A little electricity always blows in the financial air when the Federal Reserve Board meets to determine interest rates. This is the day eight times a year when the investment community learns the destiny of the federal funds rate. Technically, this is the short-term interest rate at which the Fed lends to banks, but in a broader sense, it is the rate on which so many real-world rates are based—business loans, adjustable-rate mortgages, and on down the line. Changes to the fed funds rate also indicate where the Federal Reserve believes the inflation rate is headed and what it intends to do about it.

In theory, when the Fed raises interest rates, it believes inflation needs to be cordoned off. Meanwhile, interest-rate cuts theoretically signal a noninflationary, or perhaps deflationary, environment. I say “theoretically” because not all the people who are appointed to the Federal Reserve are the same or view the world the same way; Fed policy, right or wrong, depends on the personalities guiding the operations. It is reasonable to assume that the Fed always has its eye on inflation and, thus, the value of the dollar. But Feds notoriously watch all sorts of economic indicators, some of which have nothing to do with inflation. This adds to the “electricity”—and sometimes the heartburn—that surrounds every Fed meeting.

In the early 1980s, however, I was feeling increasingly sure about the direction of Fed policy. I remember that a lot of writers, including myself, were watching interest rates very closely—and not just the Fed’s stated policy rate, but the rates of securities selling in the market. During 1980 and 1981, many of us argued that interest rates on low-risk, long-maturity securities (such as ten-year Treasury bonds) were lofty relative to inflation and that the resulting yields of the securities were near all-time highs. Based on historical experience, I argued that such high real yields could not persist and that the gap between inflation and interest rates also could be expected to narrow. (You need not worry here about what economists see when they look at the “gap” between inflation and interest rates. The early moral of the story is to keep your eyes open.) At the time, the question was, how would the gap close? By way of interest rates falling, or inflation rising?

To determine this, I kept my eyes pinned to the Fed.

Paul Volcker took over the chairmanship of the Federal Reserve in mid-1979 with the stench of that decade’s hyperinflation still thick in the air. Volcker had a couple of false starts, but in the early 1980s, I fell under the impression that the Fed was changing its operating procedures—and for the better. (I note here that the Fed does not necessarily announce what these procedures are; it is usually up to economists to discern them, by way of experience and a little mind-reading.) My indicators suggested the Fed was moving toward a price rule, which, in the simplest terms, means it would let real-world prices indicate the direction of inflation and adjust the money supply accordingly. If prices were going up, it would raise interest rates (which, in effect, pulls excess inflationary money out of the system). If prices were going down, it would lower interest rates (returning cash to the economy).

Volcker seemed to have begun the price-rule attack in earnest in October 1979 when he began to significantly hike the fed funds interest rate. By reading the newspapers, I reinforced my belief that the Fed was indeed on a new policy course: When President Ronald Reagan took office in 1980, he appointed a string of price-rule advocates to the Fed board—Martha Seger, Manuel Johnson, Wayne Angell, and Robert Heller among them. These were still inflationary times, so I knew the Fed was going to continue raising interest rates—and it did, fiercely: The increase in the underlying inflation rate during the 1970s led to a 10 percent federal funds rate by the end of 1978. However, as Paul Volker changed gears, the fed funds rate rose to 15.5 percent by October 1979 and 20 percent by March 1980. After a brief decline that year, the rate touched 20 percent again in December 1980.

And the high rates did their work on inflation. By the end of 1981, when the fed funds rate dropped back to 12 percent, inflation had suffered a severe blow, and the economy was poised to recover. For the decade ahead, I argued that both the U.S. inflation rate and the Fed’s target interest rates would decline even further. With the price rule working its magic, I knew that inflation would at last be tamed and that interest rates would come down.

As I mentioned, any investor benefits from an understanding of Federal Reserve policy, simply due to the gravity of the policy results. High inflation, in particular, can destroy the economic good times, while low inflation often equates with smooth economic sailing. But this particular Fed interlude leads us to a fundamental strategy for industry selection: In looking backward, we can sometimes know just how to look forward.

