See more episodes of Quant Concepts here
Emily Halverson-Duncan: Welcome to Quant Concepts' virtual office edition. In a previous video, we explored how value stocks tend to be some of the best performers following a market correction. Remember that value stocks are stocks that are currently trading below their expected worth tend to get hit hard during periods of volatility. Afterward, however, they could be an excellent place to look for ideas as their recovery tends to be strong. Today, I'm going to repeat my previous study which looked for Canadian value stocks but instead focus on the U.S. universe. So, let's take a look at how to build that.
First off, as always, we are going to go through and rank our universe of stocks which today holds 286 U.S. names. In that ranking step some of the factors that we're going to look at – price to trailing earnings and latest trailing free cash flow. Price to trailing earnings is a value metrics. So, we want to see that on the lower side whereas a latest trailing free cash flow is a profitability metric. So, we want to see more cash flow on hand. Lastly, price to trailing cash flow and price to book value, those are two additional value metrics and again, we want to see those on the lower side.
On the screening end, once we've gone through and ranked our universe, we're going to go ahead and screen out stocks that we don't want to own. So, our first screen here is based on market cap and this is to get us more in that mid to large-cap space. And the screen here we've got is to be in the top third of peers which today has a value of about $5.9 billion or higher in the U.S. Our price to trailing earnings, we want that to be in the bottom half of peers which today has a value of 22.27 times or below. Few other screens that we've got – long-term debt to equity, we are capping that at 1.1, and the reason for the cap there is just to encourage companies that don't have too much debt on hand. Trailing free cash flow, we want that to be positive, again, encouraging a good free cash flow number for the companies. And lastly, return on equity, which is a profitability metric, we want that to be in the top third of peers which today has a value of 16.77% or higher.
Once we've applied those, we are going to go ahead and set our sell rules which in this case have to do with price to trailing earnings again. Once that falls into the bottom third of peers which is actually the highest third of numbers, we would sell the stock from the model. That value today is about 27 times or higher. Long-term debt to equity, we bought if it was below 1.1 and we're going to sell if it rises above 1.3. And then, lastly, if their trailing free cash flow is negative on their books, we are going to get rid of the stock from the model.
So, now, we've got all our rules in place. We're going to go ahead and see how that model did across the long-term in our back test. So, let's take a look here. Our back test held 15 stocks and ran from a period of 2004 until 2020, so April 2004 until April 2020. Across that timeframe the back test returned 10.6% annualized which is an outperformance of 2.1% over the benchmark. And pretty low turnover at about 26%. Remember turnover is looking at how often you are trading stocks from the model. So, at 26% you are trading probably about 4 or 5 stocks on average a year.
If we look to some of the metrics that I always like to look at – downside deviation, the strategy has a downside deviation of 12.6% compared to the benchmark at 9.9%. So, recall that this is looking at the volatility of negative returns. So, having a higher value than the benchmark indicates that in negative markets or in down markets, the volatility of the strategy is actually higher. And then, of course, my favourite green and blue chart down here, how did the model do in both up and down markets. So, in up markets, the model outperformed 59% of the time whereas in down markets, it only outperformed 53% of the time. So, all this goes to show while it obviously did well over the long-term, having that value structure clearly had an impact in down markets and more turbulent markets but ideally coming out of there, there could be some good ideas here as a place to park your money once markets have started to recover.
For Morningstar, I'm Emily Halverson-Duncan.
:quality(80)/cloudfront-us-east-1.images.arcpublishing.com/morningstar/5WSHPTEQ6BADZPVPXVVDYIKL5M.png)
:quality(80)/cloudfront-us-east-1.images.arcpublishing.com/morningstar/Q3KIND5VXRCNHHH6JQHCCYBSSA.png)
