As Darwin noted, improving fitness is not about strength or smarts but rather about becoming more and more suited to your environment—in a word, adaptability. Better fitness requires generating options and “choosing” the “best” ones. In nature, recombination and mutation generate species diversity, and natural selection assures that the most suitable options survive.5 For companies, adaptability is about formulating and executing value-creating strategies with a goal of generating the highest possible long-term returns.
Since a fitness landscape can have lots of peaks and valleys, even if a species reaches a peak (a local optimum), it may not be at the highest peak (global optimum). To get to a higher altitude, a species may have to reduce its fitness in the near term to improve its fitness in the long term. We can say the same about companies. This is a good metaphor for the Tiger Woods experience.
Fitness landscapes are a rich way to think about businesses. For any individual company, you have to answer two questions. First, what does the fitness landscape look like from the company’s perspective? Of course, not only are a company’s decisions influenced by its fitness landscape, but the decisions themselves help define the landscape. Second, is the company pursuing the right strategies to improve its fitness (i.e., economic value) over time given its landscape?
It’s important to note, though, that you can’t focus solely on the evolution of one company or industry because of the central role of coevolution. Actions trigger reactions. Sometimes companies cooperate with one another, sometimes they conflict. Nothing happens in a void—companies are always jockeying to improve their position.6 Further, the more dynamic the fitness landscape, the greater the necessary rate of adaptation.
To help answer the first question, here are three broad types of landscapes: stable, coarse, and roiling (see exhibit 23.1):• Stable. These are industries where the fitness landscape is reasonably stable. In many cases, the landscape is relatively flat, and companies generate excess economic returns only when cyclical forces are favorable. Examples include electric and telephone utilities, commodity producers (energy, paper, metals), capital goods, consumer nondurables, and real estate investment trusts. Companies within these sectors primarily improve their fitness at the expense of their competitors. These are businesses that tend to have structural predictability (i.e., you’ll know what they look like in the future) at the expense of limited opportunities for growth and new businesses.EXHIBIT 23.1 Various Fitness Landscapes
Source: Sente Corporation.
• Coarse. The fitness landscape is in flux for these industries, but the changes are not so rapid as to lack predictability. The landscape here is rougher. Some companies deliver much better economic performance than do others. Financial services, retail, health care, and more established parts of technology are illustrations. These industries run a clear risk of being unseated (losing fitness) by a disruptive technology.7
• Roiling. This group contains businesses that are very dynamic, with evolving business models, substantial uncertainty, and ever-changing product offerings. The peaks and valleys are constantly changing, ever spastic. Included in this type are many software companies, the genomics industry, fashion-related sectors, and most start-ups. Economic returns in this group can be (or can promise to be) significant but are generally fleeting.
You can make a good case that the combination of an accelerating pace of innovation, ongoing deregulation, and globalization is causing the global fitness landscape to contort more than it has in the past.8 Once you have a general sense of what the fitness landscape looks like for a company—and whether it is becoming more or less stable—you can consider the appropriate strategy process to maximize long-term value.
Look Before You Leap?
Consultant Eric Beinhocker suggests two general strategies to improve fitness. He calls the first “short jumps,” small incremental steps toward a peak. Most process-improvement initiatives are short jumps. He labels the other “long jumps,” discontinuous moves that may catapult a company to a higher peak or may leave it in a lower valley. Long jumps include meaningful acquisitions in unrelated fields and investing in nascent products. I believe that a company’s fitness landscape largely defines the appropriate balance between short and long jumps.9
For example, the focus in stable industries is often process optimization—continual small jumps. Long jumps are potentially costly and distracting, and therefore do not yield much value. This is not to say, for example, that technology will not touch these industries. It has and it will. However, the technological improvements are generally incremental and replicable.
To go to the opposite extreme, companies that compete in roiling fitness landscapes must focus more on long jumps—pursuit of the next big thing—because even if they find themselves at a peak, the shifting landscape assures that the peak quickly disappears. Since product life cycles are short, adaptation is more important than optimization.10
Companies that compete in coarse fitness landscapes quite logically need to find a blend between short and long jumps. Indeed, models show that this mix is the best search strategy for a correlated landscape.11
Tools of the Trade-Off
Just as a different mix of short and long jumps is appropriate for different fitness landscapes, so too are different financial tools and organizational structures. Traditional discounted cash flow analysis is well suited for businesses that compete in stable fitness landscapes. A centralized management approach is effective, as industry activities are often clearly defined.
