# Exploring Greenblatt’s Magic Formula

I’ve been exploring the Magic Formula detailed in Joel Greenblatt’s latest book, The Little Book That Beats the Market. I must admit that I am leery of any formula that mechanically selects stocks, however, the concept of having a list of great companies selling at good values piques my interest.

What is this Magic Formula?

The Magic Formula seeks to identify “good” businesses selling at “bargain” prices.  It uses two factors to rank stocks so that you can identify the best businesses selling at bargain prices.

The first factor identifies a good business as one that produces a high return on capital (ROC).  Return on capital is calculated by dividing earnings before interest and taxes (EBIT) by the sum of net working capital and net fixed assets.

ROC = EBIT / (Net Working Capital + Net Fixed assets)

The second factor identifies businesses selling at bargain prices by examining earnings yield, which is basically the in inverse of the price earnings ratio (P/E).  More specifically, earnings yield is defined as earnings before interest and taxes divided by enterprise value.

EY = EBIT/EV

Shai Dardashti has done a great job discussing Joel Greenblatt and The Little Book that Beats the Market, and he has compiled all his work in a recent post to prepare for a meeting with Joel Greenblatt.  In fact, Shai will be publishing his transcript of that meeting shortly.

Looking under the hood

I’ve decided to take a closer look at how the Magic Formula works in the real world.  I just went over to the Magic Formula Investing site and registered for free.  With the login information in hand, I decided to run the Magic Formula screen.

The first step required me to select the minimum market capitalization that I would allow.  I entered 50 for \$50 million market cap minimum, since I heard that is what Joel Greenblatt used in when he developed the formula.  Step two requires you to select the number of top ranked stocks that you wish to choose from.  I selected 25, and then I did step three, which was to hit go.  Here’s the list of stocks that it returned today:

• American Eagle Outfitters Inc (AEOS)
• Anika Therapeutics Inc (ANIK)
• Block H & R Inc (HRB)
• Callwave Inc (CALL)
• Catapult Communications Corp (CATT)
• Collectors Universe Inc (CLCT)
• Deluxe Corp (DLX)
• Forward Industries Inc (FORD)
• Ftd Group Inc (FTD)
• Grubb & Ellis Co (GBEL)
• Infospace Inc (INSP)
• Innovative Soltns & Supp Inc (ISSC)
• Intervideo Inc (IVII)
• Jakks Pacific Inc (JAKK)
• K-Swiss Inc -Cl A (KSWS)
• King Pharmaceuticals Inc (KG)
• Korn/Ferry International (KFY)
• Kos Pharmaceuticals Inc (KOSP)
• Magellan Health Services Inc (MGLN)
• Mannatech Inc (MTEX)
• Marvel Entertainment Inc (MVL)
• New Frontier Media Inc (NOOF)
• United Online Inc (UNTD)
• Vaalco Energy Inc (EGY)
• Vertrue Inc (VTRU)

The first thing I noticed was that this list wasn’t ranked by the two factors, but was just an alphabetical list of the top ranked stocks with market caps great than \$25 million.  There are quite a few familiar names on that list, but there are several new companies on that list that I know nothing about.

I have decided that I’m going to research each of these companies.  But before I do that, I read a comment by Rick on Shai’s blog that got me thinking.  The comment by Rick notes:

“Screening by using a “magic formula” is merely the first step. I wouldn’t get caught up in the “formula” per se. It merely screens for businesses that have the highest ROIC and matches them with a valuation tool, earnings yield. This inherently is what all successful value investors of Buffett discipline would ascribe to. Not just a cheap price for a cigar butt investment! The real magic in my opinion comes from the determination of two things: (1) How sustainable is the competitive advantage, i.e. How long can we sustain these superior ROIC? and (2) When we utilize earnings yield, are we using normalized earnings or are we dealing with overstated or super-normal earnings? In this way, the discipline becomes far less formulaic and becomes more analytic and more of an art.”

