This is a revised version of the backtest on the free cash flow to enterprise value ratio backtest posted a few weeks ago. The free cash flow to enterprise value ratio is a rather sophisticated valuation ratio that should be a part of every value investors toolkit. It is inspired in part by the discounted cash flows method of company valuation.
Several readers requested that Fat Pitch Financials continue using the original $50 million market capitalization minimum filter for backtests versus the $1 billion market capitalization minimum that was used in the last backtest. To determine if this was the consensus, we ran a poll. The results of the poll confirmed the feedback we received, so I am switching back to the $50 million minimum market cap filter and I am also adjusting the liquidity filter based on another comment received. The results of this backtest of FCF/EV ratio with the small market cap minimum is consistent with the previous backtest as you can see below.
For this backtest, I calculated the free cash flow to enterprise value as follows:
Free Cash Flow to Enterprise Value = FreeCashFlowTTM / EnterpriseValue
In Portfolio123, Free Cash Flow (FCF) is calculated as cash from operations minus capital expenditures minus total dividends paid. I’d prefer not to subtract out dividends, but this is not likely to really impact the results of the backtest. Cash from operations is the amount that a company is taking in from its main business operations. Capital expenditures is the amount spent on equipment and property to maintain the current productivity of the business and to drive future growth. The remainder of the cash after these capital expenditures is how much of a company’s profits are available to return to shareholders.
While market capitalization measures the total value of the publicly-traded stock, enterprise value (EV) goes further and attempts to measure the value of the entire company. Many see it as the minimum price someone seeking to acquire the company would have to pay. The formula we used by Portfolio123 is as follows:
+ total debt
+ value of preferred equity
+ minority interest (redeemable + nonredeemable)
– cash & equivalents
It is possible for an extremely cash-heavy company to have a negative enterprise value but we are not considering those situations in this backtest.
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 a similar filtered universe of stocks as my recent change is shares outstanding backtest. The only major difference is that I increased the minimum market capitalization to $1 billion to better match the size of companies in the S&P 500 equal weight benchmark that I use for these backtests. I’ve designed the filtering criteria for this backtest 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 the Financial Sector. The concept of free cash flow does not really work the same way for banks and other financial sector companies.
- Liquidity test. Instead of using the average daily total dollar amount traded, we revised this liquidity test based in part on Randy Harmelink comment. The minimum daily total amount traded over the past 42 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. This filter was revised back to $50 million based on reader feedback. 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.
- Free Cash Flow to Enterprise Value != NA. We want to make sure we are only looking at companies that have valid data for the free cash flow to enterprise value ratio.
After these filters are applied, we are left with approximately 1,800 to 2,600 stocks. These stocks are then ranked by the criteria being tested; in this case, we are testing the FCF/EV ratio. The lowest 20 percent of stocks ranked by FCF/EV 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 free cash flow to enterprise value ratio in red and the S&P 500 Equal Weight Index in blue. The first quintile includes the companies that have negative free cash flow to enterprise value ratios and the 5th quintile includes the companies that had the highest free cash flow to enterprise value ratios.
Free Cash Flow to Enterprise Value Backtest Returns (2000 – 2015)
The first quintile clearly and consistently underperforms the S&P 500 equal weight benchmark as expected.
The top 20% of stocks as ranked by FCF/EV outperformed the benchmark in the 2000 to 2015 time period.
Summary of Results for the FCF/EV Backtest
The first quintile exhibited a clearly negative annualized return, versus when we ran this backtest with a $1 billion minimum market cap. The stock of these companies that had negative FCF/EV ratios underperformed the market in 75% of the years in this 16-year test period. The average excess returns versus the S&P 500 equal weight benchmark were a negative 4.32%. In contrast, the 5th quintile outperformed the benchmark 81.25% of the time and produced average excess return of 5.36%. Average excess returns seem to increase in almost a linear fashion from the 1st quintile to the 5th quintile, which gives me more confidence that the FCF/EV ratio does have a direct relationship with 1-year stock returns.
It also appears that adjusting the liquidity ratio to use a minimum daily total dollar value traded versus an average daily total dollar amount traded helped to bring the total and annualized return of the backtest universe more in line with the S&P 500 Equal Weight benchmark.
I encourage you to try backtesting other valuation ratios. Just sign up for a free 30-day trial at Portfolio123 and report your findings in the comments section below.