Many scientific studies confirm that buying a portfolio of low price-to-book companies will beat the market over time. It makes sense: you buy companies for less than what they're worth on paper. More experienced investors would argue that book value doesn't always provide an accurate picture of the company value, and a full review of the assets will help get a better understanding of the real value. While this criticism is correct, one can't deny the conclusions of these studies. Furthermore, studying these companies in great detail takes a considerable amount of time and the information necessary to perform an accurate estimate of all assets is not always available to all investors.
Joseph Piotroski, a professor in accounting at the Stanford University Graduate School of Business, had a closer look at the data used in these studies and found that in a portfolio consisting of the lowest price-to-book companies, the profits were generated by only a few stocks. In fact 44% of the companies performed worse than the market. So he thought to himself: wouldn't it be great if I could find an easy way to filter out these companies?
Piotroski wondered whether he could remove these bad apples by looking at the company financial data for the last year. He devised a scoring system called the Piotroski F-Score, a 9 points scoring system based on profitability, funding and operational efficiency. It looks at simple things such as: 'has the company made more profit compared to last year?' (+1 point) but also: 'is the company cooking the books by adjusting accruals?' (0 points). By using 9 points he was able to get enough signals to determine whether the company is really improving or not.
What he found in his research is that this score helped to predict the performance of low price-to-book stocks. In his backtests he found that this strategy outperformed the market by 10% a year on average between 1976 and 1996. The tests also showed that this was even more the case for small and medium sized companies. Piotroski attributes to the fact that these stocks are often outside of the radar of analysts and new information about a company doesn't get reflected in the share price as quickly.
You can read his influential 2000 paper by clicking on the following link.
“by selecting low Price-to-Book companies and by filtering out the best companies using a set of accounting signals, one could have generated a 23% average yearly return from 1976 to 1996.”
Our Piotroski screener selects the 20% lowest price-to-book companies and filters these out the ones with an f-score of less than 7.
The f-score is the sum of 9 binary scores in 3 categories:
To calculate this year's number we use the last trailing 12 month (TTM) number available. For last year we use the same number 1 year ago.
The F-Score is often used in combination with other screens. Our tests showed that if you filter the results of the ERP5 screen by only selecting companies with an F-Score of 7 or more, the return increases from 18,66% to 19,5% per annum. (1999-2010). Many of our members also like to use it in combination with the Greenblatt Magic Formula. We added both screens to our templates and called them the ERP5 Best Selection and the Magic Formula Best Selection.