Beta and inelasticity go a long way toward deciding these answers. We begin our industry study with some definitions.

The risk inherent in a stock (or asset class) in relation to the overall market is technically known as its beta. Every stock has a beta, a numerical value that can be positive or negative (or even zero), with a beta of 1 representing the benchmark average. For instance, if a stock has a beta of 1, it is in sync with the market, meaning that it will move with the market in either direction, up or down. When the stock market is going up, an asset with a beta of 1 will likely rise with the market; in a declining market, it likely will fall. Think of a beta of 1 as a seatbelt that secures an asset to the average performance of the market, and a beta of any other number as pulling an asset either toward above- or below-average performance. For instance, in a rising market, the beta of an asset that is less than 1 will likely underperform the market; a beta of greater than 1 might well outperform the market.

Obviously, beta is a neat little investment tool. And as a general rule, you don’t have to calculate beta for every stock or asset class out there. Financial analysts do this work for you: Go to any online stock-tracking site and type in a company name, and you will likely find that company’s beta (listed alongside a range of other stock fundamentals). For example: Dow Chemicals (DOW), beta 1.17; Hilton Hotels (HLT), beta 0.89.

Critically, however, beta is not to be viewed on its own. That is, beta must be partnered with additional economic concepts if you intend to use it as a profit-generating investment tool. Beta, you see, can change, and often the historical beta of an asset is not its true beta. Again, you won’t likely ever have to calculate beta yourself—this is an involved mathematical equation—but subjectively, you will want to forecast its direction with the changing economic times. As I see it, beta must be understood in relation to the supply-and-demand realities within every economy, as well as the ability of the separate industries to respond to these realities.

We pursue this line of reasoning shortly, but first, we turn to another new term: elasticity. By elasticity, I very simply mean the ability of an industry to adjust to economic shocks. An elastic industry shifts and alters and transforms when an economic “tsunami” envelops it, thereby helping to guarantee its very own survival. In supply-and-demand terms, when an economic shock brings about a shift in the demand for an industry’s product, an elastic industry has all options at its disposal: It can either raise or lower prices to meet that demand and/or increase or decrease output, performing all the necessaries to bring about these appropriate shifts: hire or fire employees, put up new plants or close some, keep production where it is or move it elsewhere, hold a sale or quietly raise sticker prices. But the adjustment options for inelastic industries are very limited when economic shocks arrive. Often they can only move prices higher and lower because they have a narrow ability to alter levels of production or output. As you will see, this sometimes leads to outsized profitability; at other times, it can lead to bankruptcy.

Taking all this together, the behavioral response of an industry to an economic shock goes a long way toward determining its profitability and the related direction of its stock price, up or down. Admittedly, this is a very quick interpretation of beta and elasticity, and witnessing each in real-world action might be the best way to understand their importance relative to your portfolio.

So, on to our first case study: In what follows, government regulation is our shock of choice—our thematic tidal wave, with swells of inflation thrown in. And our victim is the airline industry, an inelastic behemoth for much of its history.

A few decades before it died an old, beaten, dismembered thing, Pan American Airlines got a lot of respect—not only for being one of the original great airlines, but for representing something far more alluring than what one finds in everyday life. The 2002 film Catch Me If You Can puts a bright shine to this image. From the pilots’ perspective, that blue Pan Am jacket with the gold stripes on the sleeves meant autograph requests from children, gazes and winks from adoring women, and that extra bit of attention in each business hour of the day. It was a powerful uniform, one that elicited respect and awe—and not just for the pilots, but for the luxury planes they steered to far-off destinations. Pan Am blue meant palm trees and gold sand, romantic cafes up cobblestone streets, après-ski at an Alpine chateau. Pan Am meant possibility.

This is a Hollywood illustration. But in spirit, I believe it is an accurate rendering of Pan Am during the golden era of the big commercial airlines. This was not the airline business of crowded terminals and flight delays, of 40 planes stacked on the runway and a bag of pretzels for a meal. The carriers were rich, the passengers were well heeled, and the sky was the limit.

