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Emily Halverson-Duncan: Welcome to Quant Concept's virtual office edition. With all the market volatility that has followed the COVID-19 pandemic, most investors are focused on how best to position their portfolio to withstand those fluctuations. However, one thing to consider is how your portfolio should be positioned to recoup gains once the market recovers. Historically, we've seen styles that tend to be hit harder in down markets recover quicker. That's not always the case, of course, but serves as a good rule of thumb. One of the styles that gets hit the hardest in downturns is value. In other words, portfolios that hold stocks which currently trade below their intrinsic value or what the stock is worth. Value stocks also tend to be some of the best-performing stocks following a down period.
In today's article, I'm showcasing a model which searches for value companies within the CPMS Canadian universe. So, let's take a look at how to build that.
So, first off, as always, we're going to go through and rank our universe of stocks, which is the CPMS Canadian universe and today that holds 694 names. The factors that we're going to use to rank – price to trailing earnings. So, that's a stock's price compared to its last four quarters of trailing earnings. Price to forward earnings looks at a stock's price compared to what the stock is expected or projected to post in earnings for the current year. Price to book value looks at a stock's price relative to their book value on paper. All three of those metrics we want to see a lower value because that indicates that a stock is on the lower valuation side. And lastly, cash flow to debt. So, that's looking at how much a company has on record of cash flow for the last four quarters divided by their long-term debt. In that case, we actually want to see a higher value. So, you want to see more cash flow available compared to the debt the company has to pay off in the long term.
Once we've organized our universe of stocks in the ranking step, we're going to go ahead and screen through using the following filters. So, on that price to trailing earnings and price to forward earnings metrics, we want to value that in the bottom 50% of peers. So, what that looks like for price to trailing earnings is the value less than 13.4 times P/E and forward earnings less than 13.19 P/E. So, pretty close metrics there. Our payout ratio, so that's looking at how much a company is paying out in dividends divided by their earnings per share, their estimated earnings per share. We want that to be less than or equal to 80%. And the reason for that cap is to make sure companies are paying out all of their earnings in dividends but are still retaining some for growth. Market cap we want it to be in the top half of peers which today has a value of 277 million roughly. And last year five-year beta which looks at the sensitivity of a stock relative to the index. We want that to have a value of less than or equal to 1, meaning that it's as sensitive or less sensitive than the market.
On the sell side, we are going to sell stocks if that payout ratio rises above 100%, so if they are paying out more in dividends than they are projected to earn and if that five-year beta rises above 1.2, so if they are just becoming too sensitive.
Once all that's done, we want to see, of course, how that does in our back test. So, if we take a look here, our back test here comprises of 15 stocks and the time period was from December 1991 to March of 2020. Across that timeframe the model returned 10.8%, which is an outperformance of 3.4% over the benchmark, which in the case is the S&P/TSX Composite. Turnover as well was 31%. So, recall that turnover is how often you are trading in a model. 31% means you are trading roughly, say, 5 of those 15 stocks in an average year. But really, one thing we want to look at is, how did it do following a downturn.
So, if we look at the calendar year numbers for this particular model, we can see that in 2008 when the market was down minus 33%, the value strategy was down about the same at minus 30.13%. So, it actually did a little bit better in '08, but still pretty negative in that year. In 2009, however, the market recovered quite a bit, 35.06%, but this model actually came back 57.67%. So, that's an outperformance of about 22%. So, we can see that following a downturn the value strategy despite the fact that it was hit so hard in that downturn actually came back quite a bit stronger than the market did. So, when you're looking at your portfolio, it may be worthwhile to see do you have any names right now that look to be undervalued compared to their peers. Those might be ones we're holding on to because history does show that value tends to come back quite strongly following a downturn.
For Morningstar, I'm Emily Halverson-Duncan.
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