Excerpt: Don’t Count on It!
The following excerpt is from Don’t Count on It!: Reflections on Investment Illusions, Capitalism, “Mutual” Funds, Indexing, Entrepreneurship, Idealism, and Heroes by John C. Bogle. Listen to the Marketplace Money interview and learn more about the book.
Chapter 1: Don’t Count on It! The Perils of Numeracy*
Mysterious, seemingly random, events shape our lives, and it is no exaggeration to say that without Princeton University, Vanguard never would have come into existence. And had it not, it seems altogether possible that no one else would have invented it. I ‘ m not saying that our existence matters, for in the grand scheme of human events Vanguard would not even be a footnote. But our contributions to the world of finance–not only our unique mutual structure, but the index mutual fund, the three-tier bond fund, our simple investment philosophy, and our overweening focus on low costs– have in fact made a difference to investors. And it all began when I took my ï¬rst nervous steps on the Princeton campus back in September 1947.
My introduction to economics came in my sophomore year when I opened the first edition of Paul Samuelson’s Economics: An Introductory Analysis. A year later, as an Economics major, I was considering a topic for my senior thesis, and stumbled upon an article in Fortune magazine on the “tiny but contentious” mutual fund industry. Intrigued, I immediately decided it would be the topic of my thesis. The thesis in turn proved the key to my graduation with high honors, which in turn led to a job offer from Walter L. Morgan, Class of 1920, an industry pioneer and founder of Wellington Fund in 1928. Now one of 100 – plus mutual funds under the Vanguard aegis, that classic balanced fund has continued to flourish to this day, the largest balanced fund in the world.
In that ancient era, Economics was heavily conceptual and traditional. Our study included both the elements of economic theory and the worldly philosophers from the 18th century on–Adam Smith, John Stuart Mill, John Maynard Keynes, and the like. Quantitative analysis was, by today’s standards, conspicuous by its absence. (My recollection is that Calculus was not even a department prerequisite.) I don’ t know whether to credit– or blame–the electronic calculator for inaugurating the sea change in the study of how economies and markets work, but with the coming of the personal computer and the onset of the Information Age, today numeracy is in the saddle and rides economics. If you can’t count it, it seems, it doesn’t matter.
I disagree, and align myself with Albert Einstein’s view: “Not everything that counts can be counted, and not everything that can be counted counts.” Indeed, as you’ll hear again in another quotation I’ll cite at the conclusion, “to presume that what cannot be measured is not very important is blindness.” But before I get to the pitfalls of measurement, to say nothing of trying to measure the immeasurable–things like human character, ethical values, and the heart and soul that play a profound role in all economic activity– I will address the fallacies of some of the measurements we use, and, in keeping with the theme of this forum, the pitfalls they create for economists, financiers, and investors.
My thesis is that today, in our society, in economics, and in finance, we place too much trust in numbers. Numbers are not reality. At best, they’re a pale reflection of reality. At worst, they’re a gross distortion of the truths we seek to measure. So first, I’ll show that we rely too heavily on historic economic and market data. Second, I’ll discuss how our optimistic bias leads us to misinterpret the data and give them credence that they rarely merit. Third, to make matters worse, we worship hard numbers and accept (or did accept!) the momentary precision of stock prices rather than the eternal vagueness of intrinsic corporate value as the talisman of investment reality. Fourth, by failing to avoid these pitfalls of the numeric economy, we have in fact undermined the real economy. Finally, I conclude that our best defenses against numerical illusions of certainty are the immeasurable, but nonetheless invaluable, qualities of perspective, experience, common sense, and judgment.
Peril #1: Attributing Certitude to History
The notion that common stocks were acceptable as investments–rather than merely speculative instruments–can be said to have begun in 1924 with Edgar Lawrence Smith’s Common Stocks as Long-Term Investments. Its most recent incarnation came in 1994, in Jeremy Siegel’s Stocks for the Long Run. Both books unabashedly state the case for equities and, arguably, both helped fuel the great bull markets that ensued. Both, of course, were then followed by great bear markets. Both books, too, were replete with data, but the seemingly infinite data presented in the Siegel tome, a product of this age of computer – driven numeracy, puts its predecessor to shame.
But it’s not the panoply of information imparted in Stocks for the Long Run that troubles me. Who can be against knowledge? After all, “knowledge is power.” My concern is too many of us make the implicit assumption that stock market history repeats itself when we know, deep down, that the only certainty about the equity returns that lie ahead is their very uncertainty. We simply do not know what the future holds, and we must accept the self – evident fact that historic stock market returns have absolutely nothing in common with actuarial tables.
John Maynard Keynes identified this pitfall in a way that makes it obvious:** “It is dangerous to apply to the future inductive arguments based on past experience [that’s the bad news] unless one can distinguish the broad reasons for what it was” (that’s the good news). For there are just two broad reasons that explain equity returns, and it takes only elementary addition and subtraction to see how they shape investment experience. The too – often ignored reality is that stock returns are shaped by (1) economics and (2) emotions.
