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Emily Halverson-Duncan: Welcome to Quant Concepts' virtual office edition. Value investing has been practiced for many years. Famed investors such as Benjamin Graham, Peter Lynch and Warren Buffett have shown us how profitable value strategies can be. However, with thousands of mutual funds and ETF options available, it can be overwhelming for investors to find a value strategy that differentiates from the norm. What we're going to do today is create a value strategy that ignores the well-known blue chip companies many investors are accustomed to seeing in their portfolio. Instead, we'll build a strategy focused solely on small cap U.S. stocks that tend to have a smaller number of analysts following them. So, let's take a look at how to build that.
Logging into our U.S. CPMS here, first off, we're going to rank our universe of stocks which today holds 2,084 names. And the factors we're going to look at for the ranking are very simple. We're going to look at a trailing price to earnings metric which is of course the value metric and we want to see a lower number for that particular factor. And then, we're going to look at latest trailing free cash flow which is a measure of how much cash a company has available after expenditures and in this scenario we want a higher value for that particular factor.
In terms of screens that we're going to apply, we want to have a market cap that's actually in the bottom half of peers. This is where it's a bit more unique compared to other strategies that we've done. Typically, we're trying to get rid of the smaller companies. But in this scenario, we're actually trying to get rid of the larger and large mid-cap companies. So, we're going to put the smaller subset. So, the cap here today is at $6.3 billion or below for this particular model. Price to trailing earnings, we want to have that in the bottom half of peers as well which is a value of 17.52 times or below, again, trying to screen out those overvalued names. We're also adding a couple of screens here – long-term debt to equity, we want it to be less than or equal to 1.1 just to make sure companies don't have too much debt on their books. And then, lastly, that latest trailing free cash flow, we want that to be in the top third of peers.
On the sell side, we're going to go ahead and sell stocks if that long-term debt to equity rises above 1.3 or if that trailing free cash flow falls in the bottom half of peers. So, once we've gone ahead and applied all of those screens and set up the rules, we're going to go ahead and run the back test and take a look at how it's done.
So, just jumping into this here, there are 10 stocks being run in this back test and the timeframe runs from April 2004 until end of June 2020. The benchmark that we're using here is the S&P 500. And if we look at the results, the results are 12.6% annualized on the model and that's an outperformance of 6.6% over the benchmark. Turnover is 39% which again is pretty on the lower side here. We're looking at how often the model is actually trading stocks when we're looking at turnover. So, at 39% you're probably doing about four trades a year on average.
Some of the metrics I always like to look at – how did it do in down markets. So, if we look at downside deviation, this strategy has as downside deviation of 13.7% versus the benchmark of 13.9%, so pretty close in terms of how the volatility of negative returns looks. And then, of course, the green and blue chart that I always like to look at. In up markets, the strategy outperformed 52% of the time, so a little over half, and in down markets, outperformed 70% of the time. So, definitely, strong in terms of outperformance here, and again, this is going to source names that you're not as accustomed to seeing in your portfolio because they will smaller, you'll be less familiar with seeing them in the news or using them in your day-to-day. But there can still be a lot of great opportunities there to consider as well.
For Morningstar, I'm Emily Halverson-Duncan.
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