Return on Assets Backtest

Return on Assets (ROA) is a fundamental measure of profitability based on how much net income is generated by a company’s assets.  Return on Assets is calculated as follows:

Return on Assets = Net Income / Average Total Assets

Return on Assets recently came up in a discussion regarding the Piotroski F-Score Backtest.  Return on assets is part of the third test for the Piotroski F-Score.  That test check to see if current ROA is higher than previous year ROA. A reader noted that in his experience, higher ROA actually seems to lead to lower alpha in bactest.  I was curious to test this out.

Let’s take a look at a backtest of the Return on 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:

  1. 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.
  2. No ADRs. Fundamental data for foreign American Depositary Receipt can include errors due to currency exchange, different accounting standards, and share count.
  3. 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.
  4. 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.
  5. Price > $1. True penny stocks are excluded due to various information issues and manipulation of these stocks.
  6. ROA  != NA. This filter insures we are looking at stocks that actually have valid ROA numbers.

After these filters are applied, we are left with approximately 3,300 to 4,100 stocks. These stocks are then ranked by the criteria being tested; in this case, we are testing Return on Assets. The lowest 20 percent of stocks ranked by ROA 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 Return on Assets in red and the S&P 500 Equal Weight Index in blue.  The first quintile includes the companies that had the lowest ROA and the 5th quintile includes the companies that had the highest ROA.

Return on Assets Returns – 2000 – 2014

ROA 1st Quintile
Return on Assets 1st Quintile
ROA 2nd Quintile
Return on Assets (ROA) 2nd Quintile
ROA 3rd Quintile
Return on Assets (ROA) 3rd Quintile
ROA 4th Quintile
Return on Assets (ROA) 4th Quintile
ROA 5th Quintile
Return on Assets (ROA) 5th Quintile


Summary of Results for the Return on Assets Backtest

Backtest Results for ROA (2000 - 2014)
15-year Backtest Results for Return on Assets (ROA)

* 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.

ROA Excess Returns by Quintile chart
Average annual excess returns from 2000 to 2015 for Return on Assets (ROA)

This backtest for ROA reveals that the first quintile underperforms the S&P 500 Equal Weight Index benchmark. These companies typically are unprofitable, so it is not surprising that stock returns for these companies would underperform. The second through fifth quintiles have higher than average annual excess returns but the excess returns do not increase consistently as ROA increases.

I noticed that stocks in the lowest quintile clearly under performed the benchmark.  The median ROA for this first quintile is -14.79 while the median for all the other quintiles are positive. It appears the most powerful feature of ROA is associated in identifying stocks with negative returns on assets to avoid poor performers. I also noticed that companies with average, or in this case median ROA, likely outperform stocks that have either higher or lower returns on assets.

Given that the amount of assets required to earn net incomes varies considerably between heavy industries, such as mining or manufacturing versus the service sector that may require very few physical assets. ROA might be best used for comparing companies within industries or sectors.

What are your thoughts on the Return on Assets fundamental? Do you use ROA or some variation of it in your own stock analysis?

5 thoughts on “Return on Assets Backtest

  • February 23, 2015 at 5:45 pm

    Sorry but return on assets measured as NI/TA makes no sense at all. You are comparing the residual company flows, net income, to the total assets, which could be financed either with a lot of debt, a lot of equity or a balanced mixed between the two. Net income relates to equity. Operating profit, NOPAT to assets.

  • February 23, 2015 at 9:14 pm

    Have you had a chance to do a back test on Gross Profit / Total Assets? This is a profitability and efficiency ratio researched by Robert Novy-Marx to identify stocks that outperform the market in the long run.
    This metric is gaining popularity in value investing circles. You can find an outstanding explanation of this ratio in Deep Value by Tobias Carlisle, pages 194-195. His back testing has shown this to be a valuable indicator of future stock performance.
    Keep up the good work!

  • February 24, 2015 at 9:46 am

    Hi Ken,
    I’m checking out the Gross Profit/Total Assets ratio right now. I haven’t gotten a change to read Deep Value yet, but I’m starting to think I should soon. Check back later this morning for my backtest results on this ratio.

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