risk environment.