concluded that each share was therefore entitled to $1.20 in earnings ($1,200,000 divided by1,000,000 shares). At Jason’s asking price of $12 for eachshare, that meant that based on last year’s earnings,Jason’s Gum Shops would have given us a 10 percentreturn for each $12 share purchased ($1.20 divided by$12 = 10 percent).
[40]
J O E L G R E E N B LAT T
That 10 percent return, calculated by dividing theearnings per share for the year by the share price, isknown as the earnings yield. We then compared the earnings yield of 10 percent we could receive from an investment in Jason’s business with the 6 percent return wecould earn risk free from investing in a 10-year U.S. government bond. We concluded, without too much trouble,that earning 10 percent per year on our investment wasbetter than earning 6 percent. Of course, although thatanalysis was simple, we identified a bunch of problems.First, Jason’s Gum Shops earned that $1.20 per sharelast year. Next year’s earnings might turn out to be a completely different story. If Jason’s business earned less than$1.20 next year, we wouldn’t earn a 10 percent return onour investment and maybe we would be better off with asure 6 percent from the government bond. Second, evenif Jason’s business did earn the $1.20 per share next year,or even more, that’s only one year. How do we know, orhow would we ever know, how much Jason’s Gum Shopswould earn in future years? It could be a lot more than$1.20 per share, but it could be a lot less, and our earnings yield could drop significantly below the 6 percent wecould have earned risk free from the U.S. government.Lastly, even if we had an opinion about future earnings,how could we ever have any confidence that our predictions would turn out to be right?
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[41]
In short, all of our problems seem to boil down tothis: It’s hard to predict the future. If we can’t predict thefuture earnings of a business, then it’s hard to place avalue on that business. If we can’t value a business, theneven if Mr. Market goes crazy sometimes and offers usunbelievable bargain prices, we won’t recognize them. Butrather than focusing on all the things that we don’t know,let’s go over a couple of the things that we do know.As we discussed, Jason’s Gum Shops earned $1.20 pershare last year. At a price of $12 per share, our earningsyield was therefore $1.20 divided by $12, or 10 percent—easy enough. But what if Jason’s Gum Shops earned $2.40per share last year? What if we could still buy a share for$12? What would the earnings yield be then? Well, $2.40divided by $12 equals 20 percent. Therefore, if Jason’sGum Shops had earned $2.40 per share last year, at a priceof $12 per share, the earnings yield would be 20 percent.If Jason’s Gum Shops had earned $3.60 per share lastyear, at a price of $12 per share, the earnings yield wouldbe 30 percent! But it gets easier.Now follow closely because there are only two mainpoints in this chapter and here comes the question thatwill determine whether you understand the first. Allthings being equal, if you could buy a share of Jason’sGum Shops for $12, which of those earnings resultswould you prefer? Would you prefer that Jason’s Gum
[42]
J O E L G R E E N B LAT T
Shops had earned $1.20 per share last year, $2.40 pershare last year, or $3.60 per share last year? In otherwords, would you prefer that the earnings yield calculatedusing last year’s earnings was 10 percent, 20 percent, or30 percent? Drumroll, please. If you answered that 30percent is obviously better than 20 percent and 10 percent, you would be correct! And that’s the point—youwould rather have a higher earnings yield than a lowerone; you would rather the business earn more relative tothe price you are paying than less! Wax on!Now that wasn’t so hard, but here comes the secondpoint of the chapter, which focuses on something a bit different from the first (otherwise, I would be saying thesame thing twice, which would be wasting your time,which is something I would never do unless I put it inparentheses). The first point related to price—how muchwe receive in earnings relative to our purchase price. Inother words, is the purchase price a bargain or not? Butbeyond price, we might also want to know somethingabout the nature of the business itself. In short, are webuying a good business or a bad business?Of course, there are plenty of ways we could definewhat makes a business either good or bad. Among otherthings, we could look at the quality of its products orservices, the loyalty of its customers, the value of itsbrands, the efficiency of its operations, the talent of its
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[43]
