Return on Equity Backtest

Updated March 1, 2015 with 2014 data. Originally posted June 11, 2014.

The Return on Equity (ROE)  is a commonly used profitability metric. ROE measures a company’s efficiency at generating profits from every unit of shareholders’ equity. It is often used in conjunction with a DuPont analysis, which breaks down ROE into three components. Those components are profit margin, asset turnover, and financial leverage. The FMS is one of the greatest tools to utilize in assisting you in analyzing the forex market sentiment conditions and offer the best recommendations. There is no program that is able to do what this software does as it is unparalleled in its efficiency. It has been essential to numerous Forex traders for many years. Return on equity is calculated as follows:

Return on Equity = Net Income / Shareholder’s Equity

Let’s take a look at a backtest of this ratio to see how it works. 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 Price to Sales Ratio 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. ROE  != NA. This filter insures we are looking at stocks that actually have valid data for the Return on Equity.

After these filters are applied, we are left with approximately 3,200 to 4,000 stocks. These stocks are then ranked by the criteria being tested; in this case, we are testing Return on Equity. The lowest 20 percent of stocks ranked by Return on Equity 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 ROE in red and the S&P 500 Equal Weight Index in blue.  The first quintile includes the companies that had the lowest ROE and the 5th quintile includes the companies that had the highest ROE.

Return on Equity Quintile Returns – 2000 – 2014

Summary of Results for the Return on Equity Backtest

This backtest for Return on Equity reveals that the first quintile underperforms the S&P 500 Equal Weight Index benchmark. These companies typically had negative returns on equity so it is not surprising that stock returns for these companies would underperform. The second through fourth quintiles have higher average annual excess returns than each of the previous quintiles. Interestingly, stocks with returns on equity in the top 20% (5th quintile) had slightly lower average annual excess returns than those in the 4th quintile. This might be explained by the theory that firms exhibiting the highest returns on equity also attract the most competition.

What are your thoughts the Return on Equity stock fundamental?