February 8, 2016
by Marc Gerstein
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Eugene Fama and Kenneth French deserve enormous respect for the work they did in legitimizing an equity investors’ consideration of risk factors beyond the stock market itself and in identifying those factors. But to use factors as effectively as we can, we’ll have to use a framework that meets our client-centered concerns, which are not necessarily the same as those of academicians.
From CAPM to Fama-French
Factor analysis starts with the capital asset pricing model (CAPM), which describes return in terms of (i) the component associated with a risk-free investment and (ii) the component associated with the equity market. The initial three-factor model presented by Fama-French retained the market factor and added two more: size and valuation. Eventually, they brought the number of factors to five by adding profitability and conservatism (or investment); momentum was later recognized as an additional factor.
[drizzle]All variations conform to the following framework:
R = a + (b1*F1) + (b2*F2) +. . . + (bN * FN)+ e
R = return
a = constant (a risk-free factor)
F = factor (a risky factor)
B = a loading associated with each factor F
e = the residual error – that which the model missed
But however many factors we use, and however simply or elaborately each factor is defined, we’re ultimately seeking to describe the overall market. We want changes in the right side of the equation to describe changes on the left and achieve a correlation as close as possible to 1.00, and we want the error term to be as close to zero as possible.
An explosive – but obsolete – controversy
For practitioners, as opposed to academicians, if liquidity is a concern (as would be the case if one were managing many billions of dollars), it would be unrealistic to deviate much if at all from the market. You buy everything in proportion because you pretty much have to. But a client, or even the sum total of all clients in most practices, is not so big as to force the manager’s hand in this regard. Hence, advisors have the ability to build portfolios that reflect goals other than tracking the market.
I know, I know, I know… active investing is crazy. Countless trees have given their lives to publication and dissemination of study after study showing such endeavors to be pointless (with surviving tress grateful for digitization).
Get ready for a bombshell: I don’t care.
We’re in a different world. We no longer sit in brokerage offices and watch ticker tapes. We no longer wait patiently for the monthly S&P guide to arrive in the mail so we can look up basic information on companies. We no longer get inky fingers and tired eyes thumbing through the Wall Street Journal looking up stock prices. We no longer sit on hold waiting for brokers to get back on the phone to confirm that our trades are “done.” And we no longer trudge our way to the SEC or a library lugging suitcases full of coins to copy 10-Ks and 10-Qs, nor do we beg companies to send them faster than by third-class mail.
We know things now – quickly and cheaply. For the even moderately computer literate, we know them easily.
That has opened up a new way of doing things. Any one of us can quickly and easily complete studies that once took academicians many months and countless graduate-student person-hours to accomplish. We can use fresher data in our studies (Did you really believe once-per year is the ideal rebalancing period, or might it be that annual data was all the non-paying professors could squeeze from the data vendors?) Screening and ranking are available to anybody with a will to work this way.
The old binary world that pitted passive buy-the-market investors against active-inspired-by-my-personal-genius investors is dead. The research that shows passive investing being better than active has lost its usefulness. The question is top-down index investing versus bottom-up-rules-based strategies. Eventually, researchers will study and come up with insight into this new topic.
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