management, the strength of its competitors, or the longterm prospects of its business. Obviously, any of these criteria, either alone or in combination, would be helpful inevaluating whether we were purchasing a good or a badbusiness. All of these assessments would also involve making guesses, estimates, and/or predictions. As we alreadyagreed, that’s a pretty hard thing to do.So once again it might make sense to first examinesome things that we already know. In fact, let’s not makeany predictions at all. Instead, let’s just look at what happened last year. For instance, what if we found out that itcost Jason $400,000 to build each of his gum stores(including inventory, store displays, etc.) and that each ofthose stores earned him $200,000 last year. That wouldmean, at least based on last year’s results, that a typicalstore in the Jason’s Gum Shops chain earns $200,000each year from an initial investment of only $400,000.This works out to a 50 percent yearly return ($200,000divided by $400,000) on the initial cost of opening a gumstore. This result is often referred to as a 50 percentreturn on capital. Without knowing much else, earning$200,000 each year from a store that costs $400,000 tobuild sounds like a pretty good business. But here comesthe hard part (not really).What if Jason had a friend, Jimbo, who also owned achain of stores? What if you had a chance to buy a piece
[44]
J O E L G R E E N B LAT T
of Jimbo’s store chain, Just Broccoli? What if it also costJimbo $400,000 to open a new store? But what if each ofthose stores earned only $10,000 last year? Earning$10,000 a year from a store that costs you $400,000 tobuild works out to a one-year return of only 2.5 percent,or a 2.5 percent return on capital. So here’s the toughquestion: Which business sounds better? Jason’s GumShops, a business where each store earned $200,000 lastyear and cost $400,000 to build, or Just Broccoli, a business where each store earned $10,000 last year but alsocost $400,000 to build? In other words, which soundsbetter—a business that earns a 50 percent return on capital or one that earns a 2.5 percent return on capital? Ofcourse, the answer is obvious—and that’s the secondpoint! You would rather own a business that earns a highreturn on capital than one that earns a low return on capital! Wax off (or paint the fence or sand something orwhatever)!*But here comes the big finish. Remember how I toldyou this chapter was going to be hard to believe? That byusing just two simple tools you could actually become a“stock market master”? Well, believe it. You are a stockmarket master.*To find out what Jimbo should do, check out the box at the end of thechapter!
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[45]
How? Well, as you’ll see next chapter, it turns outthat if you just stick to buying good companies (ones that havea high return on capital) and to buying those companies only atbargain prices (at prices that give you a high earnings yield),you can end up systematically buying many of the good companies that crazy Mr. Market has decided to literally give away.You can achieve investment returns that beat the pants offeven the best investment professionals (including thesmartest professional I know). You can beat the returns oftop-notch professors and outperform every academicstudy ever done. In fact, you can more than double theannual returns of the stock market averages!But there’s more. You can do it all by yourself. Youcan do it with low risk. You can do it without making anypredictions. You can do it by following a simple formulathat uses only the two basic concepts you just learned inthis chapter. You can do it for the rest of your life—andyou can choose to do it only after you are convinced thatit really works.Hard to believe? Well, it’s my job to prove it. Your jobis to take the time to read and understand that the only reason this simple method actually works is that it makes perfect sense! But first, as always, here comes the summary:1. Paying a bargain price when you purchase a share ina business is a good thing. One way to do this is to
[46]
J O E L G R E E N B LAT T
purchase a business that earns more relative to theprice you are paying rather than less. In otherwords, a higher earnings yield is better than a lowerone.2. Buying a share of a good business is better thanbuying a share of a bad business. One way to dothis is to purchase a business that can invest its ownmoney at high rates of return rather than purchasing a business that can only invest at lower ones. Inother words, businesses that earn a high return oncapital are better than businesses that earn a lowreturn on capital.3. Combining points 1 and 2, buying good businessesat bargain prices is the secret to making lots ofmoney.And most important,4. Don’t give money to guys named Jimbo.