Pan Am boomed during the 1960s. For much of the decade, it ordered planes at a clip that suppliers couldn’t match, served a passenger base that was growing exponentially, and made money. In 1961, the airline earned $26 million on $460 million in revenues, both new highs; in 1963, profit was $79 million on $561 million in revenues.^[1] In 1965, Pan Am was serving about 6 million passengers; by 1969, it was serving more than 10 million.^[2] Such growth indicated that Pan Am had a bright future, and by most indicators, it did. In particular, Pan Am brass believed that not only would its future be one of passenger-filled cabins, but that an investment in the biggest commercial planes money could buy was warranted. Acting on this conviction, Pan Am became the first carrier to purchase the vaunted Boeing 747, ordering 23 of the jumbo planes (each carried nearly 500 passengers) in 1966 and putting the first one in the air commercially in 1970.^[3]

These were high times for the airline, which begs the question: If you were just starting out investing in 1970, would you want to own a piece of Pan Am or, in general, other airline stocks?

Not a chance.

Let’s start our investment analysis of the airlines industry at the very top by identifying the overriding macroeconomic forces of the day.

First, the 1970s were a notoriously high-inflation, high-interest-rate decade. One result was that the price of travel increased as the value of every dollar decreased. Higher air-travel prices, less air travel. Second, these were the OPEC oil-shock days, with the cost of flying airplanes climbing with the rising price of fuel. Higher air-travel prices, less air travel once more. So very quickly, we have two big negatives that warned against investing in the airlines industry.

And what would beta have told us? Well, airline stocks have been notorious for their high betas, which, again, are the most sensitive stocks to market movement. And how did the stock market do in the 1970s? It floundered for much of the decade, meaning that those high betas would only pull stock prices below the market average.

Without question, smart investors would have wanted to avoid airline stocks during the 1970s. But how about when the economic and stock market situations turned around? Would smart investors have been correct to jump back into airline stocks?

Again, not a chance.

During the 1980s, the stock market soared, oil prices declined, and eventually interest rates and inflation both came down—a seemingly perfect environment for those high-beta airline stocks. So let’s say you understood each of these variables well and put your investment dollars into the airlines early in the decade; let’s say you were an astute forecaster of the economic trends and just knew that an airline-favorable environment was in the making. How did you do?

Well, at least your forecast was correct: During the 1980s, much of what was anticipated—a rising stock market coupled with declining interest rates and oil prices—came to pass. However, despite the bull market of the 1980s and the high betas of the airline stocks, you underperformed. Airline stocks gained only 36.07 percent during the ten-year period between 1983 and 1992, well below the average of all industry groups, which came in at 180.91 percent (see Table 4.1).

What went wrong? In a nutshell, you relied too heavily on beta.

The broader explanation for this underperformance is rooted in the forces of supply and demand. Before 1978, the airline industry was tightly regulated. The federal government—specifically, the Civil Aeronautics Administration—totally controlled fares, route structures, and the like. The airlines industry could barely sneeze without the approval of the CAA, making it the textbook inelastic industry. Again, an industry is deemed inelastic when it cannot easily shift modes of production (supply) to meet changes in demand. For instance, if Pan Am wanted to fly more routes in the U.S. but was told it could not—which, indeed, was often the case—the supply of its service (which was to fly people around the globe) was severely limited.

Taking this to the next level, what happens when an industry cannot easily increase supply when the demand for its product or service increases?

The only way to satisfy demand in this case is to raise prices. Here’s the reasoning: If the price of a product goes up, a business or industry will receive more money per unit sold, although consumers will purchase less of that product. And the amount the sales volume declines depends on the flexibility of the consumer. If the consumer is quite flexible, volume will fall a lot; if inflexible, volume will fall very little.

These two opposing effects—price and volume—lead to different results: When the price effect dominates, revenues will increase. When the volume effect reigns supreme, revenues will fall. Thus, when the price effect is on and demand increases, businesses in an inelastic industry can survive—and even prosper—when the higher price of its goods or services compensates for its inability to increase supply. Basically, if you can sell more of what you have at a higher price without having to make any more of it, you’re sitting pretty.

