Emily Halverson-Duncan: Welcome to Quant Concepts. Equity analysts often make references to different ratios they use to determine whether a stock is a buy or a sell. These ratios are created from information derived from many different sources, one of which is a company's balance sheet. Recall that the balance sheet is a statement outlining a company's assets, liabilities and shareholder equity. Analysts use the information available in the statement to help them make their decision surrounding whether or not that company is a worthwhile investment. Today's strategy is going to look for companies with strong balance sheets in the CPMS U.S. universe and see how that model would have done over time. So, let's take a look at how to build that.
First off, as always, we're going to rank the stocks in our universe. Here our universe has 2,097 stocks and that's in the U.S. CPMS database. How we're going to rank that universe, first off is looking for stocks with a high cash flow to debt ratio. So, wanting to have more cash flow per unit of debt, as well as a high return on invested capital, and that's looking at the profitability of a company. From there, once we rank our universe, we're going to screen out the stocks we don't want to own. Some of the screens we'll apply here. For cash flow to debt, we want that to be in roughly the top half of peers. So that's a ratio of 0.27 or higher. Long term debt to equity, so it looks at how much debt per unit of equity a company has, we want that to be less than or equal to 1.1. So, what that means is we're okay with them having a little bit more debt than they do equity, but not wanting them to have too much. Debt to total assets, we want that to be again in the bottom half of peers which is about 0.4 or below, again, trying to keep them out of debt they've got at a lower level. And then lastly, we want our market cap to be in roughly the top half of peers which is about C$1.8 billion or higher.
On the sell side, we're going to sell stocks if that cash flow to debt ratio falls below the bottom third of peers. So that'd be about 0.14 times or below. And then if your long-term debt to equity rises above 1.3. So, they're taking on too much debt. So now we want to see how that model did across the long term.
Here we're going to run a backtest from April 2004 until the end of January 2020, and we're going to be purchasing 15 stocks. One thing to remember as you're watching the backtest, is our backtest doesn't have any survivorship bias. What that means is if a company were to go bankrupt within the backtest timeframe, we're still going to keep the history and the stock will stay in the backtest until it's either sold out or delisted.
Okay, so the model returned 13.5% annualized across that timeframe, which represents a 4.3% outperformance over the benchmark, which here is the S&P 500. Turnover is very, very low at 6%. So again, we're buying 15 stocks and what that would represent is probably about one maybe two trades a year on average. Let's look at the volatility as well. Downside deviation, which looks at the volatility of negative returns is actually on the higher side for this model. So here it's about 13 times for the strategy versus 9.3 for the benchmark. You can see that's higher what that's showing you is that in down markets, it's actually a little bit more volatile for the model compared to the benchmark. And the chart that I always like to look at is the green and blue chart here. So this shows in up markets this model outperforms 61% of the time, but in down markets, it actually only outperformed 44% of the time.
So, while the numbers do look pretty good of the outperformance, there is still some volatility associated with it. So definitely worthwhile looking at your risk tolerance before following anything of this style.
From Morningstar, I'm Emily Halverson-Duncan.
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