The price-to-book ratio (P/B ratio) is a popular valuation ratio. It is calculated by taking the latest stock price and dividing it by book value per share. Book value is simply the total assets found on the balance sheet minus liabilities, which is referred to as common shareholder’s equity. To get book value per share all you have to do is divide book value by the number of shares outstanding.
Let’s see how well the P/B ratio performs. I used the data and backtesting tool provided by Portfolio123. This backtest uses the same filtered universe of stocks as my recent market capitalization backtest. I’ve designed the filtering criteria for this backtest specifically for individual investors and with a focus on enhancing data quality. The filters include the following criteria:
- No OTC stocks. Stocks not traded on the New York Stock Exchange, NASDAQ, or American Stock Exchange markets are excluded. The quality of fundamental stock data for OTC can be somewhat lower and less timely that that for stocks traded on major exchanges.
- No ADRs. Fundamental data for foreign American Depositary Receipt can include errors due to currency exchange, different accounting standards, and share count.
- Exclude miscellaneous financial services industry. This is mainly to filter out closed-end funds.
- Liquidity test. The average daily total amount traded over the past 60 trading days must be larger than $100,000. This amount was selected so that a $1 million dollar portfolio could hold 100 positions and that each new $10,000 position would not exceed 10 percent of a day’s trading volume. The liquidity test also ensures that the backtest has reliable market price information for any of the stocks that are being tested.
- Market Cap > $50 million. Nano cap stocks are excluded to help improve data quality. This filter also ensures that positions in a modest sized portfolio never exceed one percent of shares outstanding or the available float for a company.
- Price > $1. True penny stocks are excluded due to various information issues and manipulation of these stocks.
- P/B Ratio > 0. This filter insures we are looking at stocks that actually have price-to-book value ratio data.
After these filters are applied, we are left with approximately 3,000 to 4,000 stocks. These are then ranked by the criteria being tested; in this case, we are testing the P/B ratio. The top 20 percent of stocks ranked by P/B ratio are placed in the first quintile and the next 20 percent in the second quintile and so forth until we have five portfolios of stocks. The portfolios are rebalanced every 12-months and compounded annually to more realistically replicate what an individual investor might be expected to do to avoid higher short-term capital gains tax and trading costs. To help ensure that the test is not impacted by seasonal or statistical effects, the backtest is also started at four different points during the calendar year. The results of the quarterly tests are used to calculate the average excess returns for each quintile. The results for the 10-year P/B ratio backtest are as follows:
P/B Ratio: Average Excess Returns vs. Universe
P/B Ratio: Rolling 3-Yr Periods Excess Returns vs. Universe
The top quintile with the lowest price-to-book value ratios clearly outperformed the market by a significant margin. The average annual excess return versus the universe of stocks tested was 4.89% from 2001 to 2011. The 5th quintile also underperformed the market by a significant margin. The average annual underperformance was 3.84%. If you look at the graph of rolling 3-year periods above, however, it does not appear that the top quintile (blue line) has continued to outperform in recent years and the bottom quintile has barely underperformed the market since around 2007. Nevertheless, there is a fairly linear relationship between quintile and excess return as shown in the bar graph above. This indicates that there is a strong relationship between the P/B ratio and excess returns. The biggest weakness of the P/B ratio strategy appears to be its volatility. The maximum loss of 52% for the first quintile and the maximum gain of 62% for the bottom quintile clearly indicates that the P/B ratio doesn’t always work. This volatility is also clearly shown in the relatively low Sharpe ratio of 0.34 for the top quintile versus the Sharpe ratio of 0.32 for the universe.
While the price-to-book ratio can indicate the potential for value opportunities, it doesn’t always work. Do you use the P/B ratio regularly? If so, please share with us why you prefer this ratio in the comments section below.