In part 1 of this article, we explained there are two primary approach when it comes to combining factors: isolated and integrated. Now, let’s look at how the isolated approach and integrated approach have flared.
Isolate or Integrate?
The closest approximation of an apples-to-apples comparison we can arrive at for assessing the relative merit of each approach centers around the benchmark of the iShares Edge MSCI Multifactor USA (LRGF, listed in the U.S.). LRGF tracks the MSCI USA Diversified Multiple-Factor Index, or DMF. The index targets stocks based on their exposure to the value, size, quality, and momentum factors. The index integrates factor signals to select and assign weightings to its holdings. Although LRGF launched in April 2015, MSCI publishes historical values for the index dating back to December 1998. We also have historical values for each of the four single-factor indexes that proxy the factors targeted by the multifactor index. Thus, we can construct a hypothetical portfolio that equal-weights the single-factor indexes and matches DMF’s rebalancing dates (end of May and November) as a proxy for a version of DMF that employs an isolated approach to combining factors.
While this is a cleaner comparison than a side-by-side of LRGF and the Goldman Sachs ActiveBeta U.S. Large Cap Equity ETF (GSLC, listed in the U.S.), there are a few caveats. Most importantly, DMF uses an optimizer to construct its integrated portfolio, while our proxy portfolio does not. The optimizer aims to maximize the index’s factor tilts while matching the risk level of its parent index: the MSCI USA Index. Also, the optimizer layers on constraints. For example, it limits DMF’s turnover and individual stock and sector tilts relative to its parent index. It also limits the index’s exposure to nontargeted factors. Additionally, it is important to note that DMF measures three of the four factors it seeks to exploit in the same manner as the associated single-factor indexes that form our proxy portfolio. However, DMF and the MSCI USA Momentum Index measure momentum slightly differently. Specifically, the momentum index risk-adjusts stocks’ momentum scores while DMF does not. With those caveats covered, let’s look at the results.
Exhibit 1 shows performance statistics for the DMF (integrated approach), our isolated version of the index, and the parent index (MSCI USA Index). Neither approach clearly separates itself based on risk-adjusted returns. The integrated approach provided modestly higher returns each year, but also had greater risk than the isolated approach. The integrated approach’s Sharpe ratio was modestly higher than that of the hypothetical portfolio employing the isolated approach. But the isolated approach offered a better trade-off between active risk and return, as evidenced by its higher information ratio. The integrated approach offers higher returns but with greater risk. So neither approach is clearly superior.
.png)
Let’s now expand this analysis to the largest multifactor ETFs offering exposure to U.S. large caps. Using data from the French Data Library and AQR, I measured each ETF’s factor loadings. Because each fund has a limited live track record, take these results with a grain of salt. I also include each fund’s tracking error against the Russell 1000 Index since the earliest common inception date among the funds (December 2015). Exhibit 2 displays the results.
.png)
Over their (very) short lives, the multifactor ETFs employing an integrated approach to combining factors have experienced greater tracking error versus the Russell 1000 Index than those that use an isolated approach. John Hancock Multifactor Large Cap ETF (JHML, listed in the U.S.) is a notable exception. JHML likely has lower tracking error relative to its peers because it includes more securities in its portfolio. Tracking error can be viewed as a proxy for these funds’ potential to out- or underperform an appropriate benchmark. Given these funds’ short live performance, it’s difficult to assess their factor loadings. But a cursory review shows that integrated approaches typically demonstrate higher factor loadings and tracking error. The notable exception here is GSLC, which has shown significant loadings on the profitability and momentum factors over its short life.
Clearly, there is a lot to consider when selecting a multifactor fund. Deciding which factor combination approach—isolated or integrated—works best depends on what you want to accomplish. Consider an isolated portfolio approach if you favor transparency and lower tracking error, but know that you’re forgoing more pronounced factor tilts. For potentially stronger factor tilts and higher tracking error, consider a fund that uses an integrated approach. But remember that an integrated approach is usually more complex and opaque.
