Looking at Factor Investing

The Wall Street Journal has an interesting article on the growth of “factor investing.” I think this is a fascinating area and I’ve been interested in it since before it even had a name.

I never cared much for the traditional Capital Asset Pricing Model. Instead, I’ve been interested in areas where this model fails—and there are many. Value stocks, for example, have a long-proven ability to outperform the broader market. Low volatility is another area. The response from academics has been to assert that the model indeed still works, but we need to adjust things for these “factors” like value and low vol.

I’m afraid they’re stretching things out too far and would be best served by ditching their model. Personally, I don’t care about all about preserving models but I like the idea of keying in on factors that have shown their ability to beat the market. The question is, can we isolate these factors and invest in them reliably?

What the article fails to mention is that the important thing isn’t the factor itself. Instead, it’s the characteristic. Let me explain.

Factor investors try to isolate the particular zig and zag shape of, say, most value stocks. What they want to find is anything that correlates to that line. That’s the factor, but that’s not what’s truly important. Instead, it’s the value characteristic that’s important. Even value stocks that don’t correlate with the value factor have shown themselves to be superior performers.

Last month, Eric Falkenstein wrote:

Daniel and Titman documented that it was the characteristic, rather than the factor, that generated the value and size effects. They did an ingenious study in that they took all the small stocks, and then separated them into those stocks that were correlated with the statistical size factor Fama and French constructed, and those that weren’t. That is, of all the small stocks, some were merely small, and weren’t correlated with the size factor of Fama-French, and the same is true for some high book-to-market stocks.

Remember, in risk it is only the covariance of a stock to some factor that counts. Daniel and Titman found that the pure characteristic of being small, or having a high book-to-market ratio, was sufficient to generate the return anomaly, independent of their loading on the factor proxy. In the APT or SDF, the covariance in the return with something is what makes it risky. In practice, it is the mere characteristic that generates the return lift.

(…)

The standard equity groupings of size, value/growth, and now volatility, are best done directly, and not via an exposure to factor-mimicking portfolios.

This is pretty damaging to the standard model because it claims that you can only beat the market by paying for it with more risk. That risk can only be found by correlating with the factor. But it’s not the factor that’s beating the market, it’s the characteristic.

This is a reason why, despite my interest in factor investing, I think investors are wise to steer clear of these products. There’s no magic formula out there besides “focus on good stocks and wait.”

Posted by on December 27th, 2011 at 1:02 pm


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