I totally agree with Rick.  I think the Magic Formula provides a great starting point to identify investment candidates.  However, I think determining the sustainability of these companies’ competitive advantages is critical.  Right off hand I note a few fashion stocks on the list above that may have a very fleeting competitive advantage that could disappear very quickly if consumer tastes change suddenly.  In addition, accounting shenanigans could mask whether or not these companies are really selling at bargain prices.

Kicking the tires

I’m going to kick the tires of these companies over the next few weeks.  I’ll figure out what they do and how they do it.  After a few kicks, I’ll figure out if the above stocks truly have a durable competitive advantage or whether they are going to potentially run out of gas, break down or require lots of maintenance.

I’m also going to be testing out the Magic Formula independently to see how it performed in the past.  I even have an idea of how to turbo charge this little engine.  This is all going to take some hard work, so expect a lot of activity here at Fat Pitch Financials over the next few weeks regarding the Magic Formula.

### 55 thoughts on “Exploring Greenblatt’s Magic Formula”

• January 25, 2006 at 11:27 am

George,

You might want to check out the Magic Formula Investing Yahoo! discussion board. It may help you to refine your criteria for backtesting. It seems as though others have not been very successful in coming up with the same list of companies on the MFI website.

cheers,
j

• January 25, 2006 at 3:24 pm

I’m prety skeptical about forumals and screens as well. Out of that list, i’ve had small positions in FORD at various times last year.

• January 26, 2006 at 8:52 am

Thank you for the kind mention of my blog, Value Discipline.

The “Magic Formula” is wonderfully sensible and logical; it seems straightforward thinking that the best bargains are companies with the highest profitability that are available at the cheapest price. No real “magic” there.

I will be interested in seeing what sort of refinements you bring to Greenblatt’s approach.

But the real key to using any such formula is understanding why a company exhibits these characteristics, essentially understanding the moat and the sustainability of the competitive advantage.

I can recall a similar screening technique in the late 1970’s and early 80’s that highlighted the Texas regional banks as having great profitability (ROE in this case) and seemingly cheap valuations, despite a very high rate of growth. The high growth and profitability for these banks came from high risk lending to energy and real estate companies in the energy belt. As energy prices collapsed in the deflationary aftermath and “see-through” buildings stood vacant, the returns proved unsustainable, and the competitive advantage disappeared as did most of the banks!

Please understand that I am not disparaging the “Magic Formula.” It is a great first screen to steer your thinking. But the commingling of other mental models will help one understand the value of a franchise. It is the integration of this thinking that helps distinguish a truly great investment from the pedestrian flash in the pan.

You are doing some really terrific work here! I look forward to your ongoing analysis.

• January 26, 2006 at 10:16 pm

While I admire the work ethic behind the notion of doing additional work beyond simply using the Magic Formula, but it strikes me as a little arrogant to presume that by doing additional analytics, an amatuer money manager can improve on the results posted by Greenblatt over the past 20 years (just north of 30% annual returns).

In a perfect world, expanding beyond Greenblatt’s two metrics to measure things like the sustainability of competitive advantage and the wideness of the company’s ‘moat’ would be great, but it’s not a perfect world, and it seems like hubris to me for amateurs to attempt to alter a 30% formula to make it work better.

• January 28, 2006 at 2:51 pm

Barry, Mr. Greenblatt also digs deeper than just using the Magic Formula. I don’t believe that it is a “little arrogant” to do some of my own due diligence on the companies that appear on the Magic Formula list.

I have already noticed a few companies that show up on the list for few days and then mysteriously disappear. This recently happened to CBS and I believe it was due to a data error. I think the financials for the old Viacom were being used for the Magic Formula calculations even though the company split into CBS and Viacom.

• January 28, 2006 at 9:50 pm

Absolutely, checking to ensure the MFI website is spitting out companies that do indeed fit the Magic Formula is time well spent (I too have found some erros), but if you central tenets of Greenblatt’s book, doing additional work to screen out top decile MFI companies is highly unlikely to yield increased returns – as he says, whether you take just a couple or the entire top decile, the results have largely been the same over an extended period of time.

