Isolating the value factor through different metrics can be a diversifier.
A couple weeks ago, I took a look at some of the recent research on the value premium in large-cap stocks. A commenter on my post raised some issues that I thought were worth addressing separately and in-depth.
The first issue relates to a question posed by the commenter. He asks: “Do we have robust evidence that different (or more) fundamental sorts increase exposure to value?” He also provides the following answer: “The best way to ‘check’ this is to start with an out-of-sample measurement period (1940-1962, per James Davis) and sort large cap stocks (‘fundamental indexes’) on the following variables with HmL loads:
Book Value = 0.25
Cash Flow = 0.21
Dividends = 0.11
Sales = 0.15
Low P/B = 0.43
So over this period, P/B had the greatest exposure to value and the most important determinate of value load wasn’t a particular valuation sort at all, but instead using a ‘low price’ (see Low P/B) sort as opposed to just a (any) fundamental weighting scheme.”
The numbers presented did indeed show that P/B ratios had the highest loading on value (or HmL: high minus low). However, that’s exactly what we should expect since the various values presented are specifically HmL loadings. In other words, the figures are just saying that P/B is most like P/B, which is a tautology.
The statement that "P/B had the greatest exposure to value" is thus not quite correct. It has the greatest exposure to value as measured by book value, but so what? It’s just another tautology. Again, the loading on value will depend on how you measure value.
Let’s see what professors Eugene Fama and Ken French and Dimensional Fund Advisors (DFA) have to say on this issue: