The Gross Profits to Assets ratio is another profitability measure. This fundamental was recently mentioned by Ken Faulkenberry in the comments section of my Return on Assets Backtest article. Ken was interested in seeing a backtest of this fundamental.

Apparently, the gross profits to total assets ratio is starting to gain popularity among value investors. It was detailed and researched in a 2012 paper by Robert Novy-Marx titled, The Other Side of Value: The Gross Profitability Premium. Novy-Marx found that profitable firms generate significantly higher returns than unprofitable firms, despite having significantly higher valuation ratios. The gross profit to asset ratio was also discussed in the recent book by Tobias Carlisle, Deep Value. Tobias found that gross profit to asset ratio was superior to Joel Greenblatt’s return on invested capital since it avoided picking up small companies with large cash holdings relative to their size.

Gross Profits to Assets ratio is calculated as follows:

Gross Profits to Assets = Gross profits / Total Assets

Let’s take a look at a backtest of the Gross Profits to Assets ratio to see how it performs. I used the data and backtesting tool provided by Portfolio123. The Portfolio123 backtesting eliminates the problem of survivorship bias by using point-in-time and retaining data on stocks that have gone to zero. This backtest uses the same filtered universe of stocks as my recent Piotroski F-Score 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. 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. Gross Profits != NA. This filter insures we are looking at stocks that actually have valid gross profit numbers. Total Assets != NA. This filter insures we are looking at stocks that actually have valid total asset numbers.

After these filters are applied, we are left with approximately 3,300 to 4,200 stocks. These stocks are then ranked by the criteria being tested; in this case, we are testing the Gross Profits to Assets ratio. The lowest 20 percent of stocks ranked by the gross profits to total assets 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. The following 5 charts display the quintile returns for the Gross Profits to Assets ratio in red and the S&P 500 Equal Weight Index in blue. The first quintile includes the companies that had the lowest gross profits to assets ratio and the 5th quintile includes the companies that had the highest gross profits to assets ratio.

Gross Profits to Assets Ratio Returns – 2000 – 2014

Summary of Results for the Gross Profits to Assets Ratio Backtest

* Average excess returns were analyzed starting in each month with 12-month holding periods (197 sample periods). This avoids the potential for seasonal reporting bias.

This backtest for the gross profits to assets ratio reveals that the first quintile underperforms the S&P 500 Equal Weight Index benchmark. These companies typically are unprofitable and/or are cash box companies that are unlikely to have much upside to their stock returns. The second through fifth quintiles have higher than average annual excess returns and the average excess returns increase slowly until you get to the fifth quintile. The average excess return for the fifth quintile is 1.4% higher than the fourth quintile. Backtesting reveals that stocks in the top 20% of gross profits to assets return 12.32% annualized from 200o to 2014. This fundamental seems to work well at both identifying under-performers in the stocks with the lowest gross profits to assets and outperformers in the stocks with the highest gross profits to assets.

My guess is that the gross profit to total asset ratio works really well when combined with a valuation fundamental. I’ll have to check that out in the future when I move to two factor models.

What are your thoughts on the gross profits to assets ratio? Are you already using this newer ratio or some variation of it in your own stock analysis?