An important evolution within smart beta has been the approach of blending several factors together, rather than targeting a single factor. As characteristics differ across factors, these multi-factor smart beta strategies can offer the potential for diversification benefits and may help improve consistency in performance.
As multi-factor strategies have grown in popularity, so too have our multi-factor SPDR® ETFs. Our SPDR® MSCI USA StrategicFactorsSM ETF (QUS) has been of particular interest, attracting $444 million in flows in 2019. The fund tracks the MSCI USA Factor Mix A-Series Index, which blends low volatility, quality, and value exposures together in a single strategy.
To learn more about the index provider behind QUS and how they construct their multi-factor indices, I spoke with Mark Carver, MSCI’s Global Head of Factor Index Products. This two-part blog series will share excerpts from our conversation.
Matthew: It seems there are a lot of different names used to refer to factors, like smart beta, advanced beta, or strategic beta. How would you describe factor investing at its core?
Mark: It’s true there are a lot of labels. I think they should simply be called factors. And this isn’t a new term—factors are not new, and factor-based ETFs are not new. A factor is simply a characteristic that helps the investor understand risk and return. And factor investing is the translation of that characteristic to a portfolio. Factor investing captures the characteristics that distinguish returns.
When we’re referring to “characteristics,” it’s important to recognize that while portfolios can have many characteristics, not all of them distinguish returns. For example, let’s take the quality characteristic. Do high quality and low quality stocks deliver different returns? If the answer is yes, which we believe, then it’s a factor. And while not all characteristics distinguish returns, we’ve identified a group that do—and built indexes around them.
Matthew: What is the core group?
Mark: We think value, quality, momentum, volatility, size, and yield have historically been rewarded factors. That doesn’t mean you can’t look at something like growth, for example, and build a portfolio of growth stocks that will do well in certain market environments. But the factors mentioned have broad academic evidence and support.
Matthew: For the MSCI USA Factor Mix A-Series Index, why did you choose to blend value, quality, and minimum volatility in particular?
Mark: What’s interesting about that mix is each is well-documented as showing reward and diversification over time. Value for example is often cited as a risk factor, while quality and minimum volatility are behavioral anomalies, meaning the factors capture a mispricing due to investor behavior.
In addition, value and quality have historically shown negative correlation, in this case of the active returns, so the combination of these particular factors is designed to provide diversification to the index. And the addition of minimum volatility aims to give the index a defensive posture. The desired result is an index with diversified exposure to well known factors.
Matthew: There are many ways to construct a factor index. Different index providers take different approaches—some top-down, some bottom-up. Is there a right way?
Mark: The right way and the right decision depend on the investor’s objectives. With a top-down approach such as the MSCI Factor Mix Indexes, the composition is equally weighted exposure to MSCI Quality, Value-weighted and Minimum Volatility indexes. Clients like the simplicity and transparency of the approach, the targeted high capacity and relatively low tracking error, along with the diversification across high quality, cheap valuation and low volatility stocks.
Something often cited by clients about the top-down approaches is that performance attribution is straight forward, as investors can easily calculate how much each factor contributes to the total return. However, the index’s gain in diversification and high capacity may be at the expense of the factor exposure, resulting in some factor dilution.
With bottom-up it’s different—this approach involves selecting stocks that meet criteria from multiple factors’ perspectives. This results in a completely different index that would have higher factor exposure, higher stock concentration and tracking error but lower capacity. Interestingly, investors have responded well to top-down approaches, partly because of lower tracking error to traditional market exposures.
Matthew: What is MSCI’s model for selecting index constituents?
Mark: The index provider’s approach to factor definition and construction does matter. We generally favor using multiple descriptors—like Return on Equity (ROE), earnings variability and financial leverage for quality —to capture factors. We find that the descriptors are not perfectly correlated which means you pick up additional information by using multiple descriptors. A simpler model with a single descriptor may result in unintended exposures and/or sector bias.
The next blog in this Q&A series will explore multi-factor strategy implementation and their role within a portfolio.