So sure, check the website to make sure it’s accurately capturing the calculations of the MFI, but the arrogance I referenced was the text that indicates Greenblatt’s work is “merely the first step.” That language implies that the author can improve on Greenblatt’s work, which, if you believe, has generated 30+% returns per annum for 20 years. If someone can indeed improve on that, they have a very bright future.

• January 30, 2006 at 1:28 am

IMO, unless there is some glaring error in the something that appears on the results of the magic formula website, I would stick with the results. Once you start analyzing a stock in other ways, then you start to make the same mistakes that plague all (almost) investors–the mistakes that make the average investor get average returns. The point is discipline.

With that in mind, however, Greenblatt forces you to make your own little decisions and use the magic results as just a starting point. This is because he recommends gradually building up the portfoliio every few months by picking 5 or 7 stocks. When the least number of results that his website allows is 25, then you have to start making judgment calls to winnow the 25 down to 5 or 7.
Also related, if you already were fully invested in the stock market, I do not see how spreading the purchases out at a couple points throughout the year would help. So do you think that advice that he gives is for someone who is not fully invested?

• January 30, 2006 at 1:40 am

I too noticed the inclusion of a few fashion retailers in the results and was worried about the fickleness of the whole fashion business. But I guess Greenblatt’s point is that the street’s hesitancy on that fickleness is alreadsy reflected in the high earnings yield. The street may be right in this short term period and it may be wrong, that’s the reason for his 20-30 stock (as opposed to 5-8 stock) diversification.

• January 30, 2006 at 9:09 am

Thanks for an interesting idea. Calculating an earnings ratio based on enterprise value sounds like a more informative ratio than the straight-up p/e ratio.

• February 3, 2006 at 1:30 pm

I have been studying ANIK all day today as it relates to the Magic Formula because it came up on my list on the MFI site as well. I wanted to see if I could use EBIT/Enterprise Value and come up with similar values for earnings yield. My earnings yield was 10%; however, the MFI spit out 15%. I wonder where 5% discrepensy is and why I can’t get my values on other stocks as well to come within a percentage point or two of the MFI site?

I would also like to know/research if there is a value for both Earnings Yield and ROIC that only produces market average returns. I think if I can understand what a typical value is for both of these, I can began to expect which stocks will beat the market, by how much, and which ones will fall short, of course all other things being equal. This may not make any sense, or have any corrolation to the market, but I began to think of this as I was studying ANIK, among others.

bucsgolf14

• February 22, 2006 at 4:01 pm

The book does the calculation for 17 years. Why 17? Why not 25 or 30 or 50? It would seem that longer periods would be a better indicator. Any thoughts?

• February 23, 2006 at 11:13 pm

I’m not sure why 17 years was used, but it might be that the CompuStat data that he used only goes back that far. You might want to look up information regarding the CompuStat database if you want a definitive answer. Sorry I’m short on time now to check for you.

Interestingly, 17 years is also the number that I’ve heard Buffett use to discuss the average length of long cycles such as interest rates.

• February 28, 2006 at 2:00 pm

Greenblatt says in his book that the CompuStat DB is a 17 year snapshot.

• February 28, 2006 at 5:34 pm

Thanks for clarifying that Devin. That was my initial recollection, but I was a bit uncertain since I couldn’t put my finger on exactly where I read that the CompuStat database only went back 17 years.

• March 5, 2006 at 10:08 am

Has anyone independantly demonstrated that the formula described in the book (rank 3,500 tickers by two the factors, sum the ranks, remove the utilities and fianacial companies, list the top 20 of them) DOES create lists matching those on the MFI website?
dave

• March 7, 2006 at 10:50 pm

David –
I am working on independently checking the Magic Formula this week. I hope to post about my work next week.

• March 9, 2006 at 7:05 pm

Well –

I may be stupid or brave or whatever – but here is a link to the real life test of the Magic Formula. \$50,000 – my own money – no joking – just money invested based on the formula.