This was the idealistic world of the super-regulated airlines. Largely due to government restrictions before 1978, the airlines were unable to easily expand their supply when there was an increase in demand. As a consequence, when the economy performed well and people traveled more, the regulated and inelastic airlines raised prices, an action that increased their profitability in exaggerated proportions relative to the economy. In this respect, the industry’s high betas were well earned.

But everything changed for the airlines beginning in 1978. With the passage of the Airline Deregulation Act that year, new carriers could freely enter the market, and all carriers could select their own routes. By 1982, the airlines could determine their own fares. This dramatically changed the shape of the airline industry’s supply curve: Where the spigots of supply had been tightly monitored, essentially opening or closing only by the hand of government, now the airlines could determine the flow of supply. This is not to that say the spigots could be opened all the way at this point; several factors still limited supply in the industry (for instance, airport gates and runways are not so flexible). But with the advent of deregulation, an inelastic industry suddenly became more elastic.

And by the early 1990s, Pan Am was bankrupt—which is not so surprising from the perspective of industry elasticity.

Viewed in isolation, beta can be misleading. But when observed in terms of elasticity, it can be extremely directional, letting you know exactly how to invest.

In a way, what I’m talking about are the indicator lights—like those in the cockpit of an airplane—that flash when it is time to buy or sell a stock or group of stocks. Back in 1982, a few years after deregulation hit, my indicator lights would have blinked for airline stocks such as Pan Am, telling me to sell. However, someone else’s indicator lights might well have been signaling the complete opposite: “Buy Big Air.”

Why the disparity? From my seat in the cockpit, if you bought airline stocks in the early 1980s, your indicator lights were primarily reading historical (or backward-looking) beta—an important reading, but potentially a false indicator if it doesn’t take into account both the big economic picture and the forces of supply and demand. Back in the early 1980s, when the Airline Deregulation Act was working its magic (or voodoo, depending on your point of view), the betas of the big airlines were declining as the industry shifted elastic. That meant, very simply, that the airlines would not participate in the forthcoming bull market as much as they might have in the past.

In the first blush of deregulation, the airline industry lost most, if not all, of its pricing power in the mass market. With the arrival of new airlines, the race was on to fill the marginal “empty” seat. And because the best way to fill an empty seat is with a lower price, the prices of coach tickets went down. (In theory, there is no incremental cost to filing the empty seat. Hence, all an airline needs to do is lower prices enough to induce consumers to fly. How low prices need to go depends on the price sensitivity of consumers.) Imagine, for a moment, big, bold, brassy Pan Am attempting to reach down low for the marginal-seat scraps. It did reach; it knew it had no other choice. But the big carrier couldn’t adjust at the speed or accuracy of the new and smaller carriers. Before deregulation was a decade old, Pan Am was no more.^[4]

So if you invested in the airlines industry in 1982, here’s why you got short-changed: Fluctuations in demand following airline deregulation were satisfied primarily by an increase of supply without the industry experiencing significant changes in profitability. An inelastic industry turned more elastic, those high betas plummeted, and the list of macroeconomic variables that once favored airline stocks—low inflation, low energy prices, and a rising stock market—were, to a degree, neutralized.

The investment lesson here is to be sure your indicator lights are forward looking: Use an industry’s historical beta as a guideline, but be sure to view that beta in relation to any current economic shocks that might be changing the elasticity (and, hence, the beta) within that industry.

If your indicator lights are functioning properly, you will want to own inelastic, high-beta stocks during the good times and abandon them during the bad. But a company does not necessarily fall out of favor when its business turns from inelastic to elastic. And the same holds for a stock that sees its high-beta decline. As we move between levels of elasticity and beta, all that changes are the investment rules.

To make this case, we can continue with the airlines saga.

In the decades since deregulation hit, the airlines industry as a whole has morphed along with its newfound elasticity. In particular, the airlines have become very deft at predicting the demand for each flight and each seat by passenger class, particularly with the aid of computers.