A coarse fitness landscape requires a blend of traditional cash flow tools and strategic options. Strategic options are the right, but not the obligation, to pursue potentially value-creating business opportunities.12 Finally, companies that compete in roiling industries must lean more on strategic options to assess their current and potential fitness. Further, these companies are well served to adopt a “strategy by simple rules” approach. This decentralized approach has agreed-upon decision rules but lets individuals make decisions at the local level as they see fit.13
Fitness landscape Financial tool Organizational structure
Stable Discounted cash flow Centralized
Coarse DCF plus strategic options Loose centralization
Roiling Strategic options Decentralized
Tiger Woods showed that change, while sometimes painful in the short term, is necessary to improve fitness in the long term. Fitness landscapes can help you evaluate whether a company is pursuing the right potential strategies and has the appropriate organization. The analysis also points to the appropriate financial tools to assess various businesses.
24
You’ll Meet a Bad Fate If You Extrapolate
The Folly of Using Average P/Es
For past averages to be meaningful, the data being averaged have to be drawn from the same population. If this is not the case—if the data come from populations that are different—the data are said to be nonstationary. When data are nonstationary, projecting past averages typically produces nonsensical results.
—Bradford Cornell, The Equity Risk Premium
Intangible assets . . . surpass physical assets in most business enterprises, both in value and contribution to growth, yet they are routinely expensed in the financial reports and hence remain absent from corporate balance sheets. This asymmetric treatment of capitalizing (considering as assets) physical and financial investment while expensing intangibles leads to biased and deficient reporting of firms’ performance and value.
—Baruch Lev, Intangibles
Social Versus Security
Ernest Ackerman was one lucky hombre. The first reported applicant for Social Security payment, Ackerman retired one day after the program was launched in 1937. During his day of participation in Social Security, his employer withheld one nickel from his pay. Upon retirement, Ackerman collected a lump-sum payment of seventeen cents.
Future Social Security recipients may not be as fortunate. Even though the government
has made significant changes to Social Security over the past sixty-plus years, the system faces severe challenges. In large part, these challenges reflect a change in the demographics of the U.S. population.
For example, the government originally set the retirement age at sixty-five because actuarial studies showed that “using age 65 produced a manageable system that could easily be made self-sustaining with only modest levels of payroll taxation.”1 But from 1940 to today, the average percentage of men that survive from age twenty-one to age sixty-five leaped from 54 percent to 72 percent, the male life expectancy at sixty-five swelled from 12.7 to 15.3 years, and the fertility rate dipped nearly 10 percent. As a result, the worker per retiree ratio has plunged from forty-two to one in 1940 to about three to one today.
A look at Social Security’s evolution illustrates a crucial point: It is really hard to manage a system when the underlying data are constantly changing. You can’t draw conclusions from past averages because they don’t accurately represent today’s averages.
This lesson carries over directly to investing. One instance that stands out is when investors blithely apply historical-average price-earnings ratios to value either today’s market or an individual stock. Past-ratio averages are only applicable to the degree that they capture current circumstances. Just as no policymaker would dream of using old demographic data to assess the future of Social Security, investors should not casually rely on past price-earnings ratios to understand today’s market.
Nonstationarity and Historical P/Es
Nonstationarity is a crucial concept in any time-series analysis, and it is especially relevant for fields like climatology and finance. The basic idea is that for averages to be comparable over time, the statistical properties of the population must be the same, or stationary. If the properties of the population change over time, the data are nonstationary. When data are nonstationary, applying past averages to today’s population can lead to misleading conclusions.
Theoretical and empirical analysis of price-earnings ratios suggests that they are probably nonstationary.2 In fact, research shows that there has been no statistically significant relationship between a price-earnings ratio at the beginning of a year and the subsequent twelve- and twenty-four-month returns over the past 125 years. 3 More bluntly, the historical-average price-earnings ratio provides investors little or no guidance about market returns over the typical investment horizon.
While recognition that price-earnings ratios are likely nonstationary is critical, knowing why they are nonstationary provides more practical insight. Three big drivers of price-earnings ratio nonstationarity are the role of taxes and inflation; changes in the composition of the economy; and shifts in the equity-risk premium.
Why the Past May Not Be Prologue
A bedrock concept in finance is that investors price assets to generate an appropriate return (adjusted by perceived risk) net of taxes, inflation, and transaction costs. Accordingly, changes in tax law and inflation rates have a material effect on the appropriate value of the market, and hence price-earnings ratios.
The role of taxes is conceptually straightforward. Increases in dividend and capital gains taxes require investors to earn a higher pretax return to generate comparable returns. So all things equal, lower tax rates lead to higher multiples, and vice versa.
Tax rates have been anything but stable since the 1960s (see exhibit 24.1). The government taxed dividends at a nearly 90 percent rate in the early 1960s, and the rate has trended down to 15 percent in 2003, where it remains today. Capital gains taxes have seesawed between 20 and 35 percent before dipping to 15 percent in the early twenty-first century.
