Most value investors are on the perpetual mission of trying to find stocks trading at 50% off fair price (P), in order to make a few when the market eventually realizes its mistake, and the actual price bounces from P/2 back to P.
If you sign up for the CFA Program, or any college finance class, wanting to learn how exactly one comes up with the fair price (a.k.a. intrinsic value) of a stock, pretty quickly they’ll give you an answer:
P = fair price, E = forward earnings, r = required rate of return, and g = annual growth rate
The problem, as Professor Bruce Greenwald likes to point out, is how incredibly sensitive this model is to the inputs, which you have to guess at. Say you’re trying to value the stock of a company trading at $25, with an expected forward EPS of $1. You’re guessing their cost of capital might be 9-10%, and future growth maybe 6-7%. So you start playing around with the formula:
E = $1, r = 9%, g = 7% -> 1 / (.09 – .07) = Fair Value = $50
E = $1, r = 10%, g = 7% -> 1 / (.10 – .07) = Fair Value = $33
E = $1, r = 10%, g = 6% -> 1 / (.10 – .06) = Fair Value = $25
Is it fairly priced at $25, or half off?! Who knows! While the valuation model may be mathematically correct, it’s too dangerous to actually use. We’re making 1% changes to the inputs and seeing huge swings in intrinsic value.
I don’t ever remember seeing a good “fix” for this in the CFA Program, apart from maybe a suggestion to use a few other valuation models too, and average all their results to try to remove the noise.
But of course, Master Greenwald does indeed have a fix. I’ve never seen it presented by anyone else. He claims that “though they never talk about it”, the approach was pioneered by Warren Buffett and Glenn Greenberg – who evidently had similar stellar investment performance until recently (supposedly Greenberg had some missteps during the financial crisis).
When I learned of this methodology, it was as if the sun had finally come out after a long winter. The person I consult for is predominantly interested in stocks of great businesses (franchises) to put clients into. The best I could do was concentrate my research on the quality businesses with the lowest multiples (essentially setting g to 0). It felt sloppy.
This is the answer to that conundrum. Over the next few posts, I will share my understanding of it with you.