In 2013, Robert Novy-Marx published The Other Side of Value: The Gross Profitability Premium, and it’s something I have found myself coming back to many times I first read it back then. It’s a great piece to read if you are interested in thinking about frameworks for how to pick a stock or the best stocks to invest in generally, but also the evolution of value investing, factor investing, and the conceptual underpinnings of return on invested capital. The last part (ROIC) is the main reason I wrote this post. Simply put, Novy-Marx’s gross profitability ratio is a simplified version of the two-part decomposition of return on invested capital below:
As such, it can be a useful and quick proxy for starting to gauge the capital productivity of a business. I’ll quickly summarize Novy-Marx’s work below in terms of the academic backdrop for it, the key takeaways, and its mechanics. Then I’ll discuss a simplified version of the screen and provide some resources for more reading on the topic.
A Brief History Of Value Factor Research Leading Up to Novy-Marx
As some readers may for the last 20-25 years academics have been performing studies to test whether or not buying (and sometimes shorting) stocks based on certain fundamental factors can create returns that are better than the market generally. This goes way back to Ben Graham’s idea that buying low price-to-book stocks (academics reverse low P/BV to high BV/P, but it’s the same thing) is a good way to beat the market. The grandfathers of these empirical studies are Fama and French, noble prize-winning academics who showed via backtesting in the early 1990’s that stocks ranking high base on three factors – size, (low) price to book, and excess return on the market have outperformed the stock market generally going all the way back to the 1930’s. Their research forms the basis of the idea that value stocks outperform the market.
The Fama-French factors were subsequently expanded to include additional factors like quality, momentum, and low volatility. Lots of other academics have published work on variations of these ideas over the years. There are billions of dollars devoted to quantitative investing strategies based on the insights from this research, not to mention “smart beta” passive strategies. One of my favorite follow-on academic studies is the stock scoring system (F-score of 0 to 9) created by Joseph Piotroski. Piotroski’s 9 ranking categories include return on assets (higher = better), whether or not there is positive free cash flow (Yes is better), financial leverage level (lower is better), change in gross margin (an improving % Y/Y is better), etc. The idea is to own stocks with a high cumulative score on these 9 factors, as this group has outperformed the market over time and is potentially likely to do so in the future. The original Fama & French studies and the long line of research work by others that followed it (including Piotroski) are the backdrop for Novy-Marx’s piece.
The Main Takeaways
To summarize Novy-Mark’s finding, I am going to borrow from the actual text of The Other Side of Value: The Gross Profitability Premium (including the abstract at the beginning) to make sure I very accurately convey the key takeaways but also add some of my own comments in brackets:
- Profitable firms generate significantly higher returns than unprofitable firms, despite having significantly higher valuation ratios [even though firms that are highly profitable as measured by gross profit/assets tend to trade at higher valuations than those that don’t, they still generate significantly better returns. Again, hard for low-multiple investors to accept].
- Controlling for profitability also dramatically increases the performance of value strategies, especially among the largest, most liquid stocks [The numbers show that gross profitability, which is essentially a growth strategy, can be a useful hedge for P/BV (value) strategies, suggesting they might be used well together, which is kind of counterintuitive at first.]
- Profitability, measured by gross profits-to-assets, has roughly the same power as book-to-market predicting the cross-section of average returns [Novy Marx is saying that this screen is as good or better at beating the market as the classic value, P/BV screens backtested by Fama & French. This is difficult for a lot of diehard value investors to swallow.]
All of the stats used to support these assertions can be found in the tables that are at the back of the version of the study that I have linked to here, rather than in the body of the piece. Let’s look at some of the mechanics of Novy-Marx’s approach:
Why Use Gross Profits?
Novy-Marx decided used gross profit as a rough measure of profitability, rather than NOPAT (see ROIC breakdown above), earnings or cash flow. Why? He explains it as follows:
Gross profits is the cleanest accounting measure of true economic profitability. The farther down the income statement one goes, the more polluted profitability measures become, and the less related they are to true economic profitability.
For example, a firm that has both lower production costs and higher sales than its competitors is unambiguously more profitable. Even so, it can easily have lower earnings than its competitors. If the firm is quickly increasing its sales through aggressive advertising, or commissions to its sales force, these actions can, even if optimal, reduce its bottom line income below that of its less profitable competitors.
Similarly, if the firm spends on research and development to further increase its production advantage, or invests in organizational capital that will help it maintain its competitive advantage, these actions result in lower current earnings.
Moreover, capital expenditures that directly increase the scale of the firm’s operations further reduce its free cash flows relative to its competitors. These facts suggest constructing the empirical proxy for productivity using gross profits.
So, using gross profit saves us from accrual and non-recurring item noise that can occur between it and profitability measures that are further down the income statement. It also means that when companies are investing via the income statement – i.e., the expense items such as R&D and S&M are more like intangible investments in growth rather than operating expenses, companies are not overlooked as hopelessly low/no-profit enterprises. I have discussed this in other posts, such as Recasting Expenses As Intangible Assets For ROIC.
Incidentally, gross margins are very important to tech investors – subscription/SaaS business model in particular – because they indicate the underlying operating leverage available in the business and foreshadow what profit margins could look like once the business reaches “steady state,” or a time when it is investing less heavily in growth via income statement expenses. Hypergrowth investors can be very demanding for these kinds of businesses, often demanding gross margins of 85%+. Of course, this leads to a lot of hokus pokus accounting by tech companies trying to strip expenses from COGS to get those gross margins up.
Why Scale Gross Profits To Assets?