Just like industries, consumers can be considered either elastic or inelastic, a delineation the airlines now make all the time. Inelastic passengers might be the business travelers, people who need to be in a certain place at a certain time and are less concerned as a group about ticket prices. Elastic passengers, on the other hand, might be the vacationers who can adjust times of travel to when traveling is more affordable. With different price structures for elastic and inelastic passengers, the airlines are now better able to fill each flight—a profit-generating strategy in an industry whose margins of profit are quite small.

As noted, Pan Am flew high and far as a regulated bird but was unable to adapt its business fast enough or well enough to an explosion of elastic free-market activity. Other big airlines also went out of business, while still more acquired, merged, and expanded with skill to prolong their survival. That said, the few big airlines left standing—such as Continental, United, and American—continue to deal with the aftershocks of deregulation, if only because the low-cost provider still drives the market. The older airlines—specifically, the airlines with unionized workforces—have not been able to lower their cost structures enough to compete on a level with the nonunionized, fleet-of-foot upstarts.

JetBlue, for example, was hardly a blip on the airlines map at the turn of the new millennium. But with rapid speed, it became a darling of the business. A 60 Minutes news story began this way only a couple of years ago: “With most of the major airlines cutting back or even going bankrupt, Jet Blue, the new guy on the block, keeps turning a profit and expanding.”^[5] Excellent management, service, and marketing have gone a long way toward making the airline successful. But in good part, JetBlue has operated in a low-cost, highly elastic, and efficient way because it is a nonunionized airline. Elastic and inelastic are not necessarily polar opposites; grades of elasticity exist within industries. Unions will always handcuff businesses by making the cost of doing business less elastic. Pay scales, pensions, and benefits, in particular, are shaped less by the unionized businesses than by the unions themselves. And when a business cannot adjust its cost variables to economic realities, it is put at an immediate competitive disadvantage to the businesses that can.

To borrow from another popular film, an industry is not like a box of chocolates. It’s more like a box of assorted rubber bands, with each business in an industry able to “stretch” to a different degree. As an investor, if you look hard at elasticity, you will always know which company or groups of companies you’re going to get.

Investors who “catch elasticity if they can” will see superior results. And the example of the airlines industry instructs that catching elasticity depends partly on your ability to understand the effects of government regulation on industries overall, partly on your knowledge of how macroeconomic forces act on separate industries in unique ways, and partly on your ability to detect the winning innovators within each industry (such as those companies that can provide the most to consumers at the lowest cost). But catching elasticity will not have you micromanaging your portfolio. The changes in industry elasticity that economic shocks bring on—such as regulatory changes or technological advances or shifts in the tax burden—have, in general, been gradual.

It took Pan Am more than a decade to succumb following airline deregulation, a period of time in which the carrier attempted, unsuccessfully, to become more elastic through mergers, sell-offs, and strategic adjustments to routes and pricing. At the same time, it took the low-cost carriers time to perfect the art of filling that empty seat. Changes to industry elasticity are also predictable because similar shocks have caused the same reactions within individual industries throughout history.

Taking all of this into account, any investor will want to apply this set of elasticity rules:

Elasticity Rules of Engagement

Investing in Inelastic Stocks

Investing in Elastic Stocks

As I’ve noted, industries are big-picture items, with each industry representing a large bucket of stocks. It follows that if we correctly separate the winning industries from the losers, we will, in all likelihood, be able to allocate our portfolios to many outperforming companies. When people say they invest in sectors, this is just what they are attempting to do. These investors often buy sector funds that represent stocks within individual industries, or sector funds that have grouped several industries under a common heading (such as a “consumer” fund that includes stocks from the retail, food, and leisure industries).

Obviously, this should be a profitable activity when it is performed correctly. Flip back a few pages to our industry chart for the 1983–1992 period: Tobacco (+970.2); Beverages: Soft Drinks (+825.94); Containers: Metal & Glass (+717.37). How lucrative, one imagines, to have “caught” these industries during the 1980s. Alas, I cannot offer a formula that will locate, say, the top three or five performing industries over a future ten-year period. But I do offer a strategy that will have you selecting most often from the outperforming industries in relation to the economic environment.

Beta plus elasticity will get you to this level of outperformance. In the following chapter, we develop some practical measures of beta and elasticity, which will help simplify the process of catching (or avoiding) true high beta while you can.