Quant Concepts: Healthy balance sheets

What to look for when building a basket of strong stocks with CPMS's Emily Halverson-Duncan

Emily Halverson-Duncan 15 May, 2020 | 1:39AM
Facebook Twitter LinkedIn



See more episodes of Quant Concepts here

Emily Halverson-Duncan: Welcome to Quant Concepts' virtual office edition. It can be difficult to determine whether a company is a good investment during periods of volatility such as what we've experienced in Q1 this year. With a number of analysts revising company earnings estimates downward, how can you tell if a stock is worth buying or whether you should avoid it? One way to assess a company's health is to use their balance sheet. Recall that a balance sheet is a statement outlining a company's assets, liabilities and shareholders' equity. We can use the information in the statement to help assess where a company currently stands and whether or not they are well-equipped to tolerate unprecedented conditions such as those due to COVID-19.

Today's strategy is going to look for companies with strong balance sheets in the CPMS U.S. universe. So, let's take a look at how to build that.

So, first off, as always, we're going to go through and rank our universe of stocks. Again, we are doing the U.S. CPMS universe here and that has 2,090 names. So, the factors that we're going to look at for ranking – first off, we've got cash flow to debt. What that's looking at is how much cash flow a company has on hand per unit of debt and we want a higher value for that. Long-term debt to equity looks at a company's long-term debt per unit of equity. We want a lower value of that to make sure they don't have too much debt on hand. Their trailing return on equity is a profitability metric. We want to see a higher value for that. And lastly, five-year beta, which is a measure of sensitivity of a stock, we want to see a lower value.

In terms of the screens that we've got in place – the latest cash flow to debt, we want that to be in the top half of peers. So, that has a value of 0.27 times or higher. Long-term debt to equity, we want that to be less than or equal to 1.1. What that indicates is that you don't have too much more debt on hand than you do equity, allowing it to go a little bit higher, maybe assuming that they need debt to further finance additional projects, so that's okay, but not too much debt over that. Latest debt to total assets, we want that to be in the bottom half of peers which is 0.38 and below as of today. Market cap, we want to be in the top half of peers just to screen out any small-cap stocks and today, that has a value of 1.27 or higher.

On the sell side, we're going to sell stocks if that cash flow to debt metric falls below the bottom third of peers or falls into the bottom third of peers which has a value of 0.14 or below. And lastly, if long-term debt to equity rises above 1.3, so we bought at 1.1, allowed that to raise a little bit, but then once it passes 1.3, we would sell the stock.

Of course, we want to see how this model does across the long-term. So, if we take a look at the back test. Here, our back test, we're buying 15 stocks and comparing to the S&P 500. Timeframe across that we built it is April 2004 until April 2020. Performance across that timeframe was 12.9%, which represented an outperformance of 4.5% over and above the S&P 500. And the turnover there was actually only 14%. So, recall that turnover is how often you are trading. At 14% that's quite low, probably only a few trades a year on average.

So, my favourite metrics to look at, downside deviation. So, the strategy downside deviation was 9.6 versus the benchmark at 9.9. Recall that downside deviation is the volatility of negative returns. So, having a lower value is better. And then, of course, my favorite green and blue chart here, this looks at how often the model is outperforming in both up and down markets. For up markets, the model is outperforming 54% of the time. And in down markets it's actually outperforming 71% of the time, indicating that companies with a good balance sheet actually do well in down markets when there's more volatility, again like what we've seen this year.

Let's test that a little bit further and just see how the model did year-to-date. If I take a look here, I can compare. So, the benchmark, the S&P 500 as of end of April was down 9.3%. But this particular model was down only 3.2%. So, you can see a roughly 6% outperformance year-to-date. And again, that was looking at companies with strong balance sheets. So, that might be another thing to consider when you are picking stocks for your portfolio.

For Morningstar, I'm Emily Halverson-Duncan.

Empower your investment selection

Sign up for the latest insights in your inbox here

Facebook Twitter LinkedIn

About Author

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

© Copyright 2024 Morningstar, Inc. All rights reserved.

Terms of Use        Privacy Policy       Disclosures        Accessibility