The Magic Formula is an investing strategy designed by Joel Greenblatt, a professor and former hedge fund manager. According to Mr. Greenblatt, the strategy averaged returns of 30%/year. Learn the strategy below. Also addressed is whether the strategy still works (and whether Greenblatt’s numbers are accurate), potential variations of the strategy and things to consider when utilizing the magic investing formula.
Greenblatt is an American professor and former hedge fund manager who attained extraordinary profits while presiding over Gotham Capital between 1985 and 2006. During that the time the fund returned 40% annualized. Greenblatt used a number of strategies to attain these results. Some of those strategies are laid out in his book, You Can Be a Stock Market Genius. That book contained some more advanced strategies, which explains why it didn’t become as popular as his Magic Formula strategy, which has a simpler premise.
In The Little Book That Beats the Market (2005) and The Little Book That Sill Beats the Market (2010), the successful stock picker outlines his approach. It’s a codified process by which any investor can source undervalued stocks. He calls it his “Magic Formula”.
Greenblatt is predominantly a value investor. This type of investing philosophy looks for mispricing in the market, buying stocks that are priced cheaply compared to the future prospects of the business, or that are cheap compared to what the upside in the stock price is. Value investing requires a valuation of what a stock is actually worth (or could be worth) relative to what it is trading at now.
Of course, the secret sauce for any successful value investor lies in how they calculate their valuation. Some investors rely on estimating future cash flows while others eschew future growth or focus on present earnings.
Joel Greenblatt relies on his Magic Formula.
The Magic Formula For Stock Investing
Value investing is simple when you boil it down to its purest essence. Find good quality companies at a discount and wait until the market catches up (price goes up). In practice, it’s as much an art as it is a science and Joel Greenblatt is particularly good at it – growing his hedge fund from $7 million in assets under management to nearly $15 billion.
Here’s his Magic Formula in greater detail:
- Include only stocks with a minimum market capitalization. For example, greater than $50 million.
- Exclude utility and financial stocks.
- Exclude foreign companies (American Depositary Receipts).
- Determine company’s earnings yield, which is EBIT/EV.
- Determine company’s return on capital, which is EBIT/(net fixed assets + working capital).
- Rank all the companies above the chosen market capitalization by highest earnings yield and highest return on capital (ranked as percentages).
- Invest in 20 to 30 of the highest ranked companies, accumulating 2 to 3 positions per month over a 12-month period.
- Re-balance portfolio once per year, selling losers one week before the year-mark and selling winners one week after the year mark.
- Continue over the long-term, at least 3 to 5 years or more.
There are nine steps, of which the most important are number 4 and 5. Return on Capital and Earnings Yield are the engine of the formula, as those are the metrics by which you end up valuing various stocks. You can think of these two metrics as trying to find above average companies at a below average price.
You may be wondering, what does EBIT/EV mean? These figures can be found on a company’s financial statements. Before investing it is a good idea to have some background on how to read these statements. Gleenblatt’s books provide a bit of knowledge on this subject, but for a more comprehensive guide (but still very easy to read) on understanding financial statements, check out Warren Buffett and the Interpretation of Financial Statements (Mary Buffett).
Understanding the workings behind the machine is always prudent, but Mr. Greenblatt has made it even easier for investors to find stocks that meet the criteria he outlines.
On MagicFormulaInvesting.com you can utilize the free stock screener to produce a list of the highest ranking stocks that meet the criteria mentioned above (the screener does steps 1 through 6 for you). The investor’s only job is to follow through on steps 7 through 9. The site also provides some additional guidance on the strategy via the FAQ and How it Works pages.
Performance of Greenblatt’s Magic Formula Investing Strategy
Seems a bit too simple, right? Especially since you don’t even have to do most of the research work yourself. How does the Magic Formula actually perform in the real world?
To start, we have figures from Greenblatt’s book (2010; the 2005 book showed a higher return mainly because 2008 hadn’t happened yet) detailing its performance.