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[47]
In fact, unless Jimbo expects those Just Broccolistores to earn a lot more in the coming years (a presumption that would obviously involve making predictions about the future), it seems pretty clear thatJimbo’s business is so bad he shouldn’t even be building Just Broccoli stores. If he has a choice of buildinga new store for $400,000 that will earn him just 2.5percent each year on his investment or buying a U.S.government bond that will earn him 6 percent on hisinvestment—risk free—what’s the point of even building a store in the first place? By opening Just Broccoli stores, Jimbo is actually throwing money away!(Even though it looks like he is earning 2.5 percenton his investment in a new store, in reality he isthrowing away the added 3.5 percent he could earn bysimply buying a risk-free U.S. government bond!)
Chapter Six
SO WE’RE READY FOR the magic formula! Of course, you’restill probably thinking it won’t work or it’ll be too hard orthere’s something wrong with a book that even claims tohave a magic formula. But if it makes you feel any better,even the great Benjamin Graham, one of the mostrespected and influential pioneers in the investment field,the man who introduced us to the concepts of Mr. Market and margin of safety, wrote about and used a magicformula of his own. Okay, so he didn’t really call it that(apparently, the man had some dignity). But Graham feltthat most individual investors, and even many professionalinvestors, would have a hard time making the type of predictions and performing the level of analysis necessary to
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[49]
value and invest in businesses on their own. Graham figured that by sharing a simple formula, one that madesense and had worked well in the past, individual investorswould be able to achieve excellent investment results witha high degree of safety.Graham’s formula involved purchasing companieswhose stock prices were so low that the purchase pricewas actually lower than the proceeds that would be received from simply shutting down the business and sellingoff the company’s assets in a fire sale (he called thesestocks by various names: bargain issues, net-current-assetstocks, or stocks selling below their net liquidation value).Graham stated that it seems “ridiculously simple to say”that if one could buy a group of 20 or 30 companies thatwere cheap enough to meet the strict requirements of hisformula, without doing any further analysis, the “resultsshould be quite satisfactory.” In fact, Graham used this formula with much success for over 30 years.Unfortunately, the formula was designed during aperiod when many stocks were priced cheaply. For severaldecades after the stock market crash of 1929 and theGreat Depression that followed, investing in stocks wasconsidered to be an extremely risky business. Investors,for the most part, were therefore unwilling to place a highvalue on stocks for fear of losing their money again.Although Graham’s formula has continued to work over
[50]
J O E L G R E E N B LAT T
the years, especially during periods when stock prices areparticularly depressed, in today’s markets there are usually few, if any, stocks that meet the strict requirements ofGraham’s original formula.But that’s okay. By using his formula successfully forso many years, Graham showed that a simple system forfinding obviously cheap stocks could lead to safe and consistently good investment returns. If Mr. Market was willing to sell him a group of stocks at prices so low that theymet his formula’s strict requirements, Graham figuredthat on average he would end up owning a basket of bargains. Sure, the low prices of some of the stocks would bejustified. Some companies deserve low prices becausetheir future prospects are poor. But on average, Graham figured that the purchases made by using his formula would be bargains—bargains created by Mr. Market practically giving awaybusinesses at unreasonably low prices. Graham suggested thatby buying a group of these bargain stocks, investors couldsafely earn a high return without worrying about a fewbad purchases and without doing complicated analysis ofindividual stocks.Of course, that leaves us with an obvious challenge.Can we come up with a new formula, one that can beat themarket averages with low risk? Can we find one that notonly works in today’s market but one that is flexibleenough to work far into the future—regardless of the
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[51]
overall level of the market? Well, as you might haveguessed, we can. In fact, you already know what it is!Last chapter we learned that, all things being equal, ifwe have the choice of buying a stock with a high earningsyield (one that earns a lot relative to the price we are paying) or buying one with a low earnings yield (one thatearns very little relative to the price we are paying), wemight as well choose the one with the high earnings yield.We also learned that, all things being equal, if the choiceis between buying shares in a company that earns a highreturn on capital (a company whose stores or factoriesearn a lot relative to the cost to build them) and buyingshares in a company that earns a low return on capital (acompany whose stores or factories earn very little relativeto the cost to build them, like Just Broccoli), we might aswell choose the one with the high return on capital!So here it comes. What do you think would happen ifwe simply decided to buy shares in companies that hadboth a high earnings yield and a high return on capital? Inother words, what would happen if we decided to only buyshares in good businesses (ones with high returns on capital) butonly when they were available at bargain prices (priced to give usa high earnings yield)? What would happen? Well, I’ll tellyou what would happen: We would make a lot of money! (Oras Graham might put it, “The profits would be quite satisfactory!”)