The interplay between tax rates and inflation is also important. Investors who seek real, after-tax returns increase their pretax-return requirements when they expect rising inflation. Exhibit 24.2 shows annual inflation (including forecasts) and rolling five-year trailing inflation from 1960 through 2006. The combination of high inflation and high nominal capital gains tax rates spurred very high discount rates—and very low price-earnings ratios—during the 1970s. Inflation also distorts financial statements. So price-earnings ratios vary significantly from one tax and inflation scenario to the next.
A second factor that shapes price-earnings ratios is the global economy’s shift from a reliance on tangible to intangible capital. Companies recognize tangible investments, such as new factories, on their balance sheets and depreciate the assets over their useful life. In contrast, companies immediately expense intangible investments like research and development or advertising.
EXHIBIT 24.1 Historical Tax Rates
Source: HOLT, American Council for Capital Formation.
EXHIBIT 24.2 Inflation Rates
Source: U.S. Department of Labor.
So it’s the form of investment, not just the magnitude of investment, that dictates the earnings a company reports. A tangible-oriented and an intangible-oriented business may invest an identical amount with the same return on investment and still have significantly different earnings. In general, intangible-reliant companies have a higher cash-flow-to-net-income ratio.
To illustrate this point, I take two samples from the Dow Jones Industrial Average. The first, which I call the tangible group, includes Alcoa, Caterpillar, United Technologies, and Wal-Mart. The intangible group comprises Altria, Coca-Cola, Microsoft, and Procter and Gamble. Over the five reported fiscal years that ended with 2006, the tangible group had a cash-flow-to-net-income ratio of 28 percent, versus a 111 percent ratio for the intangible group.
There is pervasive evidence that the global economy is moving from a reliance on tangible to intangible assets, including market-to-book ratios, workforce allocation, and the rising significance of education. Further, because intangible-reliant businesses have few assets on their balance sheets, they tend to show high returns on capital. With other factors held constant, higher cash-flow-to-net-income ratios and returns on capital support higher price-earnings ratios.4
The final factor that dictates the price-earnings ratio is the equity-risk premium, or the return that equity investors demand above and beyond a risk-free security. (The equity-risk premium itself appears to be nonstationary.) 5 While a number of factors come into play to determine the risk premium, including future growth estimates, the aggregate risk appetite of investors is certainly important. In periods of general optimism, equity-risk premiums shrink, and premiums expand when investors are cautious. The ebb and flow of investor risk appetite likely contributes to the nonstationarity of multiples.
Bounded Parameters
The market’s price-earnings ratio has averaged just over fourteen over the past 130 years or so, and the multiple has zigzagged across this level many times during that period.6 Isn’t this proof enough that fourteen is the multiple to which the market reverts?
The answer, I believe, is a qualified no. In all likelihood, two of the three drivers of nonstationarity—taxes/inflation and equity risk premium—are probably bounded. That is, they vacillate within reasonably defined, albeit large, channels. These drivers might average out over the very long term (i.e., a decade or more), but they are the source of significant, and legitimate, multiple differences over many decades.
Absent a change in our accounting system, the third driver, the evolving economy, argues for higher price-earnings multiples, all else being equal. The simple basis for this conclusion is that companies that expense their investments tend to have higher cash-flow-to-net-income ratios than companies that capitalize their investments. This is likely a secular trend.
Offsetting this upward bias, though, is the fact that the period of sustainable competitive advantage may well be shorter for service and knowledge businesses than it was for the physical capital businesses of the past. So the warranted price-earnings ratio, net of these countervailing forces, may not be much different than historical averages. But the underlying economic rationale for the ratio has changed substantially.
Unpacking the (Men
tal) Baggage
Because price-earnings ratios are likely nonstationary, investors should use them sparingly and cautiously, if at all. The attraction of a ratio, of course, is that it is often a useful rule of thumb. I argue, however, that investors who insist on using multiples will find them much more useful if they unpack the embedded assumptions. This unpacking reveals how and why circumstances are different today (e.g., growth, inflation, taxes, risk appetite, the structure of the economy) than they were in the past and what that means for the multiple.
25
I’ve Fallen and I Can’t Get Up
Mean Reversion and Turnarounds
The key finding of this research . . . is that the demonstrated rarity of achieving sustained superior economic performance implies that it is extremely difficult to achieve. An associated finding . . . is that even if superior performance is achieved and sustained for a period of time, the probability of slipping from that lofty perch is relatively high.
—Robert R. Wiggins and Timothy W. Ruefli, “Sustained Competitive Advantage”
Returns and Growth
Finance professor Josef Lakonishok argued that the stock market had many “pockets of craziness” in a 2004 New York Times article.1 Lakonishok’s case was based on the relationship between growth and price-earnings ratios, and he suggested that the market was implying unrealistically rapid earnings-growth rates for some companies with lofty price-earnings multiples. Research he conducted with a pair of colleagues showed that very few companies sustain high growth rates.2
More Than You Know Page 15
