Investors love simple rules of thumb. A simple stock picking rule that has stood the test of time is to buy stocks with low trailing Price-to-Earnings (P/E) or Price-to-Book (P/B) ratios. There is overwhelming evidence to show that low P/E (P/B) stocks, on average, outperform the market and high P/E (P/B) stocks. For example, low P/E (P/B) stocks, on average, outperform high P/E (P/B) stocks by between 6% and 13% p.a. depending on the country.
But averages can be misleading! This is because about 39% of the low P/E (P/B) stocks experience negative returns for the 12 months following their selection. And while it is true that as a group they outperform, one needs to have a lot of funds to be able to buy all the 50 or 60 stocks that fall in the lowest P/E (P/B) quartile of stocks, namely stocks with a P/E < 13 or P/B < 1.2.
Investing randomly in, say, 10 of these low P/E (P/B) stocks, due to lack of funds, may not be a good idea as the investor may happen to choose the 10 stocks that will underperform, leading to feelings of disappointment and disenchantment with value investing. But value investing is not just investing in low P/E (P/B) stocks, even though a commonly held misconception is that all value investors do is sort stocks by P/E (P/B) and invest in those with low P/E (P/B).
Value investing is a process that involves three steps and selecting low P/E (P/B) stocks is the first step – the step of searching for possibly undervalued stocks. The second step is that of valuation of possibly undervalued stocks to determine their intrinsic value. The third step is the one that identifies truly undervalued stocks – those that meet the margin of safety requirement and are destined to outperform. This is how value investors are able to separate the good from the bad low P/E (P/B) stocks.
But this is not easy to do for the average investor and, even for professionals, it is a very time consuming exercise. Is it possible to identify the good low P/E (P/B) stocks (i.e., the truly undervalued or quality stocks) without having to go through the time consuming estimation of each stock’s intrinsic value?
Here is the approach I have developed to deal with this question, and a quick review of other approaches:
I remove the time-consuming step of valuing each stock individually by assigning a Score to each stock that is based on publicly available financial ratios from historical company information. First, I sort the stocks in my sample by trailing P/E ratios from low to high and form quartiles. Value stocks are those that fall in the lowest quartile. A Score for each value stock is then assigned based on six historical variables: market cap, stock liquidity (i.e., annual trading volume/shares), asset turnover (i.e., assets/revenues), total debt to equity, cash to assets and year-over-year EBIT annual growth rate, one variable at a time. The overall Score is derived by assigning a value of 1 (for good ranking) or the value of zero (for bad ranking) to each of the six firm-specific variables and summing up the zero or one values for each firm. Finally, I form seven portfolios of firms with Score values from low to high.
Using US stock data, I find that value firms with the highest Score had a mean annual return of 54.38% from 1969 to 2011. The lowest Score value firms had a mean annual return of 13.32%. For comparison, the mean annual return for all value stocks was 22.36%.
Using Canadian non-interlisted stock data, I find that value firms with the highest Score had a mean annual return of 36.89%, whereas the lowest Score portfolio had a mean annual return of -11.35% from 1985 to 2009. For comparison, the mean annual return for all value stocks was 16.86%. (Non-interlisted Canadian stocks were used to test the robustness of my approach since these stocks are very different from the US stocks based on size, liquidity and visibility).
Others have followed similar approaches to identify quality or outperforming low P/E (P/B) stocks.
Joel Greenblatt develops a “magic formula” that uses return on capital (ROC) (namely, EBIT/Tangible Capital) as a key metric to select quality value stocks. He ranks value firms by ROC and buys only stocks with high return on capital.
Joseph Piotroski uses a Score to separate the good from the bad value stocks. His Score consists of nine variables that take the value 0 (bad signal) or 1 (good signal). His variables capture profitability (positive earnings, positive cash flows from operations, increasing return on assets and negative accruals), operating efficiency (increasing gross margins and asset turnover) and liquidity (decreasing debt, increasing current ratio, and no equity issuance). The Score for a stock is then the sum of the 0 or 1 values for all firm-specific variables.
Ben Graham uses another Score-related approach to identify quality value stocks. A good Score (i.e., value of 1) is assigned if the current ratio exceeds two, or net current assets exceed long-term debt, or 10-year history of positive earnings, or 10-year history of returning cash to shareholders or EPS are at least a third higher than they were 10 years ago. Otherwise, the Score is zero. The Score assigned to a stock is then the sum of all 0 or 1 values.
Finally, Robert Novy-Marx uses a simple measure for quality, namely gross profits to assets (GPA), and focuses on those value stocks that have a high GPA.
For all markets examined, irrespective of the approach followed to identify truly undervalued stocks, it was possible to separate winning from losing value stocks when stock selection took place by focusing on high Score or quality value stocks. Consequently, an additional screening (based on a Score or quality indicator) to the first screening of the value investing process (i.e., only looking at low P/E (P/B) stocks) adds considerable value to an investment strategy and makes stock picking simpler, easy to standardize and, hence, faster.