[52]
J O E L G R E E N B LAT T
But does it make sense that something this simple andobvious would actually work in the real world? Well, toanswer that question, a logical first step might be to goback and see how a disciplined strategy of buying goodbusinesses at bargain prices would have worked in the past.As it turns out, following a simple, commonsense investment strategy actually would have worked pretty well.Over the last 17 years, owning a portfolio of approximately 30 stocks that had the best combination of a highreturn on capital and a high earnings yield would havereturned approximately 30.8 percent per year. Investing atthat rate for 17 years, $11,000 would have turned into wellover $1 million.* Of course, for some people, that mightnot seem like such a great return. On the other hand,those people are basically nuts!During those same 17 years, the overall market averaged a return of about 12.3 percent per year. At that rate,$11,000 would still have turned into an impressive $79,000.While that’s certainly a lot, $1 million is more! And youcould have made that $1 million while taking much less risk*The special database used for our magic formula study (Compustat’s“Point in Time” database) contains data going back a total of 17 years. Itcontains the exact information known by Compustat customers at the timeof each stock purchase. At a rate of 30.8 percent per year for 17 years,$11,000 would grow over 96× to $1,056,000 before taxes and transactioncosts.
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[53]
than investing in the overall market. But we’ll talk moreabout that later.For now, let’s see just how the magic formula was puttogether. In that way, we can begin to understand why sucha simple formula works and why it should continue to workfar into the future. Later, we’ll learn, in step-by-step fashion,how to apply the magic formula to find winning investmentstoday. But keep in mind, the mechanics aren’t the importantpart; the computer will be doing most of the work. As youread in Chapter 1, it will be your belief in the overwhelminglogic of the magic formula that will make the formula workfor you in the long run. So let’s try to understand how themagic formula chooses good companies at bargain prices.The formula starts with a list of the largest 3,500companies available for trading on one of the major U.S.stock exchanges.* It then assigns a rank to those companies, from 1 to 3,500, based on their return on capital.The company whose business had the highest return oncapital would be assigned a rank of 1, and the companywith the lowest return on capital (probably a companyactually losing money) would receive a rank of 3,500.Similarly, the company that had the 232nd best return oncapital would be assigned a rank of 232.*Details of this test are provided in the Appendix section (certain financialstocks and utilities are excluded from our stock universe).
[54]
J O E L G R E E N B LAT T
Next, the formula follows the same procedure, butthis time, the ranking is done using earnings yield. Thecompany with the highest earnings yield is assigned a rankof 1, and the company with the lowest earnings yieldreceives a rank of 3,500. Likewise, the company with the153rd highest earnings yield out of our list of 3,500 companies would be assigned a rank of 153.Finally, the formula just combines the rankings. Theformula isn’t looking for the company that ranks best onreturn on capital or the one with the highest earningsyield. Rather, the formula looks for the companies that have thebest combination of those two factors. So, a company thatranked 232nd best in return on capital and 153rd highestin earnings yield would receive a combined ranking of 385(232 + 153). A company that ranked 1st in return on capital but only 1,150th best in earnings yield would receivea combined ranking of 1,151 (1,150 + 1).*If you’re not a numbers person, don’t worry. Justkeep in mind that the companies that receive the bestcombined rankings are the ones that have the best combination of both factors. In this system, the company thathad the 232nd best return on capital could outrank thecompany that ranked 1st in return on capital. Why?Because we could purchase the company that had the*The better combined ranking is, therefore, 385.
