# Return on Invested Capital (ROIC) Backtest

The Return on Invested Capital (ROIC) ratio is a very popular measure of company “quality” among value investors. Many even use this metric as part of their valuation models to account for future sustainable growth. Professor Aswath Damodaran discusses the significance of ROIC in detail in his widely quoted paper, Return on Capital (ROC), Return on Invested Capital (ROIC)

and Return on Equity (ROE): Measurement and Implications. I highly recommend you read that paper if you are interested in ROIC.

I’ve previously backtested a variation of ROIC submitted by one of Fat Pitch Financials’ readers. It’s been a couple of years since I ran that backtest, so I decided to revisit this metric with a simpler version of ROIC that I prefer using for backtesting. There are many different variation on the formula for ROIC. Unfortunately, there is no definitive formula for this ratio. For this backtest, I calculated return on invested capital as follows:

ROIC = (OperatingIncomeTTM * (1 – Max(TaxRateTTM, 15%)) / (TotalEquityPreviousYearQtr + TotalDebtPreviousYearQtr – CashAndEquivalentsPreviousYearQtr)

I use an estimate of after tax operating income in the numerator of the ratio. Max(TaxRateTTM, 15%) just means that I use either the trailing twelve-month effective tax rate or 15%, whichever is higher. I use this to prevent using an overly low tax rate, if for example a company is carrying forward net operating losses from previous years. It’s not a good idea to assume that government won’t eventually get its cut of the profits.

For the denominator of the ROIC ratio, I estimate total invested capital to be equal to total equity and debt minus cash. Ideally, I would estimate excessive cash using some fancy formula, but in reality this rarely makes a difference in the final outcome.

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 5-Year Average Return on Investment 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.**ROIC != NA**. This filter insures we are looking at stocks that actually have valid data for the 5-year average Return on Investment ratio.**Sector not Financial**. Financial stocks are excluded since ROIC doesn’t make much sense for this sector.

After these filters are applied, we are left with approximately 2,600 to 3,300 stocks. These stocks are then ranked by the criteria being tested; in this case, we are testing return on invested capital. The lowest 20 percent of stocks ranked by ROIC 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 ROIC in red and the S&P 500 Equal Weight Index in blue. The first quintile includes the companies that had the lowest ROIC and the 5th quintile includes the companies that had the highest ROIC.

## Return on Invested Capital Quintile Returns – 2000 – 2014

## Summary of Results for the Return on Invested Capital Backtest

The results for this backtest are similar to my previous backtest of a variation on ROIC. While the first quintile produced the lowest returns, the 4th quintile produce the highest returns. The top 20 percent of stocks sorted by Return on Invested Capital (ROIC) was found to just underperform the benchmark, the S&P 500 equal weight index. This distribution of excess returns is similar to that of the other profitability measures I’ve tested including, ROE and ROI. I’m surprised to see that ROIC under-performed ROI and ROE. Seeing lower excess returns for the top quintile is consistent with the theory that the most profitable companies often attract the most fierce competition.

I encourage you to try backtesting other ROIC formula variations. Just sign up for a free 30-day trial at Portfolio123 and report your findings in the comments section below.

Interesting result George but its something we have also found.

We have however found a quality ratio that works. Its the gross income ratio as defined by Professor Novy-Marx and is calculated by dividing gross profits by total assets.

I wrote about it in here: http://www.quant-investing.com/blogs/general/2015/01/28/have-you-been-using-the-wrong-quality-ratio

Why not use ROIC as net income divide by (total equity+long term liability)

In my own simplified backtest. I found it to be compelling. Hope u can try and back test it as well