Quant Concepts: U.S. Picks for a Second Wave

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Emily Halverson-Duncan: Welcome to Quant Concepts' virtual office edition. The U.S. is going through a lot of uncertainty right now, not only about COVID-19 but also with regard to the upcoming presidential election and what the future of the economy will look like. If the recent presidential debate showed us anything, it made it clear that the Democratic and Republican candidates have very opposite views on how they would respectively run the country. All that uncertainty can translate to volatile markets and possibly lead to downward movements in your investment portfolio. Today's video is going to look at a strategy focused on creating a U.S. portfolio that makes downside protection a priority. So, let's go take a look at that.

First off, we're going to go ahead and rank our universe of stocks. Note that in this particular model, our universe of stocks is the S&P 500. The factors we're going to look at to rank here – we're looking at 5 and 3-year price beta. So, what this is looking at is a measure of sensitivity comparing a stock's sensitivity to the market, or in this case, the S&P 500, and we're looking at that both across a 5-year basis and a 3-year basis. In both cases, lower values are preferred.

We're looking at the earnings per share variability relative to the industry median. So, what that's calculating is for a particular company, we're looking at the last five years of their earnings per share metrics and calculating the variability or the volatility of those metrics and then comparing that number to the industry median earnings per share variability as well. In this case, you also want a lower value, meaning that you're less volatile than the industry from an earnings per share perspective. And then, lastly, we're looking at 5-year trailing ROE, and in this case, we want higher values.

On the screening side, some of the screens that we're looking at here – we want 5-year beta to be less than or equal to 1.4. We want the normalized earnings per share variability to be in the lower third of peers, which is actually the better third of peers, and today it has a value of negative 1.88% or higher. The trailing ROE, we want that to be in the top third of peers, which today has a value of 22.29% or higher.

And then, the last two factors we're looking at – 5-year sales growth, that's an annualized metric looking at a company's sales across the last five years. We'd like that to be positive. And then, lastly, cash flow to debt. What that's looking at is a company's cash flow divided by their debt. And again, we want higher values there to make sure that they've got enough cash flow on hand per unit of debt. In this case, we want that to be in the top third of peers which has a value of 0.39 or higher as of today.

On the sell side, we're going to sell stocks if their earnings per share variability relative to the industry goes into the higher half of peers, or if their trailing ROE over the last five years goes into the lower half of peers. In addition to that, one additional metric that we've got over and above, or one additional screen that we've got above is no more than four stocks can be included per economic sector. This is just to encourage diversification and make sure you're not centred or focused solely on one or two particular sectors.

So, now that that's all done, we can go ahead and take a look at the back test. Our back test here, we're buying 15 or up to 15 stocks and we're comparing against the S&P 500. The back test timeframe is from April 2004 until August of 2020, and across that timeframe the model performed 11.2%, which is an outperformance of 1.7% over and above the S&P 500. That also had a turnover of 25%, which again that's looking at how often you're trading from a model. At 25% that looks at roughly every 1 in 4 stocks you would be flipping over in a year.

So, the 1.7%, that might look like a lower performance. But again, remember the focus here is really to protect on the downside. So, a couple of good metrics to check for that would be downside deviation as well as the percent of markets you beat when the market is going down. So, starting with downside deviation, that's looking at the volatility of negative returns, for the strategy, it has a value of 8.1% and for the benchmark, a value of 9.8%. The fact that that 8.1% is lower is a good indication that it's protecting better in down markets.

And then, of course, down here, we're looking at the percent of markets the time the model has beaten both up and down markets. In up markets, it's outperformed 43% of the time and in down markets, it's outperformed 100% of the time, which is obviously a very good indicator that this model is well set up for when markets decline, that it will do better and ideally decline less or maybe even return positively in those instances. So, if you are concerned about the economic climate and what's going to happen in the next several months, the next year, it might be worthwhile reviewing your portfolio and see if there's some changes you can make to help yourself protect your capital.

For Morningstar, I'm Emily Halverson-Duncan.