If you read the newspapers in the early 1980s and understood a little bit about Federal Reserve policymaking, a future economic shock became knowable: Inflation and interest rates were both headed down. But how to take advantage of this insight? Well, my first inclination was to look back a few years and isolate periods of rising and falling interest rates. I show these results in Table 5.1—information that, on its own, would not have done any investor much good.^[1]

However, in these interest-rate periods, I had a baseline for comparison. Which industries, I wondered, performed the best, or the worst, in each of these timeframes? I show these results in Table 5.2.

My methodology here was simple: The industries that outperformed the market during periods of declining interest rates, and the ones that underperformed the market during periods of rising interest rates, were defined as those that would benefit from falling interest rates.^[2] Similarly, the outperformers during periods of rising interest rates and the underperformers during periods of falling interest rates became the industries that would most benefit from rising interest rates. Just as I might look for the high-beta sensitivity of stocks or industries, I was now looking for interest-rate sensitivity. My elasticity rationale was, and is, the same: The most sensitive stocks in relation to any economic shock can be said to have high-betas in relation to that shock. And high beta, as we know, pulls a stock disproportionately upward in the good times and disproportionately downward during the bad.

The potential upside of such a historical strategy is obvious: In the Fed example, the industries that had benefited from falling interest rates in the past gained an average of 238.97 percent in the 1983–1992 period. If you did your historical homework and invested in the industries projected to do the best in this environment, you would have beaten the industry average by 58.06 percentage points (238.97 – 180.91 = 58.06). In other words, if you “caught” those sectors with the greatest sensitivity or (highest betas) to falling interest rates, you would have eclipsed the average industry gain by a noteworthy amount. Avoiding the groups that benefited from rising interest rates also would have added to your strategy performance because this group gained a mere 32.69 percent for the period.

This is how one properly looks backward to properly invest forward. Here’s the historical industry-selection process, step by step:

This method isn’t perfect. In the case of the interest-rate shock, you might have noticed that a few losers mingled with the winners, while some industries “won” by much greater margins than others. Still, had you selected all the historical industry winners, you would have beaten the industry average decisively during the period.

And beating the average is what above-average performance is all about.

Over the years, I have examined the levels of employment and profitability within separate industries when economic shocks occur. From this study, I am able to pull two general rules for identifying whether an industry will behave in an elastic or inelastic manner following the arrival of an economic shock.

First, inelastic industries respond to positive economic shocks with below-average employment increases and above-average profit gains (example: the airlines industry preregulation). Second, elastic industries respond to positive economic shocks with above-average employment increases and below-average profit gains (example: the airlines industry post-deregulation).

Common sense is your guide here.

In the first case, no increase in employment takes place while profits go up. Thus, higher prices must be meeting demand, rather than an increase of supply meeting demand. This is classic inelastic. You want to own these stocks (and/or industries) when profits climb and employment gains are below average, and avoid them in the converse situation.

In the second case, an increase in employment takes place, although profits come in slightly below or slightly above average. This indicates strong competition and that demand is being met by greater supply at lower prices. This is classic elastic. Sometimes you’ll want to own these stocks; other times not. (We discuss why shortly, in the next section.)

If you can understand the general rules for selecting industries using historical data and/or jobs-and-profitability statistics, I’d say you are well on your way to becoming a certified inelasticity catcher—or avoider. Whatever you want to call these stocks—inelastic, high-beta, or sensitive—you want to own them when they are the beneficiaries of positive economic events and avoid them when shocks turn negative.

As for selecting stocks within elastic industries, your investigative skills might need to mature, although the payoff can be worth it.

In the last chapter, I stated that an industry is more like a box of assorted rubber bands than a box of chocolates. Here’s a closer look at why.

The ultimate burden of any given macroeconomic shock finally comes to rest on an industry’s supply-and-demand elasticities. Inelastic companies face rigidities that restrict their ability to adjust production during periods of shifting demand. These rigidities are central to an active investment strategy because they determine which industries will experience above- or below-average rates of return when the demand for their products rises or falls.