Lots of researchers and investors have used gross profits as a factor before, including looking at the change in gross margin over time (improving?), the margin rate in absolute or relative terms (high?), etc. But from what I can tell no one scaled it specifically to investment to achieve that profit, especially by using assets rather than market or book equity. Here is Novy-Marx’s reasoning:
Scaling by a book-based measure, instead of a market-based measure, avoids hopelessly conflating the productivity proxy with book-to-market. I scale gross profits by book assets, not book equity, because gross profits are an asset level measure of earnings. They are not reduced by interest payments, and are thus independent of leverage.
In other words, the scaling makes sure that capital productivity is captured by the ratio, without regard to financial leverage or how the stock market is valuing the business. This is important for me because over time I have learned that thinking about capital productivity before valuation is a better way to find investment ideas, and this ratio does that, or at least is a pretty good starting point for doing that. In formula terms, the scaling of the gross profit/assets ratio is basically capturing the right side of the ROIC breakdown formula:
Novy-Marx breaks down the gross margin this way, which is just a version of the ROIC formula I show above, albeit with the orders of the margin and asset turnover ratios reversed:
And here is his explanation of how to think about it, in which he sprinkles in a little bit of competitive advantage economic theory to explain what’s driving the financial performance captured by the ratio:
Gross profitability is also driven by two dimensions, asset turnover and gross margins, a decomposition known in the accounting literature as the “Du Pont model.” Asset turnover, which quantifies the ability of assets to “generate” sales, is often regarded as a measure of
efficiency. Gross margins, which quantifies how much of each dollar of sales goes to the firm, is a measure of profitability.
It relates directly, in standard oligopoly models, to firms’ market power. Asset turnover and gross margins are generally negatively related. A firm can increase sales, and thus asset turnover, by lowering prices, but lower prices reduce gross margins. Conversely, a firm can increase gross margins by increasing prices, but this generally reduces sales, and thus asset turnover.
So, gross profit/total assets is a good way to get a (very) quick and dirty sense of the quality of a business from its financial statements.
Running The Screen
To be clear, I am a bottom-up, fundamental stock investor and I am not interested in screens such as Novy-Marks’ because I want to use them as the basis of some kind of automated trading strategy. Even if I was interested in this, chances are someone like AQR is going to do it far better than me, and it would probably be better to just give them my money. But the way Novy-Marks’ work can be useful to me and you is as a starting point for finding new ideas, and that’s why I run his screen every few months. Below is a simple example of one in which I sorted gross profits/total assets from high to low for US companies with market caps of $2B – $10B. I cut the list off below 50% gross profit/total assets:
Here’s how I would use this screen: I would naturally start with the highest gross profit/total assets percentages at the top, and quickly look at the data points I included for each stock – industry, market cap, and then basic ROE and ROIC numbers for each of those names. As has been discussed in prior posts like ROIC: Operating vs. Financing Approach, there can be a lot of arbitrariness in how capital return metrics are calculated, so I wouldn’t rely too much on these numbers – they are just ballparks. For example, the ROIC number in this screen is from Bloomberg, which uses the financing approach for ROIC. Just use the screen results as a launching off point for ideas.
For example, I might be drawn to #2 on the list, Rober Half International. After seeing it rank high on gross profitability, I would be drawen to the high ROE, ROIC, and low P/E. I would take a quick look at the 2022 annual report, and a recent Robert Half investor presentation to try to understand the business to contextualize the capital productivity numbers I am seeing.
A mistake I think people sometimes make while screening is they pass over stocks they worked on years ago or knew fairly well at some point in the past. I might do this with Robert Half. But the fact is that companies and industries are constantly changing, and narrowing your search by doing this freezes the companies in time. Mistake! Take another look.
Another advantage of making a habit of perusing screens every few weeks is it keeps you up to date on capital productivity and valuations broadly; failing to do this can leave you too locked into the companies you own making you lose perspective on how they perform relatively to who they compete with for capital. If you don’t know this, you won’t know when there are other opportunities to make better risk-adjusted returns out there. This is an important discipline to have.
All in all, I strongly recommend reading Novy-Marx’s piece – even if you aren’t too interested in stock screening. I would also look at the list of references in the footnotes at the end for more related studies to read. I have spent lots of time over the years looking at Piotroski and Novy-Marx screen results, and I know it’s not for everyone! But understanding the research is pretty convincing support for the idea that higher quality businesses, as measured by ROIC, are more likely to outperform the market, even though they are more highly valued by the market at time 0 (i.e., when you buy them) than low multiple stocks that don’t screen as well on capital productivity. That’s good to know, and it’s useful to keep in mind for everything you do in selecting stocks, I think.
Additional Resources
Here are some additional links for things to read if you are intersted in this material:
A 2021 podcast interview with Novy-Marx – it’s a great way to see him discuss his own work and broader thinking on investing.
A CFA Institute article (2013) summarizing this research piece.
A 2013 article on AAII.com entitled Screening for Quality Growth, Value & Momentum that discusses The Other Side of Value: The Gross Profitability Premium and how to run the screen used in the piece.
A CFA Institute article (2022) entitled Derisking The Profitability Factor in which the author proposes to enhance the Novy-Marx screen by adding what it describes as an “additional quality dimension” called “conservatism.” Conservatism adds rankings for cap ex growth, financial leverage, and cash holdings. The article provides some interesting statistical backup for the efficacy of this modification.
A somewhat random link to a piece authored by a money management firm (2019) that I found on the internet. It argues against the usefulness of the gross profitability factor, calling it a trap: “It appears that enough investors now view Gross Profitability as a viable proxy to future firm profitability that it has temporarily, and likely in a very short-sighted manner, replaced a more robust approach to valuation in stock selection. Ironically this metric, which claims to be the “other side of value”, does not have a link to firm value at all and should not be used as a stock selection criteria on a stand-alone basis.” This piece also does a good job of summarizing the basic takeaways of The Other Side of Value: The Gross Profitability Premium.