Results so far ?

Hey – it’s been 2 weeks – but so far just a little ahead of the market…

http://realmagicformulatest.blogspot.com/

• March 11, 2006 at 11:08 pm

Just finished the book and am still waiting for the confirmation e-mail to get access to the site.

So, I was looking around to see, whether I could find screening websites, which would allow the same sort of screen and to validate whatever is going to be on the magicformula site. MSN seems to have taken their great Java-based screener down and every other site I found, including Fidelity and TDWaterhouse didn’t provide the data the screen requires.

Seems like a ‘simple’ formula, when you have to go to Greenblatt’s website. Perhaps, he’s going to charge for it soon? What use is the simple formula, if one can not replicate the screen easily?

Anyone know of an alternate screening site?

• April 20, 2006 at 10:30 am

Although the magic formula is a good startbefore purchasing stocks you should do research to see if the stock will go up. The formula is agood toll to narrow down stocks so you can pick the few you want to use. I will do research on 10 stocks and buy the top 10 i pick which I think should grow. Not all stocks that make the magic formula criterion are going to give you a magically high profit in the future.

• July 24, 2006 at 6:57 pm

I just ran a quick test of the stocks listed in the Jan 24 column. The Magic Formula is down 5.55% from 01/24/06 to 07/24/06. The Russell 2000 is down 6.41% and the S&P500 is down 0.47% during the same time period.

Ticker 1/24/2006 7/24/2006
AEOS 25.39 33.34 31.31%
ANIK 10.5 9.86 -6.10%
HRB 24.9 23 -7.63%
CALL 4.79 3.53 -26.30%
CATT 14.55 9.98 -31.41%
CLCT 15.07 12.38 -17.85%
DLX 28.4 13.57 -52.22%
FORD 10.55 6.05 -42.65%
FTD 10.02 14.86 48.30%
GBEL 11.95 8.6 -28.03%
INSP 23.7 22.02 -7.09%
ISSC 14.01 16 14.20%
IVII 10.99 8.86 -19.38%
JAKK 22.57 17.04 -24.50%
KSWS 31.32 23.55 -24.81%
KG 17.99 17.09 -5.00%
KFY 19.34 18.38 -4.96%
KOSP 45.17 39.27 -13.06%
MGLN 33.85 44.15 30.43%
MTEX 13.84 13.39 -3.25%
MVL 16.5 18.03 9.27%
NOOF 6.49 6.76 4.16%
UNTD 14.48 10.77 -25.62%
EGY 5.77 8.61 49.22%
VTRU 38.22 43.65 14.21%

Average 18.8144 17.7096 -5.55%

S&P 500 1267 1261
-0.47%

Rus 2000 718 672
-6.41%

• July 25, 2006 at 5:58 pm

Very needed information found here, thank you for your work

• August 1, 2006 at 8:56 am

RG made enormous mistake with Ford. It’s not right to make assertions and be so careless.

• August 2, 2006 at 10:15 am

I’ve read a report from a big US broker lately on the same idea. They only implemeted a market neutral long / short strategy. They screened the MSCI Europe index for low EV/EBITDA (personaly i too find these better then P/E) and high ROCE. These stocks they put in the long list, the other way around for the short list.

They backtested this model from 1990 till 2005 and the results were remarkably. We see only 11 years on 16 with a positive result for the long portfolio. On average it showed 6% profit pro year. This far from the results of 30% acclamied possible with this model.

On the other hand the short portfolio showed a negative result in 13 on 16 years , with an avarage of -9%. So much more profitable then the long portfolio. Together with the long portfolio this model showed a positive result in 15 out of 16 years of on average 15% pro year.

