Factor investing series

Factor mix and pure alpha

| 7 June 2017

Satrix factor series: “Practical applications of factor investing”

Part 1/10: Understanding your existing portfolio’s mix of factors and pure alpha

Client level of adoption/allocation:

Not allocation, but evaluating

Factor investing has the ability to empower consultants, multi-managers and advisors to build client portfolios simply and efficiently.

From 1) the transparent manner in which factor portfolios are systematically constructed, to 2) the capability of building tailored investment outcomes with greater diversification and predictability, to 3) the low fees, to 4) the reliability in consistently delivering a specific investment philosophy. Factor investing is beginning to revolutionise the investment industry.

While the potential impact of factor investing is transforming in nature, the level of adoption by clients varies by degree of simplicity, from ‘not allocating’ to ‘sophisticated allocation’. In this series we aim to highlight all applications of factor investing across this continuum.

This article is the first in the series of articles by Jason Swartz, Head of Portfolio Solutions at Satrix, aimed at discussing practical ways to employ the power of factor investing.

This first application represents the initial point of departure for factor investing, and creates a foundation for further and potentially more in-depth applications.

Interestingly, this application does not explicitly employ factor investing; instead, it utilises a mathematical framework to assist in understanding an active portfolio’s mix of factor exposures, as well as pure alpha.

The reason this exercise is meaningful and important, is that many traditional active managers deliver a significant percentage of their active returns via static exposures to factors (see figure 1). This phenomenon has less to do with the fact that factor strategies are implemented in a passive way, but more to do with factor strategies having the same ideology as active managers with respect to exploiting market inefficiencies and aiming to outperform the market.

Figure 2

With factors constructed to have characteristics which historically explain excess returns, active managers typically embed these characteristics in their investment process through well-known strategies such as Value, Momentum, Quality, Size and Low Volatility [See Figure 1]. A useful exercise, and the subject of this article’s application, is to understand which combination of these factors is needed to best replicate an active manager’s return through time [See Figure 2] .

This analysis provides valuable insight into whether the active manager incurs style drift though changing exposure (intentionally or inadvertently) to the underlying factors. In our example we see active manager’s apparent drift toward Momentum during 2008 and Quality during 2011; an outcome that would be revealing to the client or asset owner with respect to whether the active manager is being consistently ‘true to label’ versus their claimed investment style.

A constructive variant of this application is performance benchmarking. Given the framework discussed above, one could decompose the expected return of a portfolio into 1) the return to a relevant benchmark, 2) the active return from the portfolio’s exposure to a mix of factors, and 3) the pure alpha, i.e. the active return above and beyond static exposures to factors. By making this distinction when attributing performance, the client is able to properly ascribe the value the active manager is adding relative to their fees charged – and since pure alpha is rare and more expensive, it is important to understand that the active manager is adding return beyond factor exposures.

For more information on this topic please feel free to contact us directly. In our next part in the series, we discuss the concept of ‘portfolio completion’, which is the next logical progression to employ factor investing whereby a client is able to address unintended factor tilts.

Watch this video for a practical application of factor investing by head of portfolio solutions at Satrix, Jason Swartz.

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Our factor portfolios are created in Barra Portfolio Manager using the GEMLT risk model. Specifically: Momentum is a combination of the Barra price momentum factor and consensus earnings revisions, Value is a combination of the Barra book to price factor, the Barra earnings to price factor and the Barra dividend yield factor, Quality is a combination of the Barra profitability factor, -1 times the Barra leverage factor and -1 times the Barra earnings variability factor, Low Volatility is a combination of -1 times the Barra beta factor and -1 times the Barra residual volatility factor. Factor portfolios are constructed using the top 33% of stocks in the universe based on the above factor scores, and the portfolio is equally weighted to avoid any portfolio construction influences. Factor portfolios are rebalanced monthly.

We use a 3-year rolling window to estimate the optimal combination of factor exposures to explain the portfolio’s return variation.