See more episodes of Quant Concepts here
Emily Halverson-Duncan: Welcome to Quant Concepts' virtual office edition. When you hear the term conservative investment, your first thought may be that low risk implies low return. This assumption has some merit to it as less volatile strategies tend to produce lower and more stable returns. However, a conservative strategy does not necessarily require giving up all of the upside and can in fact still generate upward momentum. Today's strategy is looking for conservative stocks that still offer an attractive upside. So, let's take a look at how to build that.
First off, we're going to go through and rank our universe of stock. Today's universe of stocks is all the Canadian stocks in the CPMS database which is 698 Canadian names. Of those 698 names how we are going to organize them is just by two simple factors. First off is the percent price change from a stock's 12-month high. So, what that's looking at is a stock's price today and comparing it to the highest price the stock has reached in the last 12 months and calculating the difference. Might sound a little funky, it's a momentum factor and essentially what you're looking for is the price that's the closest to the 12-month high. So, the closer you are to the 12-month high, the more beneficial that will be for this particular factor and we found in testing that this is actually a very impactful momentum factor.
The other factor we're looking at for the ranking side is variability of historic earnings per share. So, what that's looking at is a company's history of earnings and how volatile or variable they are. So, a company that's consistently reporting similar earnings will have a lower number for this whereas a company that's constantly going up and down depending on the quarter, that would have a higher variability.
On the screening side, once we've gone through and ranked our universe, some of the screens that we're going to apply here – quarterly earnings momentum, which is looking at the quarter-over-quarter change in earnings is we want that to be positive, so greater than or equal to zero meaning that they are maintaining or growing their earnings. Quarterly earnings surprise – so, that looks at a company's posted earnings and whether or not they beat or missed expectations and again, we want that to be greater than or equal to zero, meaning they've at least met expectations or beat them. That variability of historic earnings per share, we want that to be in the bottom half of peers roughly which today has a value of 16.8% or lower. And then, lastly, long-term debt to equity, we want that to be less than or equal to 1, so just making sure there's not too much debt on the books per unit of equity.
Moving then from there on to the sell side, we are going to sell stocks when either that quarterly earnings momentum or that quarterly earnings surprise falls below negative 8% or if that long-term debt to equity rises above 1.2. So, from here we've got our strategy built. Now, we can see how the model has done across the back test.
So, here we can see our back test is running from December 1985 to May 2020. And across that timeframe the strategy produced returns of 13.7% which is an outperformance of 6% over the benchmark which in this case is the TSX Composite. Turnover is pretty low at 41%. So, again, in our 15-stock model, you are looking at probably about 6 or 7 trades per year, so not too active in terms of managing on an ongoing basis. But again, we want to check those low-vol characteristics. We can see the performance looks pretty good compared to the benchmark but maintain still some downside protection.
So, a couple of metrics I always like to look at. Downside deviation which looks at the volatility of negative returns for the strategy had a value of 6.9% but the benchmark actually had a value of 10.3%, so a pretty big improvement for the strategy. And then, lastly, of course, I want to look at my favorite green and blue chart which tells me how the model did in both up and down markets and specifically honing in on down markets, you can see the model outperformed 80% of the time. So, even though the outperformance is pretty strong at a 6% outperformance over the TSX, in down markets this model is still doing its job, it's still protecting. So, again, just because you are doing well doesn't mean you can't have a nice big outperformance over the market, but you can still be protecting on the downside which of course cumulates into better returns.
For Morningstar, I'm Emily Halverson-Duncan.
:quality(80)/cloudfront-us-east-1.images.arcpublishing.com/morningstar/54RIEB5NTVG73FNGCTH6TGQMWU.png)