Economics and Emotions
By economics, I mean investment return (what Keynes called enterprise***), the initial dividend yield on stocks plus the subsequent earnings growth. By emotions, I mean speculative return (Keynes’s speculation), the return generated by changes in the valuation or discount rate that investors place on that investment return. This valuation is simply measured by the earnings yield on stocks (or its reciprocal, the price-earnings ratio). â€ For example, if stocks begin a decade with a dividend yield of 4 percent and experience earnings growth of 5 percent, the investment return would be 9 percent. If the price – earnings ratio rises from 15 times to 20 times, that 33 percent increase would translate into an additional speculative return of about 3 percent per year. Simply add the two returns together: Total return on stocks = 12 percent. â€¡
So when we analyze the experience of the Great Bull Market of the 1980s and 1990s, we discern that in each of these remarkably similar decades for stock returns, dividend yields contributed about 4 percent to the return, the earnings growth about 6 percent (for a 10 percent investment return), and the average annual increase in the price – earnings ratio was a remarkable and unprecedented 7 percent. Result: Annual stock returns of 17 percent were at the highest levels, for the longest period, in the entire 200 – year history of the U.S. stock market.
The Pension “Experts”
Who, you may wonder, would be so foolish as to project future returns at past historical rates? Surely many individuals, even those expert in investing, do exactly that. Even sophisticated corporate financial officers and their pension consultants follow the same course. Indeed, a typical corporate annual report expressly states, “Our asset return assumption is derived from a detailed study conducted by our actuaries and our asset management group, and is based on long – term historical returns.” Astonishingly, but naturally, this policy leads corporations to raise their future expectations with each increase in past returns. At the outset of the bull market in the early 1980s, for example, major corporations assumed a future return on pension assets of 7 percent. By the end of 2000, just before the great bear market took hold, most firms had sharply raised their assumptions, some to 10 percent or even more. Since pension portfolios are balanced between equities and bonds, they had implicitly raised the expected annual return on the stocks in the portfolio to as much as 15 percent. Don’t count on it!
As the new decade began on January 1, 2000, two things should have been obvious: First, with dividend yields having tumbled to 1 percent, even if that earlier 6 percent earnings growth were to continue (no mean challenge!), the investment return in the subsequent 10 years would be not 10 percent, but 7 percent. Second, speculative returns cannot rise forever. (Now he tells us!) And if price – earnings ratios, then at 31 times, had simply followed their seemingly universal pattern of reversion to the mean of 15 times, the total investment return over the coming decade would be reduced by seven percentage points per year. As the year 2000 began, then, reasonable expectations suggested that annual stock returns might just be zero over the coming decade. ****
If at the start of 2000 we were persuaded by history that the then long-term annual return on stocks of 11.3 percent would continue, all would be well in the stock market. But if we listened to Keynes and simply thought about the broad reasons behind those prior returns on stock–investment versus speculation–we pretty much knew what was going to happen: The bubble created by all of those emotions–optimism, exuberance, greed, all wrapped in the excitement of the turn of the millennium, the fantastic promise of the Information Age, and the “New Economy” had to burst. While rational expectations can tell us what will happen, however, they can never tell us when. The day of reckoning came within three months, and in late March 2000 the bear market began. Clearly, investors would have been wise to set their expectations for future returns on the basis of current conditions, rather than fall into the trap of looking to the history of total stock market returns to set their course. Is it wise, or even reasonable, to rely on the stock market to deliver in the future the returns it has delivered in the past? Don’ t count on it!
*Based on my keynote speech at the “Landmines in Finance” Forum of The Center for Economic Policy Studies at Princeton University on October 18, 2002.
**John Maynard Keynes commenting on Edgar Lawrence Smith’s book (1926).
*** John Maynard Keynes, The General Theory of Employment, Interest, and Money (New York: Macmillan, 1936; Harcourt, Brace, 1964), Chapter 12. This chapter makes as good reading today as when I ï¬ rst read it as a Princeton student in 1950. Interestingly, in the light of the thesis that I present in this essay, Keynes introduced these concepts with no quantiï¬cation whatsoever. So I have taken the liberty of inserting the appropriate data.
â€ The earnings yield is also inï¬‚uenced by the risk-free bond yield. But because that relationship is so erratic, I have ignored it. For the record, however, the correlaÂ¬tion between the earnings yield on stocks and the U.S. Treasury intermediate-term bond since 1926 has been 0.42. However, for the past 25 years it was 0.69, and for the past 10 years 0.53.
â€¡ I recognize that one should actually multiply the two (i.e., 1.09 X 1.03 = 1.123), obviously a small difference. But such precision is hardly necessary in the uncertain world of investing, and when addressing the lay investor, simplicity is a virtue.
****Update: As it turned out, the annual return on stocks for the 1999-2009 decade came to -0.2 percent.
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