Margins Theorem Summary

by Louis Corrigan (TMF [email protected])

Atlanta, GA. (Oct. 6, 1998) -- Today, I'm presenting an overview of the margins theorem I've been discussing for the last few weeks, including what we've learned about it and how we might deploy it.

To go back to the basics for a moment, margins here mean profit margins, and there are generally three types of margins that could interest us. First is gross margins, or gross profit (revenues minus cost of goods sold) divided by net revenues. Second is operating margins, or operating profit (gross profit minus operating expenses) divided by net revenues. Last, we have net margins, or net profit (operating profit minus other adjustments such as interest expense and taxes) divided by net revenues. All of this information can be gleaned from a company's quarterly income statement, which appears in press releases announcing earnings and, later, in the company's quarterly 10-Q or annual 10-K, which is filed electronically with the SEC.

Each margins line tells you something different about the business, and fundamental analysts pay attention to trends in all three. For example, gross margins can reflect changes in materials costs or in manufacturing efficiency or utilization. Changes in marketing or advertising expenses or research and development spending show up in the operating margins. Net margins reflect all of the above but may also be affected by unusual one-time gains, a jump in interest expenses, or changes in the tax rate.

Net margins reflect the "bottom line" profits of the company, but of even greater interest to investors is the amount of profits per share. Earnings per share (EPS) can grow faster than net profits if a company is retiring shares of its stock through buybacks. Since that's generally a positive sign, the Fool's margins screens focus on EPS as a proxy for net margins. Specifically, the rising margins screen captures companies that have seen sales increase 15% or more versus the year-ago period and that also see EPS increasing faster than sales. For our purposes, EPS growth in excess of sales growth equals rising margins.

The theorem I proposed was straightforward: Consumer-oriented stocks should be sold (or avoided) when their margins fall, and they should be bought (or held) when their margins rise. I'm most interested in consumer-oriented companies because I think they're the easiest for individual investors to really understand, and I don't want to invest in something I don't understand.

As we've seen, this theorem would have served you extremely well in finding and directing you to hold Dell <% if gsSubBrand = "aolsnapshot" then Response.Write("(Nasdaq: DELL)") else Response.Write("(Nasdaq: DELL)") end if %>, Best Buy <% if gsSubBrand = "aolsnapshot" then Response.Write("(Nasdaq: BBY)") else Response.Write("(Nasdaq: BBY)") end if %>, and the Gap <% if gsSubBrand = "aolsnapshot" then Response.Write("(NYSE: GPS)") else Response.Write("(NYSE: GPS)") end if %>, the three best-performing stocks (as of my August 26 study date) among those in the mechanical model portfolios. Indeed, from what I can determine, the theorem would have given a "buy" signal on these winners long before they appeared in the models. That's a distinct positive. Of course, without presenting you with a universe of stocks from which these would have been selected, I can't claim more than that; the theorem might have picked a bunch of losers, too (more on this soon).

Yet, to deliver these results, we found it necessary to amend our screen to pick up companies with any increase in sales. The 15% threshold was just too high for Best Buy to jump at the early stages of its amazing turnaround. That was partly because the turnaround in profits came directly from a deliberate slowdown in its store expansion. A margins theorem that missed more than the first few months of Best Buy's revitalization wouldn't be worth much. Then again, Sharon (TMF Rockie) has been compiling our margins data manually, and lowering the sales threshold would make her job impossible. So that's a problem we'll need to resolve at some point.

Finding great investments as early as possible is a tremendous accomplishment. While the margins screen won't detect every great investment, it at least appears to do pretty well at finding some of them. On the other hand, its capacity for detecting losers seems far more mixed. We saw that the margins theorem would have kept you from losing serious money on ICN Pharmaceuticals <% if gsSubBrand = "aolsnapshot" then Response.Write("(NYSE: ICN)") else Response.Write("(NYSE: ICN)") end if %> and Coca-Cola Enterprises <% if gsSubBrand = "aolsnapshot" then Response.Write("(NYSE: CCE)") else Response.Write("(NYSE: CCE)") end if %>, though cursory research into ICN should have convinced you to avoid the stock for other reasons.

With Whole Foods Market <% if gsSubBrand = "aolsnapshot" then Response.Write("(Nasdaq: WFMI)") else Response.Write("(Nasdaq: WFMI)") end if %>, the margins theorem would have had you hold through the recent downdraft. Yet the theorem would have gotten you into the stock much earlier than the models. So instead of a sizeable loss, you'd still be sitting on a very nice gain.

However, the theorem proves completely useless when dealing with more cyclical businesses, including high-tech companies like Iomega <% if gsSubBrand = "aolsnapshot" then Response.Write("(NYSE: IOM)") else Response.Write("(NYSE: IOM)") end if %>, whose results depend on product cycles rather than broader economic cycles. The margins theorem proves so incapable of dealing with these companies, one could probably use margins as a contrary indicator. That is, as soon as the margins turn up, it may be time to start worrying about the business, fearful that the stock may begin discounting the eventual cyclical downturn.

What should we do with the margins theorem?

I hope that some of you will think about at least looking at margins as one of several ways of doing a more nuts-and-bolts fundamentals check on the stocks that appear in the models. Purists will say that's contrary to the whole rationale behind the models, which is to stick to a time-tested approach and avoid injecting any subjective judgments into the process. To which I say, "True." At this stage, I have nothing more to offer the purist.

Ultimately, though, the theorem seems to offer a decent starting point for constructing a new type of model, or what I would prefer to call a screen. As many of you have pointed out, showing how the theorem might have worked on some of the model stock picks isn't the same thing as showing whether the theorem really works, much less whether it works over time.

Both points are absolutely right. To pursue this further, then, I would need to refine the criteria, put together a universe of stocks to which the theorem could be applied, and, as a start, begin to offer a real-time test. (Though I understand the desire for backtesting, I think it would be extremely difficult to piece together accurate historical financial information to manage the task.)

Looking at those cases where the theorem clearly worked, it may make sense to limit the stock universe for this experiment to companies with at least $1 billion in annual sales. (The margins screen itself, though, can definitely point to terrific small-cap growth prospects. Recall the American Woodmark <% if gsSubBrand = "aolsnapshot" then Response.Write("(Nasdaq: AMWD)") else Response.Write("(Nasdaq: AMWD)") end if %> example that I began with.)

But what really qualifies as "consumer-oriented?" Are there excessive industry risks in narrowing the universe to such companies? How do we screen out companies like Iomega that fall under the product cycle risk category? What other qualifications will we need to make? Does the effort seem likely to be worth the trouble?

I'm going to spend some time working up a list of the stocks that might qualify for a margins theorem screen and thinking through some of these issues. Any feedback would be appreciated. In the meantime, I think I'll probably divide my columns between applying my margins theorem to stocks that appear in the updated models and using the Fool margins screen to hunt for the next American Woodmark.

Check out the latest file updates for the Workshop:
New Rankings | 1998 Returns | New Database

What Happened to Robert Sheard?