The Little Book That Beats The Market: Book Review

There’s been a lot of buzz about The Little Book That Beats the Market, so I was excited when it finally came in from the library. Of course, at the time I was midway through Index Funds: The 12-Step Program for Active Investors, which I’ll also be posting a review about shortly. Alternating between the two books was like a roller coaster – the Little Book fanning the (little) stock-picking flame inside me, and Index Fund book trying just as hard to stamp it out forever.

The Little Book is well, really little. It’s about the size of a 5″x7″ photograph and barely over 100 pages long. It could be easily finished in one afternoon. The writing style is simple and easy to read, although many of the jokes felt a bit forced to me.

It starts with a nice little story which explains what you are actually buying when you purchase a stock. In short, you’re not buying a physical object, but a stream of future earnings. This is why stock prices fluctuate so much – you’re trying to predict the often-hazy future.

Accordingly, Greenblatt argues that the Market is simply crazy over the short term. But due to this craziness, there is the opportunity to snap up a company at a bargain price. Enter the Magic Formula: Buy good companies at bargain prices. Doing some number-crunching, using the formula gives you historical annual returns of about 30%, beating the market by 20% every year. All with lower risk than the market. Yowza! Sounds good right?

The tricky thing about this book is how ‘good’ and ‘bargain’ are defined. Greenblatt uses a vague definition in the main part of the book, and then a more complicated definition in the appendix. Thanks to JLP at AllFinancialMatters, I discovered this Barron’s article which confirms that even other quantitative people can’t understand the exact definition of the Magic Formula or replicate his awesome returns. They used a different stock database, leading to the returns going down significantly. That’s a bit fishy.

But… even if you use his dumbed-down (my name, not his) definitions of:

Good = High Return On Assets (ROA), and
Bargain = Low P/E ratio,

both of which are part of most stock screeners, you still get market-beating results.

Any time a book claims to beat the market, people line up to crap all over it. I mean, isn’t this just good ole’ Value investing? Traditionally this is done with other ratios like Book-to-Market ratios. Again, the data seems to support that the Little Book method does better than other ratios.

Another criticism, which is noted in the book, is if everyone knows this secret, won’t the prices adjust and remove this market inefficiency? Greenblatt counters this with the fact that his method only works for the long-run, and will underperform the market for sometimes years at a time. This volatility will scare away enough investors and/or fund managers over the long haul such that the premium will endure. Okay, maybe.

My personal nitpick is that the returns also don’t take into account trading commissions and bid-ask spreads. Greenblatt glosses over this point by implying “This method kicks so much ass (remember, 30%!) that you could pay full-service broker commissions and you’d still come out ahead!”

But let’s take a closer look. He suggests holding 30 stocks, each for only a year. Unless you’re investing huge sums, that’s a big drag. If you buy in $500 chunks ($15,000 total portfolio size) with $10 trades, that’s a 4% dent in profits every year (buy and sell). Even at $5 trades, that’s 2%. Finally, if you’re not holding these in an 401k/IRA, you’ll have to deal with taxes.

1) His returns were based on data from 1988 to 2004, which may be the best he could get will full data, but still is less than 20 years. Will it persist?
2) The book has a website,, which you can generate the current picks per the Little Book method.

So, if you add in the database inconsistencies, smaller future market inefficiencies, the existing value-premium, the trading costs, and taxes, will you still end up with a risk-adjusted market-beating return for the next 20 years? I have no clue. I can only say that I’m not changing any of my current investments, but if I do eventually set up a small stock-picking portion of my portfolio, I’ll keep the results of this book in mind.

Although I don’t really recommend it as an investing guidebook like The Four Pillars of Investing, I did find it a fun book to read. I think it presents a new-ish view on picking stocks and was a refreshing change of pace for me.

Overall Rating: 3 Stars (ratings explained)


  1. If anyone wants to see how this works (or doesn’t) in practice, you can follow along with my monthly “little book portfolio” updates each month. I started the portfolio in June and have so far bought H&R Block, Motorola, Microsoft, ASEI and PWEI. I’m invested US$5000 each month in a stock picked out from the current little book websites list of candidates, and I intend to hold each stock for 18 month (mainly to cut down a bit on the trading costs highlighted above).

    Doing my trades from Oz, I’m paying a hefty US$65 per trade – so on a $5000 lot this works out as 2.6% round trip expense.

    My total “little book” portfolio when fully invested in 18 stocks will be approx. US90,000 – which is around 8% of my total investment portfolio, or around 15% of my stock portfolio.

  2. I read this book a few months ago and really wasn’t impressed. I felt like he spent most of his time with the “fuzzy story” and not enough time talking about the actual market strategy. It could have been written in 5 pages. With that said, I think the rest of your comments are right on. The transaction costs of this method make it difficult to follow for small investors.

  3. I added some more info to the review that I forgot to include:

    1) His returns were based on data from 1988 to 2004, which may be the best he could get will full data, but still is less than 20 years. Will it persist?
    2) The book has a website,, which you can generate the current picks per the Little Book method.