My conclusion from this study is that it seems to work out better the other way around as the “worst” list performs 9% and the long list performs only 6% …

• November 16, 2006 at 10:12 am

I have a question about the ROC (return on capital) metric used by Greenblatt. If you use Greenblatt’s site for the top 25 companies with a market cap > \$100M, you’ll get a lot of companies with a ROC > 100% which I cannot understand. Let’s take PALM as an example. You’ll find PALM’s balance sheet there:
http://finance.yahoo.com/q/bs?s=PALM
If you take EBIT = 125M, net working capital = 453M, fixed assets = Property, Plant, Equipment= 83M, your ROC is equal to 23%, nowhere near 100% that Greenblatt seems to find? (I took Balance sheet figures as of 31-May-06 and yearly EBIT for the last 4 quarters as of 31-Aug-06)
Can someone help me and tell me what figures you take for EBIT, net working capital, and fixed assets to find a ROC > 100% ???

Pascal

• December 22, 2006 at 1:05 pm

Hi,

I believe the results of Greenblatts’ MF-screen won’t be that good in the coming years. This because of the (unexpected) rise of commodity prices in the last years. These have led to high ROIC’s and EY’s for these kind of companies, which make them likely candidates in the screening process.

Because of the lack of (durable) competitive advantages, their returns won’t be that good, and will drag down the returns of the whole MF-selection,

Hendrik Oude Nijhuis
http://www.magicformulastocks.com

• January 27, 2007 at 6:06 pm

I have used the Magic Formula for over a year now. In January 2006, without doing any further research, I bought 20 stocks from the Magic Formula \$50mm cap list. The majority of those 20 were in the >100% Return on Capital category; most were in the double digit Earnings Yield category. (Not quite a dart board approach, but almost.)

Results: 11 winners and 9 losers. The 11 had very substantial gains; the 9 losers were absolute dogs. Net profit: greater than 30% return overall, much greater. The biggest scorers were NUE, MVL, UST, HOG. Others like CBS, EGY and HNR were marginally cool.

The performance of my 9 uncany canines (among others: DLX, CECO, KG, VCI, JAKK, BSX) continues to bug me, so I have done additional research on this year’s picks and I have developed losing stop loss and trailing stop loss criteria, rather than just blindly holding for a year. I know that’s heresy from the Joelian MFI doctrines, but paraphrasing Robert Frost, I can’t resist “holding history and heresy in fruitful tension.” One of my other departures was to buy all of the 20 in January, rather than spacing them over months, as Joel suggests. Thank you Joel (and Benjamin Graham, too).
Keenan Davis

• February 19, 2007 at 11:15 pm

Someone on the MFI Yahoo Group that did some research on stop losses found that dropping the big decliners actually lowered the overall return because many bounced back strongly. It seemed to imply that cost averaging down might be a good tactic to use on MFI stocks, at least overall.

• March 14, 2007 at 12:06 am

it just may be possible

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• February 13, 2010 at 1:58 am

Hi,

I am new in the area of investing but am pretty fascinated by the MFI. Can someone give a simple method on how to get the data needed to verify the ranking of the companies oneself – how does one go about getting the ROC and Earnings Yield and doing this ranking? Also, to someone’s earlier question, has someone verified this by running the data him/herself and matched it with the MFI data?

Thanks!

• March 12, 2010 at 4:45 pm

AJ-

Had the book for a while but just got the chance to pick it up a few days ago.

I agree that a safe, minimal check of the MFI spit-outs is a smart idea, and that can be found just checking the ROC: EBIT/(Net Working Capital + Net Fixed Assets) and EBIT/Enterprise Value, which can be found on major financial websites. I am very wary, as an inexperienced, young investor of probing too much further into further screening (remember the suspension of disbelief is probably the most important aspect in maintaining dedication through thick and thin)

And this may be a dumb question in lines with some of the other Greenblatt over-analyzing and “heresy” as previously described, but does the current recession bear any weight in the reliability of the MFI screening? I would think not as it analyzes inherent value, but i also recognize that this book was published before the market crashed.

• March 13, 2012 at 4:40 am

Is there a clear definition for “excess cash” for the magic formula?

I hope you will forgive a bit of self-promotion: we had an interesting, if not entirely conclusive, discusion about this on Investment Q & A.

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