Magic Formula investing & Price Index 6m

In this article I show you the returns the Magic Formula achieved in Europe over the 12 year period from June 1999 to June 2011.

Good ideas on how to improve the Magic Formula

I also show you how you can improve the Magic Formula returns as we also tested it with 14 other ratios and indicators.

First a bit of background information.

As you most likely already know the Magic Formula investment strategy was developed by Joel Greenblatt and described in his excellent book called The Little Book that Beats the Market.

It is also the book that got me started with quantitative investing.

What the Magic Formula does

The Magic Formula identifies good quality companies that are trading at an attractive price.

It does this by looking for companies with a high earnings yield (companies that are undervalued) and a high return on invested capital (ROIC) (quality companies).

The formula then ranks the universe of companies on ROIC (where 1 is the company with the highest ROIC), and by earnings yield (where 1 is the company with the highest earnings yield), and then sum the two ranks to give a combined score.

The screener does all this for you with the click of a button.

Companies with the lowest combined rank (high quality companies that are undervalued) are recommended for purchase, usually the top 30 companies.

This is how the two Magic Formula investing ratios are calculated:

Return on invested capital (ROIC) = EBIT / (net working capital + net fixed assets).

Earnings yield = EBIT / Enterprise value.

Before I  show you the returns of the Magic Formula applied to European companies first some information on how we tested.

Methodology

We only use historical accounting data and no forecasts.  The reason being is that there is ample evidence that forecasts cannot be relied on.  For example, in his excellent book, ‘The New Contrarian Investment Strategy’, David Dreman mentioned a study that used a sample of 67.375 analysts' quarterly estimates for companies listed on US stock exchanges.

The study found that the average analysts’ error was 40%, and that the estimates were misleading two-third of the time!  A less important but not insignificant factor is that historical accounting data is also cheaper.

The backtest universe and benchmark

Our backtest universe is a subset of companies in the Datastream database containing an average of about 1500 companies in the 17 country Eurozone market during our 12-year test period (13 June 1999 to 13 June 2011). 

We excluded banks, insurance companies, investment funds, certain holdings companies, and REITS. 

We included bankrupt companies to avoid any survivor bias. Bankrupt companies, or companies that were taken over, returns were calculated using the last stock market price available before the company was delisted.

We excluded companies with an average 30-day trading volume of less than €10 000.

It was not a good time to invest in stocks

The test period was most certainly not a good time to be invested in stocks.
The 12-year period we tested included a stock market bubble (1999), two recessions (2001, 2008-2009) and two bear markets (2001-2003, 2007-2009). 

In spite of all the substantial movements, over the whole period it was essentially a sideways market, as Vitaliy Katsenelson defined in his book, ‘The Little Book of Sideways Markets’. 

Holding periods and quintile tests

Each year all the portfolios we tested were formed on 16 June.  We chose 16 June as most European companies have a December year-end and by this date all their previous year-end results would be available in the database. 

The annual returns for our back test portfolios were calculated as the 12-month price change plus dividends received over the period.  Returns were compounded on an annual basis. 

This means each year the return of the portfolio (dividends included) would be reinvested (equally weighted) in the strategy the following year. 

The portfolios were all constructed on an equal-weighted basis.

In order to test the effectiveness of a strategy, we divided our back test universe into five equal groups (quintiles), according to the factor we were testing.  For example, when testing a low price-to-book (PB) value strategy, we ranked our back test universe from the cheapest (lowest PB) to the most expensive (highest PB) stocks. 

The cheapest 20% of companies were put in the first quintile (Q1), the next in the second, and so on, with the 20 % of companies with the worse Magic Formula ranking  in the fifth quintile (Q5).

What returns did the Magic Formula generate?

These are the returns the Magic Formula achieved in Europe over the 12 year period from June 1999 to June 2011.

Source: Quantitative Value Investing in Europe: What works for achieving alpha

As you can see companies with the best Magic Formula rank (the most undervalued companies), quintile 1 (Q1) in the above table, did a lot better than companies with the worse Magic Formula rank, and did this for small, medium and large companies.

Substantially better than the market
The best Magic Formula investing companies all substantially outperformed the market which returned only 30.54% over the same 12 year period.

You can improve the returns of the Magic Formula strategy

We also tested the Magic Formula investing strategy with a lot of other ratios and as you can see in the table below the returns of the strategy can be improved substantially.

Source: Quantitative Value Investing in Europe: What works for achieving alpha

In the table the returns you should look at are those in column Q1.

They show the returns generated by first selecting the best Magic Formula companies (most undervalued) and then sorting them by the items in the Factor 2 column.

Best combination +783% was Momentum
This means you could have earned the highest return of 783.3% over 12 years if you invested in the best ranked Magic Formula companies that also had the highest 6 month price index (price momentum).

How to implement this strategy in your portfolio

If you are interested to implement Magic Formula investment strategy in your portfolio I wrote the following article (click on the link) to show you exactly how (step by step):

How to implement the Magic Formula investment strategy

PS To find Magic Formula investment ideas in the countries you invest in (for less than an inexpensive lunch for two) click here: Join today

These Magic Formula articles may also interest you:

Does the Magic Formula also work in Finland?

Does the Magic Formula also work in Belgium, Luxembourg and the Netherlands?

A better alternative to the Magic Formula?

How to get the best returns with Magic Formula investing

Please note:  This website is not associated with Joel Greenblatt and MagicFormulaInvesting.com in any way. Neither Mr Greenblatt nor MagicFormulaInvesting.com has endorsed this website's investment advice, strategy, or products. Investment recommendations on this website are not chosen by Mr. Greenblatt, nor are they based on Mr Greenblatt's proprietary investment model, and are not chosen by MagicFormulaInvesting.com. Magic Formula® is a registered trademark of MagicFormulaInvesting.com, which has no connection to this website.

Period
May 1999 - May 2011

Index
+2.25% pa

Return
+19.9% pa +783.3% 12yr