Factor Spotlight
Factor University

Factor Returns Overview

As discussed in prior blog posts, factor exposures are an important lens through which to understand portfolios. The returns of factors are also an important metric for understanding what is going on in the stock market.

There are thousands of ways to define factors, but most factors fall into specific generalized groups. Some factors separate stocks based on apparent risk factors. Other factors are based on the idea that investors overreact or underreact to price movements or announcements. Then there are the growth and value factors, an area which fundamental investors are particularly likely to overlap with factor investors. By looking at the performance of a few selected factors in each group we can better understand some of the recent trends driving performance in the stock market.

The table below explains how each selected factor is calculated and why it might work. Each factor also has a polarity, which lets us know how the factor’s metric is expected to influence returns. For instance, a P/E ratio would have a low-high polarity, as value stocks have historically outperformed growth stocks on average. But when we look at the factor as E/P, the polarity then becomes high-Low as the stocks with the high earnings yield are the value stocks.

Looking at the historical returns of each factor gives us some context as to which factors have been popular in the market recently. We calculate the factor returns on an equal weighted sample of the 2000 largest stocks trading on US exchanges. Sometimes factor measurements need to exclude financial stocks, as their tendency to carry high levels of debt makes them look overly risky on metrics that utilize debt and extra cheap on metrics that look at earnings.

Breaking this data down into a table makes it a little bit easier to analyze.

Note: 2016 Q3 factors are actually calculated through 9/27/2016.  Source: OmegaPoint Calculations.  Asterisk indicates a low-high polarity.
  • Some factors have underperformed drastically in recent periods. 12M beta does particularly badly when technology stocks are outperforming. In the 12M volatilityand ROE factors we see a very classic pattern of a factor getting more popular and returns subsequently decreasing.
  • Other factors like Momentum are more volatile, and others like Estimate Dispersion simply haven’t been working in the 2000 largest US stocks over the past couple years.
  • Overall, 2016 does not look like it has been a fun year for traditional factor investors. But even in tough years there are factors like Size, Reversal and Dividend Yieldthat have worked out well for investors.
  • Avoiding the popular factors and getting into trades as investors crowd into what is currently working is one way to interpret this data. Another is to note that good stocks with factor exposures that haven’t been doing too well might now be bargains.

Going forward, we’ll update you on the performance of these factors and occasionally do a deeper dive into what has been behind the return of specific factors.


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