The chart above shows that Greenblatt consistently outperformed the S&P 500 using this investment strategy. Between 1988 and 2009, he beat the market 18 years out of 22.
All told, Greenblatt returned nearly 24% per year versus 9.55% for the overall market, on average.
Investing $10,000 into this strategy, over the time frame, would have returned just over $1million. In comparison, $10,000 invested in the S&P 500 would have turned into just under $75,000. $1million versus $75,000…that’s a big difference!
Is It Repeatable? Here Are Some Other Tests
Okay, so it works wonders according to Greenblatt, but would this work for anyone? At anytime?
Let’s find out.
Luckily for us, the internet is a wonderful place and many analysts have conducted back-tests of the Magic Formula to try and replicate its results. We’re going to look at the results of several different studies to see how it fared.
As it turns out (spoiler alert), the Magic Formula is not quite as a good as it looks initially.
Old School Value is up first; they backtested the Magic Formula from 1999 to 2009 and found that while it beat the market during that period, it fell short of Greenblatt’s advertised numbers.
The backtested portfolio does come close though, returning 13.74% versus Greenblatt’s 18.57% over that time frame. Old School Value does suggest however, that Greenblatt is reporting his returns free of fees. When you remove the impact of fees on the backtested portfolio the return rises from 13.74% to 17.33%.
It’s not 23% or 30%, but still it still performs quite well.
James Montier, an analyst at Dresdner Kleinword Wasserstein, tested the formula in 4 markets – the US, Europe, Japan and the UK – from 1993 to 2005. The magic formula won in all four scenarios, outperforming the benchmark indexes by 3.6%, 8.8%, 7.3% and 10.8% respectively. This study also provides some interesting variations for the strategy.
P. Postma, featured on Quant Investing, wrote a thesis where he found that the Magic Formula outperformed by 7.7% over a 20 year test period (1995-2014) compared to the combined Benelux (Belgium, Luxembourg, Netherlands) market.
Value Walk found the Magic Formula beat the LSE by 3.6%
Colin Moshman confirms that the Magic Formula continues to beat the market. In a test from the years 2000-2016 he reports that the strategy outperformed by 8.8% when compared to the iShares Russell 3000 – an index that seeks to approximate the performance of the United States equity market.
In the book Quantitative Value, Tobias Carlisle and Wesley Gray ran a test on data from 1974 to the end of 2011. The Magic Formula gained 13.9 per cent per year, versus S&P returns of 10.5 per cent, on average. Again the research shows some interesting variations, such as only using EBIT/EV would have returned 16%.
There were very few studies where the formula was unable to beat the market.
Stockpedia tested Greenblatt’s strategy against the London Stock market over a period of 18 months between 2012 and 2013 and found that it did not beat the market.
Robert Manders found the Magic Formula underperformed the S&P500 by 7%. This is over a one-year period.
Short time frames here makes it difficult to give these findings the same weight as the others. Greenblatt says himself that this strategy should be in place for 3 to 5 years or more (see point 9 of the Magic Formula).
Other Considerations, and Improving Investing Performance
There is a vast amount of variability within the strategy, which back testing simply cannot capture. For example, there is a choice of which stocks to buy. Tiny variations in what stocks are purchased, and when, could significantly impact performance.
Investing in 20 stocks would provide different returns than investing in 30. Not investing in stocks that are very similar (more diversity) would also affect performance.
If you run the screens yourself and focus on value first, then select for quality, you will end up with different results than if you only select the highest quality stocks and then pick the cheapest ones within it.
Setting the minimum market capitalization at 50 million, or 200 million or 1 billion, will change the stocks that meet the criteria.
