One of the great things about travel is that it usually offers me free time to catch up on some reading. On my recent trips to Orange County and Berlin (not in the same weekend), I’ve managed to knock a few more off my reading list. As a result, I’m going to try another book review here on the blog for good measure. Let me know what you think.
The Little Book That Beats The Market by Joel Greenblatt
Overall Rating: Definitely worth the quick read. While the schtick got tiring after a while, the author is clearly intelligent and educated, and the content well thought out. Surprisingly, I found the most interesting part of the book not the “magic formula” itself, but the implicit structure the author put in place to try and help the average investor be successful with the strategy over the long term.
Synoposis: This book is an extremely quick read. Joel Greenblatt is the founder and managing partner of Gotham Capital and currently teaches at Columbia Business School, so he’s definitely educated in both theoretical and practical aspects of finance. This book is written in extremely simple and plain language, and he clearly goes out of his way to make it folksy and fun. I think I finished it in under an hour, appendix included.
Greenblatt’s points are pretty simple:
- The idea that the market is truly efficient is something that only makes sense in theory. In practice, you can definitely beat the market.
- The key to beating the market is to buy above-average companies at below-average prices. Rinse, wash, repeat.
- The “magic formula” is an updated method, similar in concept to those outlined by Benjamin Graham (one of my must-read investing books). The formula is as follows:
- Every year, begin with a list of the 3500 largest companies that are publicly traded
- Rank them 1-3500 based on their return on invested capital (ROIC). This tells you how good a business they are, as defined by taking invested money and turning it into more money.
- Rank them a second time based on their earnings yield, basically the percent of their stock price you get back every year in their earnings. This tells you roughly how expensive they are per-dollar of earnings
- Add the scores from the two lists together, and then invest in the top 20-30 companies based on the combined score. Voila, a list of “above average” companies at “below average” prices.
- This formula will not outperform the market every year. You have to stick to this formula for at least three years if you want a high probability of beating the market average.
Greenblatt has done his homework, using a detailed 17-year history of stock prices to ensure that this formula, based on information actually available at the time, would have outperformed the market handily. In fact, he goes to some trouble to explain some other variants of the formula. The one I outlined above returned an average of 30.8% per year. That’s compared to a 12.4% return for the S&P 500 over the same period, and a 12.3% return for an even investment in all 3500 companies.
I’m guessing that part got your attention.
When I began investing in the mid-1990s, there was a lot of excitement about the Dogs of the Dow strategy. It basically said, take the Dow 30 stocks, rank them by dividend yield, and buy the 10 cheapest every year. The Motley Fool took this one step further, and published their own variant called the Foolish Four, based on a similar concept, with some more gaming around the picks. I actually bought two of those books – I still have them on my shelf, and I actually invested an IRA according to the Foolish Four for 5 years. (It beat the market during that period, by the way).
If you think about it, all these strategies say: “buy great companies at cheap prices”. Now, I think Greenblatt’s formula is much more compelling: ROIC is a much better measure of a “great company” than being in the Dow 30. And earnings yield is more compelling to me than dividend yield, since a lot of great growth companies don’t pay out dividends proportionally to slow-growth companies.
However, I stopped investing according to the Foolish Four in 2001 largely because of an insight into a common flaw with all of these strategies – data mining. It turns out that statistically, if you data mine enough for a “winning formula”, odds are that you’ll find some. I won’t go into the details here, but it is possible using advanced statistics to estimate the likelihood of finding a “winning formula” through data mining. So, even when you find one, you have to evaluate it’s results against the fundamental odds that if you look at any pattern of data, there will be “winning” patterns to a certain degree.
In the case of the Foolish Four, to their credit, the Motley Fool published this analysis, and stopped recommending this approach in late 2000.
So, what makes this magic formula different?
First, Greenblatt is clearly more deeply educated about finance than the Motley Fool, thank goodness. In his appendix, he runs through six or seven of the common flaws with strategies like these, and explains why this approach is still valid.
One of the most compelling pieces of additional analysis he provides is the fact that this formula seems to actually generate linearly predictive results. In other words, if you take the top 10% of companies ranked by this formula, then the next 10%, then the next, each decile of companies outperforms the groups below it.
That type of consistency is rare for most quantitative approaches to ranking stocks, and is a good sign that this formula may be useful.
In fact, Greenblatt runs through almost all of the critiques I would expect in his appendix. The only one he doesn’t address, which to me is extremely important, is the time period bias. Greenblatt has only tested this approach over 17 years of data. That means he basically just looked at 1988+. Given that he includes the longest bull market in history, and then a period of outperformance by value over growth, my guess is that there is significant bias in these results.
Still, my guess is that this formula will still generate outperformance over time. The best thing about this book is that Greenblatt spends a lot of time explaining that in any one year, this formula can and will underperform the market from time to time. In fact, he advocates a minimum of a three-year window to evaluate its performance.
I think this is great advice, but likely doesn’t even go far enough. The stock market, in general, is a long term investment. Investors consistently buy high and sell low, not because they are stupid, but because in the short term, we rationalize investing in the winners (which are bid up because they are popular), and we rationalize selling the losers (which are low because they are not popular).
Buying high and selling low is a very bad investment strategy.
I’m going to check out Greenblatt’s website, and investigate the analysis for this approach further. In the meantime, I do recommend this book to people who like value investing, or who are thinking about investing in individual stocks.