Joel Greenblatt, the author of "The Little Book that Beats the Market", is a value investor extraordinaire and a professor at Columbia's business school. In the book, Greenblatt discusses and justifies the "Magic Formula", a stock selection method that allows individual investors to beat the market using value investing.
Greenblatt starts the book with a discussion about buying a hypothetical business. Basically, the value of a business is the cash it is going to generate over its lifetime, with money that arrives in the future not quite being worth money in the present (since money in the present can be lent to the government for a "risk-free" return and therefore would be worth even more in the future). The concept of how much to pay for a business is briefly discussed. If a business is presumed to be worth $1500, then it makes no sense to pay $1500 for that business since you already have $1500 in hand!
In Chapter 2, Greenblatt discusses at the importance of saving and, at a high level, the various places individuals can store their cash. He discusses the various benefits and drawbacks to storing money in mattresses, banks, as loans to businesses and as stock in businesses.
In the third chapter, the reader is taken through an example income statement. The income of the company is then compared to the offering price for the company, and concepts like earnings yield are discussed. Greenblatt asserts that since the business has risk, the earnings yield should be higher than the risk-free rate (i.e. what the government would pay for your money). But of course, the income statement only looks at past data, but what's important is what the yield will be next year and beyond.
Greenblatt assures readers that discussion of the magic formula is coming up, but that these concepts had to be discussed first for the novice.
Chapter 4: Fluctuating values
Every year, Greenblatt starts his first lecture to his graduate class at Columbia Business School in the same way. He asks students to yell out companies, and he subsequently looks up the 52-week lows and highs of these companies' stocks. For every company, he finds large differences between the highs and the lows. For example, in the year that preceded his publication of the book, the following companies could be purchased at the following prices:
General Electric (NYSE:GE): $29 to $53
General Motors (OTC:MTLQQ): $30 to $68
Abercrombie & Fitch (NYSE:ANF): $15 to $33
IBM (NYSE:IBM): $55 to $93
These stocks were not chosen because of their wild price swings. Instead, their price swings are typical of many companies on the stock market. In such a short period of time, how can it be that such large, well-recognized, widely owned companies fluctuate in value so dramatically? Did GM all of a sudden make half/twice as many cars as it did a few months ago? Unlikely.
There are entire fields devoted to figuring out why and how these fluctuations take place. Greenblatt argues that much academic effort has been expended trying to explain "why something that clearly makes no sense, actually makes sense."
Greenblatt doesn't care why it happens. The point is that it does, and that's what allows you to profit. He goes on to discuss Mr. Market, and how you should buy from Mr. Market when he is offering you bargains, and sell to Mr. Market when he offers you a good price.
Chapters 5 and 6: Earnings yield and ROC
In these chapters, Greenblatt introduces two concepts which form the foundation of the Magic Formula: Earnings yield, and return on capital.
Earnings yield is simply earnings divided by price. If a company was for sale at a certain price, a buyer would hope its earnings are high (relative to the price), not low. As such, a high earnings yield (or conversely, a low P/E) is desirable.
Return on capital is the money that a company receives from investing its own money. A company that can generate a higher return on capital is more desirable than a company that generates a low return on capital. A company that generates a return on capital less than the risk free rate is actually destroying capital.
By owning businesses that trade at high earnings yields and that have high returns on capital, investors will beat the market. To demonstrate this, Greenblatt examined the results of owning approximately 30 stocks with the best combination of earnings yield and return on capital over the last 17 years (since that's how far back the Compustat "Point in Time" database went back). The portfolio returned 30.8% per year, compared to 12.3% for the overall market.
How were these portfolios constructed? All stocks in the market were ranked by the two criteria described above. The rankings were then added together. The top 30 combined-ranking stocks were considered the portfolio for the purposes of this study.
Chapter 7: For Magic Formula skeptics
In this chapter, Greenblatt speaks to the skeptic who doesn't believe the formula described in the last chapter. To that end, Greenblatt identifies possible pitfalls of using the formula, and attempts to disprove them.
First, he uses the past data to ascertain whether these results could indeed have been realized. For example, if the formula only showed great results because the simulation model used prices of small, illiquid stocks, then it may not be very useful. But Greenblatt ran the formula against markets of all sizes, and found that it beats the markets handily even among large caps.
Second, Greenblatt discusses whether the formula could have been lucky. After all, one could use historical data to come up with several winning strategies, but that doesn't mean they will work going forward, as they could be the result of coincidence. Considering the size of the sample Greenblatt employed (number of stocks over number of years), he does not believe the formula to work as a result of luck.
Finally, another possibility is that the market could wise up going forward, and no longer offer the top 30 stocks (as ranked by the formula) at such a large discount. If those 30 are no longer available, is the formula useless? To counter this theory, Greenblatt divided the stock universe (in his study) into deciles. He found that the deciles outperformed each other exactly as expected. In other words, the 4th ranked decile outperformed the 5th ranked decile, the 5th ranked decile outperformed the 6th ranked decile etc. This suggests the formula works on the general market, and does not require a special group of 30 mispriced securities (which is considered the 1st decile).