Given such a poor track record, is anyone still using the CAPM?Lot’s of people, apparently… Welch (2008) finds that ~75% of professors recommend the use of the model when estimating the cost of capital, and Graham and Harvey (2001) find that ~74% of CFOs use the CAPM in their work. A few quotes from Graham and Harvey 2001 sum up common sentiment regarding the CAPM:
Of course, there are lots of arguments to consider before throwing out the CAPM. Here are a few:
“While the CAPM is popular, we show later that it is not clear that the model is applied properly in practice. Of course, even if it is applied properly, it is not clear that the CAPM is a very good model [see Fama and French (1992)].”…practitioners might not apply the CAPM or NPV rule correctly. It is also interesting that CFOs pay very little attentionto risk factors based on momentum and book-to-market-value.”
- Everyone learns about it and knows how to use it (although, Graham and Harvey suggest that many practitioners don’t even apply the CAPM theory correctly)
- Data is easy to obtain on betas.
- Roll’s critique–maybe the CAPM isn’t a junk theory, rather, the empirical tests showing the CAPM doesn’t work are bogus.
The Fama French 3-Factor Alternative?Given the CAPM doesn’t work that well in practice, perhaps we should look into the Fama French model (which isn’t perfect or cutting edge, but a solid workhorse nonetheless). And while the FF model inputs are highly controversial, one thing is clear: the FF 3-factor model does a great job explaining the variability of returns. For example, according to Fama French 1993, the 3-factor model explains over 90% of the variability in returns, whereas the CAPM can only explain ~70%! The 3-factor model is great, but how the heck does one estimate the FF factors? Dartmouth Professor Ken French comes in for the rescue! Prof. Ken French houses one of the richest data resources on the web–I like to call it “MSCI Barra for broke people.” Here’s the link Prof. French provides all the data you’ll ever need. (update: we have our own factor data library as well)
The Fama and French 3-factor ModelFirst, here are the links to the 3-factor model source documents if you enjoy reading archaic academic finance journals: Fama French 1992 and Fama French 1993. I also recommend reading the CAPM chapter from Ivo Welch’s finance book to “freshen up” on your quantitative factor model knowledge (admit it, upon graduation from your MBA program you threw all that knowledge out the window!) In words, the Fama French model claims that all market returns can roughly be explained by three factors: 1) exposure to the broad market (mkt-rf), 2) exposure to value stocks (HML), and 3) exposure to small stocks (SMB). For a full recap of exactly how the factors are created, here is a link. A video on how this works (and spreadsheet):
How to use the Fama and French 3-factor modelI went ahead and built a simple spreadsheet model so blog readers can calculate some alphas and betas associated with the 3-factor model and get some ‘hands-on’ experience. A link to a spreadsheet and more details is here. I have posted data from French’s website into the excel document. Returns are from 1950–2010. The user can enter in data for their favorite index/mutual fund into column “I” and see how the returns stack up against the CAPM and the FF model. For fun, I went ahead and plugged in the equal-weight CRSP universe (consists of all NYSE/AMEX/NASDAQ stocks–imagine Wilshire 5000). And here are the results: According to the CAPM, the EW CRSP index has alpha of roughly 2.5%/year. However, when the FF model is used, the alpha drops to a mere 25bp a year, or essentially zero. This brief analysis of the equal-weight CRSP index is a prime example of why the FF model is better than the CAPM–the FF model can actually tell you what is driving the returns (you’ll notice the .84 SMB estimate associated with the EW CRSP index). And knowing what drives returns is important: We’ve all heard the tales of magical performance from the 1.5% and 20% “mini-Warren-Buffett-crowd” who run small value funds and continuously pound the table that they “beat the market.” Before FF, an allocator might look at these small-cap managers and think, “Wow, this manager has some secret sauce at their disposal and deserves a 1.5% management fee and 20% performance allocation.” Now, an allocator can use the FF model and quickly determine that the manager has little “alpha,” and can switch their allocation into a vanguard small-cap index fund that charges 25bp. If you’re curious, go ahead and drag and drop returns of your favorite ‘active manager’ into the spreadsheet. In many cases, the CAPM will show that they have alpha, but when you examine their returns using the FF model you will quickly see that they don’t have “alpha,” merely an ability to invest in small caps and/or value stocks. Luckily, gaining exposure to small caps and/or value stocks is very cheap these days.
“Alpha” versus genuine “Value-add”There is a great controversy over whether or not small stocks and value stocks are actually ‘riskier’ than other stocks in the universe. The arguments fall on two sides of the fence:
- size and value represent “risk,” and therefore SHOULD earn higher average excess returns.
- size and value represent “alpha,” and therefore provide investors with an opportunity to earn outsized risk-adjusted returns.