@SD – Thanks for the note. You’ve stolen part of my next post in which we look at data sets over and above those used in the original paper. But to answer your question about being an advisor: I’m honestly just trying to do what’s right for investors as an advisor, but this blog is not really aimed at clients/potential clients. It’s largely for pleasure and learning (on my part!) Also, I do have a question about your last paragraph as well – do you have the ability to provide the data for what Michael James is looking for? I too would be most interested in seeing that.

I didn’t understand your comments about the greater cost of borrowing. Do you mean “c < 1%” and “c < 2%”? Are you saying that you have an idea how these values would fare compared to pure CAPM after doing the calculations?

Preet, you are doing an excellent job in explaining this information – why are you wasting your time as an advisor? I can’t imagine the average investor will ever grasp this and have the conviction to stick it out.

For the other commenter, I cannot tell if you agree or disagree with F/F’s research and conclusions based on your comments, but if you just supply your spreadsheet with an artificially larger Rf you could account for a greater cost of borrowing and a simultaneous decrease in the market factor, and you will get the answer of ‘it still works brilliantly’ for c < about 1, and ‘it still works really well’ for c < 2.

The idea of trying to find a vowel factor would be pure data mining and if you found it in one set of data you wouldn’t find it in any others.

A interesting test would be to add the following term to CAPM: u(high v – low v), where v is the number of vowels in the company’s name. If this improves the coefficient of determination significantly after doing the regression to find the best constant u, then we might think twice about being impressed by Fama-French.

I’d be interested in seeing what the effect is on CAPM’s coefficient of determination if we replace (Rm-Rf) with (Rm-Rf-c), where c represents a constant gap above the T-bill rate to take into account the fact that we can’t borrow at the T-bill rate. The regression would give the optimal value for c, and we could tell from the resulting coefficients of determination whether this is a significantly better model.