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[55]
232nd best return on capital (an excellent ranking out of3,500) for a price low enough to give us a very high earnings yield (153rd cheapest out of 3,500 based on earningsyield). Getting excellent rankings in both categories(though not the top-ranked in either) would be betterunder this ranking system than being the top-ranked inone category with only a pretty good ranking in the other.Pretty simple, right? But it can’t be this easy! Can aportfolio of 30 or so of the highest-ranked stocks reallyget such great investment results? Well, consider this.Take a look at the returns that would have been achievedover the last 17 years if we had simply followed the recommendations of the magic formula (see Table 6.1).Oops! This can’t be. The results are just too good!Surely, something must be wrong here. We’ll really haveto examine these results very closely. But let’s say we leavethat for the next chapter. For now, we can review the shortsummary and spend some more time enjoying the resultsfrom using the magic formula. They appear to be quite satisfactory.
Quick Summary
1. Ben Graham had a “magic formula.” Graham figured that purchases that could meet the strict
[56]
J O E L G R E E N B LAT T
TABLE 6.1 Magic Formula ResultsMagic Formula
Market Average*
S&P 500
1988
27.1%
24.8%
16.6%
1989
44.6
18.0
31.7
1990
1.7
(16.1)
(3.1)
1991
70.6
45.6
30.5
1992
32.4
11.4
7.6
1993
17.2
15.9
10.1
1994
22.0
(4.5)
1.3
1995
34.0
29.1
37.6
1996
17.3
14.9
23.0
1997
40.4
16.8
33.4
1998
25.5
(2.0)
28.6
1999
53.0
36.1
21.0
2000
7.9
(16.8)
(9.1)
2001
69.6
11.5
(11.9)
2002
(4.0)
(24.2)
(22.1)
2003
79.9
68.8
28.7
2004
19.3
17.8
10.9
30.8%
12.3%
12.4%
*Note: The “market average” return is an equally weighted index of our3,500-stock universe. Each stock in the index contributes equally to thereturn. The S&P 500 index is a market-weighted index of 500 large stocks.Larger stocks (those with the highest market capitalizations) are countedmore heavily than smaller stocks.
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[57]
requirements of his formula were likely to be, onaverage, bargains—bargains created by Mr. Market’s practically giving away businesses at unreasonably low prices.2. Today, few companies meet the strict requirementsoutlined by Graham.3. We have designed a new magic formula—a formulathat seeks to find good companies at bargain prices.4. The new formula appears to work. In fact, it appears to work too well.5. Before piling every penny we have into the magicformula, we should probably examine the resultsmore closely.
Chapter Seven
“IT AIN’T THE THINGS WE DON’T KNOW that get us in trouble,”said Artemus Ward, a nineteenth-century newspaper columnist. “It’s the things we know that ain’t so.” And that, ina nutshell, is our problem. The magic formula looks like itworks. In fact, the results are so good there can hardly beany argument. And of course, we want it to work. Whowouldn’t want to make lots of money without trying all thathard? But does the magic formula really work? Sure, all thenumbers look good, but do we know where they came from(or who they’ve been with, for that matter)? More important, do we know where they’re going? Even if the formulaworked in the past, are we merely learning how to “fight thelast war”? Will the formula continue to work in the future?
