See more episodes of Quant Concepts here
Emily Halverson-Duncan: With earnings season right around the corner, many investors will be closely watching to see how the reports look for the companies they hold. Earnings can have a significant impact on the price of the stock, especially in the short term. If a company were to severely miss analysts' expectations, this can be seen as a very negative signal and can cause a sell-off as investors react to the news, or vice versa, if the stock significantly beats expectations. One way to capitalize on this season is to look for companies with a strong history of earnings growth, and surpassing expectations coupled with a risk reduction metric, such as variability of earnings per share, to help avoid companies with massive swings in earnings. So, let's take a look at how to build a model.
Today, we're going to build a Canadian earnings focused strategy. So, first off, we're going to rank the universe of Canadian stocks. Factors we're going to look at are quarterly earnings momentum, so stocks that on quarter-over-quarter are growing their earnings and you want obviously that to be a higher number. Quarterly earnings surprise looks at how much a stock either beats or misses their earnings expectations. 10-year and 5-year annualized earnings per share growth. So, again, that's an annual number of how much they're growing their earnings year-over-year. And lastly, variability of historic earnings per share, that's looking at how wide the swings are in terms of their earnings per share. So, for example, if in one quarter, they had very high earnings and the next quarter, they had extremely low earnings, that would be more likely to have a higher earnings variability.
From there, after we ranked our stocks, we're going to apply a few screens. Some of the screens we will apply – we want a positive quarterly earnings momentum and quarterly earnings surprise, just as we defined before. We're looking at a minimum market cap of stocks in the top two-thirds of peers. So, just trying to eliminate the very small cap low liquidity companies. And we're looking for a 5-year price beta to be less than or equal to 1. So, that's just to keep the sensitivity of the stocks relative to the index on a minimum. And then, lastly, we're going to sell stocks if their quarterly earnings momentum or their quarterly earnings surprise falls below minus 8% or if their price beta goes above 1.1.
Now, let's go and see how that looks. Here we're going to run our back test. Our back test is going to take place from May 1992 to August 2019. And we're going to run 15 stocks. So, let's go ahead and see how that did.
All right. So, the model returned 16.1% annualized. That's a net outperformance of 7.5% over the S&P/TSX, which is our benchmark. Turnover was a little bit on the higher side at 84%. Again, what turnover is looking at is how often you're going to be trading the stocks in our model. So, on average, you're going to be trading roughly 84% of those 15 stocks on a yearly basis. A few other metrics that I like to look at – downside deviation, which looks at the volatility of negative returns for the strategy is 7% and the benchmark is 9.6%. So, that shows that this particular model has better protection on the downside. We can also verify that by using this green and blue chart here. What we're looking at is the percent of times the model is beat in both up markets and down markets. In up markets we can see it outperformed 56% of the time and in down markets a pretty high 77%. So, clearly, focusing on that earnings expectations and the outperformance over the long term has helped quite a bit with good overall performance and good downside protection.
For Morningstar, I'm Emily Halverson-Duncan.
:quality(80)/cloudfront-us-east-1.images.arcpublishing.com/morningstar/QK4UAVKQMJACFGURDC5APNEA3U.jpg)