The stocks that are on the list will change frequently, or at least their rank will change frequently. So even if you and I use the same criteria, if we run our scans at different times we may end up with different stocks. For example, market caps change daily, as do stock prices which will affect the EV calculation. This means the rank of the stocks could change as frequently as daily…which means on any given day, the stocks purchased could differ from other Magic Formula followers who ran their tests (and make purchases) on another day.
You can also choose at what price to buy those stocks. Waiting for a slightly better price than what is available at the start of year (and the “start of the year” will be a different day for different people depending on when they start buying the stocks), or when the scan is run, could produce significantly different results. Waiting for a better price could produce better or worse returns. Better if a trade is made at the lower price, but potentially worse if some big winning trades are missed due to being too patient.
The strategy also recommends purchasing at least 20 stocks over the course of a year, and then selling them. On small accounts, the commissions could sting. If position sizes are quite small then commission could eat into the return making it less effective than simply buying larger positions in diversified index funds (which will cost commissions as well as a yearly management fee, called the expense ratio). So each investor needs to weigh the costs of the various options. As shown, even saving or making 1% extra per year can make a huge difference in the amount of money made over long periods of time.
Also, most of the backtest results are based on the start of the year. Meaning, the results in most of these studies reflect what would have happened if you bought all the stocks at the opening price of the year. Not only is that likely impossible, but there are seasonality factors that tells us buying at certain times of the year is better than other times. For example, January is typically a poor month for stocks, so purchasing toward the end of January or February (March is a better month) would change performance, potentially by 1% per year or more. Buying during summer months may also be beneficial since stocks are typically a bit weaker during these times…which means a lower purchase price. [Note: these variables have not been tested, just food for thought.]
The chart shows the percentage of times the month finished higher than it opened over the last 20 years. The small numbers near the bottom indicate the average percentage rise or fall in that month, over the last 20 years. These figures are for the S&P 500, courtesy of StockCharts.com.
Another Magic Formula variation is to allow winning stocks to continue moving to the upside. A trailing stop loss could be used, for example. One year is an arbitrary holding period, designed mostly for tax purposes and not profit maximization purposes. Exploiting more of the favorable trends could favorably skew the results.
Also, traders can use other metrics to buy the stocks on the ‘strategy buy list’ at a cheaper price. For example, looking at forward P/E and/or P/B (or insert other metrics here) could help filter down the list of stocks to ones that are trading at more attractive valuations. As one of the backtesters proved, looking for value first, then filtering for quality, tends to produce higher returns than going in the opposite order.
The strategy does work, but individual traders can utilize their own skills to help determine what stocks to buy (by looking at other fundamental criteria) and when to buy them (with the aid of some technical analysis). How far traders wish to deviate is up to them. The bones of the strategy can be used to build a more personalized trading approach.
The Final Word on Greenblatt’s Magic Formula
A thorough examination of the Magic Formula indicates that it is the real deal in terms of beating the S&P 500 over long periods of time.
The rules are simple, but can produce a lot of variability which isn’t necessarily reflected in the backtesting data. What a trader buys, and when, will significantly impact results. Also, how a trader screens for stocks (for example, market cap.) will alter the stocks available for purchase. We could all use this strategy and end up with different results…as with most strategies.
Buying good quality stocks is a good investment approach, but investors can add their own twists to help improve performance. The evidence indicates that the Magic Formula provides great bones for a strategy. It works on its own, but investors can dress up the strategy by adding in more analysis, and using other fundamental, seasonal and technical tendencies to help improve performance.
No matter how an individual chooses to trade, have a plan that is trusted and tested, and stick to it for the long-term.
Written by: Jiva Kalan: A researcher and writer whose work is featured on DailyFinance, the Wall Street Survivor and Financial Choice.
and Cory Mitchell, CMT: Trader, investor and author of the Canadian Investor Stock Signals Newsletter.
Disclaimer: This is not investment advice, or a recommendation to buy or sell any particular securities. Nor it is necessarily an endorsement of the Magic Formula strategy. Historical and simulated results may not necessarily reflect future performance.