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[59]
Good questions, certainly. Before what we learned from lastchapter gets us into too much trouble, let’s see if we canfind some good answers.First up, where did all those numbers come from?There’s often a problem when looking back and makingassumptions about what could have been accomplished inthe past. While a computer stock-picking formula mayappear to have generated spectacular theoretical returns,duplicating those results in the real world may be quitedifficult. For instance, the magic formula may be pickingcompanies that are so small that few people can really buythem. Often, small companies have very few shares available for purchase, and even a small amount of demand forthose shares can push share prices higher. If that’s thecase, the formula may look great on paper, but in the realworld, the fantastic results can’t be replicated. That’s whyit’s important that the companies chosen by the magic formula be pretty large.Last chapter, the magic formula ranked 3,500 of thelargest companies available for trading on the major U.S.stock exchanges. The formula then chose its favoritestocks from that group. Even the very smallest of those3,500 companies still had a market value (the number ofshares times the stock price) of over $50 million.* With*See Appendix section for details.
[60]
J O E L G R E E N B LAT T
companies of that size, individual investors should be ableto buy a reasonable number of shares without pushingprices higher.But let’s see what happens when we raise the bar a little bit. It would certainly be nice if the magic formulaworked for companies whether they were large or small.That way we could be more confident that the basic principle of buying good companies at bargain prices worksfor companies of any size. So instead of choosing from thelargest 3,500 companies, let’s look at just the largest2,500 companies. The smallest companies in this grouphave a market value of at least $200 million.Over the last 17 years (ending in December 2004),the magic formula worked remarkably well for this groupof larger companies, too. Owning a portfolio of 30 stockschosen by the magic formula would have achieved anannual return of 23.7 percent. During the same period,the market’s average return for this group was 12.4 percent per year. In other words, the magic formula practically doubled the market’s average annual return.But what if we take it one step further? Let’s look backand see what happened when we narrowed the group tojust the largest 1,000 stocks—only the companies withmarket values over $1 billion. Even large institutionalinvestors like mutual funds and large pension funds canbuy these stocks. Well, take a look at this! (See Table 7.1.)
T H E L I T T L E B O O K T H AT B E ATS T H E M A R K E T
[61]
TABLE 7.1 Magic Formula Results (Largest 1000 Stocks)Magic Formula
Market Average*
S&P 500
1988
29.4%
19.6%
16.6%
1989
30.0
27.6
31.7
1990
(6.0)
(7.1)
(3.1)
1991
51.5
34.4
30.5
1992
16.4
10.3
7.6
1993
0.5
14.4
10.1
1994
15.3
0.5
1.3
1995
55.9
31.4
37.6
1996
37.4
16.2
23.0
1997
41.0
19.6
33.4
1998
32.6
9.9
28.6
1999
14.4
35.1
21.0
2000
12.8
(14.5)
(9.1)
2001
38.2
(9.2)
(11.9)
2002
(25.3)
(22.7)
(22.1)
2003
50.5
41.4
28.7
2004
27.6
17.3
10.9
22.9%
11.7%
12.4%
*Note: The “market average” return is an equally weighted average of our1,000-stock universe. The S&P 500 index is a market-weighted index of 500large stocks.
[62]
J O E L G R E E N B LAT T
Once again, it appears that even the largest investorscan practically double the market’s compounded annualreturn simply by following the magic formula! But thiscan’t be. There must be a catch. It just looks too darneasy! And of course, there may still be some problems.It’s just that the problem of a magic formula that worksonly on paper but not in the real world isn’t one of them.Okay. So, the companies chosen by the magic formulaaren’t too small for investors to buy. But how about this?Maybe the magic formula just got lucky with a few goodstock picks and that’s why the whole average looks sogood? If the magic formula doesn’t stay lucky, relying onpast results could be very dangerous. Fortunately, it’s veryunlikely that luck was much of a factor at all.Throughout the 17 years of our study, we held a portfolio of roughly 30 stocks. Each stock selection was heldfor a period of one year.* In all, over 1,500 different stockpicks were made for each of the tests (largest 3,500stock