  4. My personal belief is that if something has a high P/E that it “may” not be the best time to purchase the stock as I do believe in RTM (return to mean) theory, but we don’t know when it will return. It’s kind of like purchasing the S&P500 in 1999 or purchasing it in 2006, having a low P/E is a better time to buy. I wouldn’t just compare high and low bargin/market to price stocks.

    If any fund manager could pick up this book and beat the market, wouldn’t 9 out of 10 managed funds beat the market. But as we are aware it’s the opposite, 9 out of 10 funds cannot beat the market. What’s more important is the asset class you are investing in.

  5. Hi, just wanted to say that I find the review and the rating realy objective.

  6. Great write up. I too thought the book was a little “simplified”, and there is much more to his theory than meets the eye.

  7. The simplicity is the book’s beauty. I am a wall street analyst and you’d be amazed at how many active (fundamental research based) portfolio managers do not have a structured process for sourcing ideas. They would do well to follow Greenblatt’s advice.

    I use Greenblatt’s screen to run ~80% of my personal account. I like it because we can’t trade in stocks that our fund is also trading (mostly large cap growth), so small-cap value stocks aren’t blocked as often.

    Starting this March, I buy three stocks every quarter, narrowing his list down by P/B and PEG ratio and picking some names I’ve always wanted to own and are in diverse industries. I agree that minimum position should be $2,000 – with $10 trades that’s 1% drag. 1% is a small price to pay for the expected outperformance.

    My portfolio is up 28% on an average 5.4 month holding period.

    Total Portfolio
    28.1% Return since inception
    8.2% S&P Return
    20.0% Outperformance

    Tranche 1
    48.8% Return since inception
    8.0% S&P Return
    40.8% Outperformance

    Tranche 2
    19.8% Return since inception
    9.4% S&P Return
    10.4% Outperformance

    Tranche 3
    15.7% Return since inception
    6.0% S&P Return
    9.8% Outperformance

    So far I’ve replicated his claims, and I plan on sticking with it.

  8. for Sea–
    what are the Tranche 1,2,3 portfolios you mentioned?

  9. For Sea:
    Do you have an easier way to narrow the list down by P/B and PEG? I had to check out each of the 25 stocks and it is very time consuming.

  10. Juan de la Vega says:

    This is what I found on the magic formula website:

    “In general, purchase 5 to 7 top ranked stocks every 2 months or 7 to 9 top ranked stocks every 3 months. After 9 or 10 months, this should result in a portfolio of 20 to 30 stocks.”

    Which “5 to 7” stocks should be purchased?
    How does one narrow down the selection from the stocks returned by the formula’s search screen?
    Isn’t it better to invest equal amounts in all 20-30 stocks instead of cherry picking? I think the biggest concern about investing in 20-30 stocks is trading costs. But trading costs can be minimized by using a discount broker such as Zecco.

  11. It doesn’t matter which 5-7 stocks are picked from the screen. And yes, one should invest in equal amounts in all 20-30 stocks.

    As for the Barron’s article, Greenblatt had actually responded to that in an interview. He claims that the database used by them (not sure which, Bloomberg’s?), does not exclude one time gains. He removed such gains from his analysis.
    One time gains can artificially inflate the earnings yield of a company, and allow it to pop up on the list when it really shouldn’t belong because of a one time event.
    I think it’s also important to point out that one set of researchers in the article did come up with 28% annual returns, which is close enough to Greenblatt’s 30%.

    CompuStat is a widely used database for such research purposes, providing the best point in time picture of stock prices as they were available to the investor.
    The Bloomberg database, it should be noted, is not as widely used for this purpose (if I’m not mistaken, the Barron’s article states that that professor is the only one who uses it).

    What Greenblatt offers is a structured, diversified investment program that should beat the market (by how much though, who knows). It is better than speculating, which is what most investors tend to do.

    I’ve just begun using it. Commissions can take a hit on your earnings, but I’m using Zecco which, as of this writing at least, has 10 free trades a month. That’s all you need anyhow.

  12. I have not read the book, just Jonathan’s review. But based on that, the premise impossible to accept. In order to accept this premise we have to believe that there are thousands of mutual fund managers out there who all would love to be getting 30% returns year after year, but the idea of “buying a good company at a bargain price” never occurred to them.

    Personally I have a small portion of my portfolio devoted to individual stocks and *of course* I look for good companies at bargain prices (I should have written a book instead!)… and I use some really good screeners to find them. What typically happens is: a few of them really are bargains. They take off and double in value. However, others appear to be bargains but a few months down the road, the reason they appeared to be bargains becomes apparent and their market value tanks. The bargain price might be because of an upcoming train wreck that not everyone digs deep enough to foresee. Avoiding the train wrecks – that’s where the hard work lies.


  1. Weekly Review - 11/04/06 says:

    […] My Money Blog writes a straight forward review on “The Little Book that Beats the Market.” […]

  2. The Paranoid Brain » Review of The Little Book that Beats the Market by Joel Greenblatt - Personal Finance and Investing Advice says:

    […] My Money Blog’s review is skeptical that after commissions, taxes, and spreads you will still get the same returns as in the book. I agree completely. But it is true that with online stock trading, the costs are coming down to the point where owning a set of 20-30 individual stocks can be cost effective for portfolios worth $100,000 or more. […]

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