Critically, however, there’s nothing static or constant about this approach: Sometimes an inelastic industry goes elastic, as the airlines example showed, starkly changing how it can adjust to shifts in demand. Inelastic and elastic components also exist within the same industries, company to company, although some elastic industries or companies have been able to generate what we might call unique inelasticity, giving them a decided competitive advantage.

Think of how the computer industry developed. When personal computers first arrived, they were high-priced and accessible by only a few. However, as the technology advanced and competition in the category increased, prices came down, making PCs available to the masses. The market expanded rapidly, and computers quickly became standardized products in offices and homes—which is another way of saying that computer manufacturing turned elastic. When the benefits of this technology became known to consumers, increased competition for those consumers forced a price reduction. This also meant that one PC would soon be about as good as another PC at the same price.

So what we have is a classic example of a once unique product turning into a commodity, which here can be defined as any standard bulk item that can be freely bought and sold.

That’s the hardware story. But the PC explosion has had a well-documented “spillover” effect: What company or industry has not benefited from the computer revolution? PCs have spawned several tributary industries, such as software. But unlike keyboards or monitors or hard drives, with one about as good as another at a similar price, PC software is task-specific. “Costs” also are associated with learning a particular program—for instance, time—and copyrights have restricted the entry of clones to the category. In short, unique factors in both supply (copyrights) and demand (such as the time invested in learning programs) have made the PC software industry less elastic than the PC hardware industry.

The art of industry selection often requires that an investor follow innovation from the source to the extremities. To stick with this example, the computer revolution has had far-reaching implications that have shifted elasticities within many industries. For instance, just-in-time inventory—the technique by which factories produce certain goods right when they are needed and only in the amounts needed—has been greatly enhanced by computerization, which, in turn, has greatly reduced the cost of doing business industry-wide. This is an elastic event from the point of view of all manufacturers, bettering their just-in-time capabilities thanks to the computer. However, high-tech developments applied to the production process also can give rise to economies of scale that make it difficult for small competitors to enter a category. Witness Wal-Mart: In the sense that it dissolved much of its competition in becoming one of the most efficient low-cost operators in the history of chain-store retail, it can be considered uniquely inelastic.

The investor challenge becomes to separate the elastic commodities (the standard “bulk” goods, such as PCs or TVs) from the unique inelastic factors company to company within industries (i.e., software, MP3 players, etc). The elastic/inelastic rules of engagement from Chapter 4, “Catch Elasticity If You Can: An Introduction to Industry Behavior,” still apply—in particular, buy or hold those high-beta inelastic companies in periods of high demand. But looking company to company, we now have a nuance:

Companies usually can be classified as commodities for a good reason: They do it just as well as most everyone else. Within industries, the true gems are those businesses that have been able to become uniquely inelastic. Such companies often energize a portfolio.

At some point, all investors must decide who they really are. Are they low-risk, long-run passive investors? Are they higher-risk active players? Are they somewhere in the middle? Putting aside my strong position that an investor can be all of these at different times, or at the same time, each of these strategies can be geared to capture as much high-beta as possible.

Across each of these industry-selection strategies, I note that my message remains the same: Elasticity-minded investors are empowered investors—people who are adept at selecting the assets that will earn them superior portfolio returns in the event of any economic shock. Indeed, if you take anything away from this book, I want it to be an elasticity mindset. This is not a static world. The winds of change never stop swirling: a light breeze of change here, a gale-force transformation there. Shocks come and go, and businesses change with them.

To track all this, you need to keep your eyes and ears open—although not a shock goes by that the media doesn’t report. And to act on all this, you now have some simple procedures at your disposal.

Investigate how industries performed when a shock occurred in the past and capture (or avoid) that performance when the same shock returns. Separate unique businesses from commodity businesses and invest in that uniqueness. Detect and invest in inelastic industries based on the simple recipe of high profitability and low employment gains.

Because elasticity asserts itself everywhere, the applicability of these strategies is sweeping. In the next chapter, we investigate the elastic responses of businesses within distinct geographical locations; in so doing, we fine-tune our ability to invest properly across all sorts of economic shocks. The old business phrase is that location matters. In terms of investing with an elasticity mindset, it matters a lot.