Quant Concepts: Income and Growth at the Same Time?

CPMS's Emily Halverson-Duncan finds out that the two goals can get along

Emily Halverson-Duncan 23 October, 2020 | 1:09AM

 

 

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Emily Halverson-Duncan: Welcome to Quant Concepts, virtual office edition. As an investor, it can sometimes feel difficult to balance your investment needs and wants. A really common need for investors is income, whether it’d be for maintaining your retirement lifestyle, paying for your education or any other regular income stream. While that may be a priority, oftentimes investors will also want to meet their desire for long term growth and appreciation. These two goals are certainly not mutually exclusive. And there are different ways to do it together. In today's video, we're going to pull a model together using two different sleeves, one focused on income stocks, and the other focused on growth stocks all within the CPMS U.S. database. So let's take a look at how to build that.

So just jumping into our CPMS U.S. database here, we've got two different sleeves that we're going to explore and we're going to start first with the income sleeve. Our universe here is actually the S&P 500 so we are focusing more so on the large cap blue chip names that investors would be more familiar with. And first off, as always, we're going to go ahead and rank that universe. So some of the factors we're looking at, three-month earnings per share estimate revision. So that looks at whether or not a company's earnings per share estimates, which is driven by analysts' estimates are revised upward or downward. Stocks that have them revised more so upward would be listed higher on the list than stocks where they've been revised downward or held flat. Forward return on equity spots a growth metric, and again, we're looking for higher values there. And then return on total assets is another growth metric as well. So just looking for higher values to push companies towards the top.

On the screening side from the screens that we're looking for minimum market cap of $500 million, so the reason that’s set there is just to eliminate any really small cap stocks or less liquid stocks. We're looking for dividend yield that's in the top half of peers, and today it has a value of about 2.33% or higher. So again, making sure we've got some good income coming in. We're looking for a dividend payout ratio using expected earnings. So again, this is the ratio of a company's dividends divided by their current year earnings. And we want that to be less than or equal to 100%. So what that means is we don't want them paying out any more than what they've received in earnings in dividends to make sure that they have adequate cash flow leftover and that they're not even borrowing to pay out their dividends.

On the sell side, some of the factors we're looking at here the dividend yield, if it falls into the bottom third of peers, which today has a value of 1.34% or lower, that's a negative enough signal for us to get rid of it. And again, if that payout ratio goes above that 100% level, we're going to look at that as too much in terms of what they're paying out in dividends. And again, we would sell that stock out of the model. So that's our first sleeve that we're considering. Second one we're going to look at is on the asset growth side.

So looking at the asset growth here we can see the stock universe is the same the S&P 500 and again, that's just looking for more well known and large cap names. And some of the factors that we use first off to rank this universe of stocks. We've got quarterly earnings momentum, which is looking at the growth of earnings quarter-over-quarter for particular company. So again, higher values there would indicate the stock would be listed higher on the list. Revision of current year median estimates from 30 and 90 days ago. So it's looking at their earnings 30 days and 90 days ago respectively, compared to their earnings today and seeing whether they're revised upward or downward. If they are revised upward, and the higher upward they are, there'll be listed higher on the list versus being revised downwards would of course, push them towards the bottom of the list. And then three month and six-month price change. So pretty straightforward. We're looking at a stock's price three months ago and six months ago, respectively, compared to their price today and seeing whether or not the price has gone up or it's gone down.

On the screening side, some of the screens that we're applying here that quarterly earnings momentum, we want it to be greater than or equal to zero, meaning that their earnings are either staying flat or growing. Their latest four quarter reported earnings versus the estimate, we again want that to be greater than or equal to zero. We've got that same minimum market cap of $500 million again to get rid of those small cap and less liquid stocks. And then on the sell side, some of the sell triggers that we've got here, that quarterly earnings momentum, if it falls below that zero threshold and starts to move into the negative territory, we're going to sell the stock out of the model because that's an indication that their earnings are starting to decline.

So combining them together, we're going to go ahead and take a look at the backtest. Our backtest here is running 10 stocks in each sleeve. So 10 asset growth focused stocks and 10 income focused stocks and combined together for a total portfolio of 20 names. We're comparing that to the S&P 500 and the backtest period is April 2004 until end of August of this year.

Across that timeframe, the model returned 10.5% which was an outperformance of just under 1% over the benchmark, and turnover about 63%. Again, just a quick note on turnover, what that's looking at is how often you're trading stocks out of a model. So on 63% turnover, you could say you're placing about six trades or so per sleeve, so, six trades per each of the 10 stocks in the growth and income components. Some of the metrics that I like to look at are on the downside protection. So first off downside deviation, which is the volatility of negative returns, for the strategy, it has a value of 8.4% and for the benchmark 9.8%. So that indicates that the downside deviation and the downside protection and volatility measurements are actually better for the strategy because it has a lower number.

And then lastly, the green and blue chart here that I always like to look at. In up markets, the model outperformed 51% of the time over the benchmark, but in down markets it actually outperformed 76% of the time over and above the S&P 500. So that's a really good indication that in down markets this combined model is doing quite well and is very effective. As the markets going down and is able to better manage that volatility. So again, if you have two different types of needs that you want, there's different ways that you can look at them, but sometimes separating them out can be an effective way to still achieve both goals.

For Morningstar, I'm Emily Halverson-Duncan.

 

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Emily Halverson-Duncan  Emily is Director, CPMS Sales at Morningstar

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