Sticky Luck

Ten:

What Can We Say About Bubbles?

A market pattern we cannot ignore.  Rational investing can take strange forms - call it rationalization.  Why thinly traded stocks must be excluded from normal market theory.  P/Es over 100 can remain in our models though not in our conventions.  The "I" distribution.  Fire drills and Ponzi schemes.  Why people decide to enter Ponzis, and why they enter bubbles.  Instability, not inevitability.

Financial bubbles create little consensus and, probably as a result, are a constant source of fascination.  The huge, almost arbitrary transfers of wealth they cause excite our tabloid instincts, as does the gamble they imply.   I will use the term to describe highly unusual market rises, typically followed by sudden market downturns which then stay down (relative to the peak) for at least a number of years.  A more typical definition includes concepts such as “severe overvaluation” and perhaps reference phenomenon like “herd behavior.”  A short paragraph describing bubbles is usually enough for the writer to take at least a partial swing at efficient-market theory, claiming that the irrationality of bubbles is a major challenge to the “rational investor” concept underlying the idea of efficient markets.   Hopefully, the reader who has reached this point on the website no longer confuses an efficient market with rational behavior. 

Yet, in order to support my statistical model two chapters ago, I did rely upon the fact that the actions of investors could be viewed as if those investors were rational.  I am therefore challenged to show how this can occur in the event of a bubble, or admit that the theory breaks down in such circumstances.  I have been careful to define such circumstances by what can be objectively known – the magnitude of the market change.  I have said “typically followed” rather than “followed” by a downturn, because a key question concerning bubbles is whether or not they can be identified before they pop.   The problem with the usual definition of a bubble is that it not only presumes to diagnose human behavior, but references valuations as if they provided some scientific measuring rod.  Needless to say, the confidence of such diagnoses is almost always after the fact of the pop.

In fact, if there were ever an opportunity for the pattern followers, bubbles would seem to be it.  Repeating patterns, and also cherished “fundamentals,” appear to be abandoned during these exceptional periods of market growth.  It would seem reasonable that all those market professionals would be ringing alarm bells long before a bubble took hold, telling us of the dire consequences.  Yet, at least for those of us who followed the financial media during the run-up to the NASDAQ crash, even the “quality” sources were largely muted.  In Irrational Exuberance, Schiller points out wryly that one of our largest and most respected investment houses, on the occasion of the Dow passing 10,000 (indirectly fueled by the hi-tech surge) took out a full-page advertisement with the central message, “Wow!”  Those institutions which, both before and after the crash would constantly tell us how they would shepherd us safely towards out retirement goals, had the power and authority to explain to the public the dangers of bubbles.  Instead, as we now know, many of the institutions’ senior employees were actively exploiting the bubble, sometimes at the public’s expense, and being hugely rewarded for it. 

Greenspan’s View

Official sanction was given to this approach by a Federal Reserve Chairman who expressed the view that bubbles are not obvious at the time they are developing and therefore can be managed only in their aftermath.   Therefore there seem to be weighty opinion behind either one of the two following theories:

·        Irrational behavior can only be understood as such in retrospect, or

·        Bubbles are the product of rational behavior.

Since we would all hoped to recognize irrational behavior when we see it, there therefore appears to be an institutional bias in favor of rational bubbles.  Indeed, we had books such as “Rational Exuberance” and “Dow 30,000” which caught this quite widespread view.  People didn’t seem to be going crazy.  They seemed to be taking a much deeper interest in the stock market than ever before, consuming new magazines and TV programs that poured out great detail on the new technology.  Some chartists and fundamentalists demurred, but we have bears in every type of market.  Many adapted to the new reality by showing how such valuation could be justified with the right assumptions about future growth.  And, as we have explained, there are patterns to be found which can back up pretty much any theory we choose.

I had better explain more fully how I am using the terms rational and irrational in this context.  Earlier in the book my task was different – to explain why efficient-market theory could coexist happily with irrational investment behavior, as defined by the behaviorist school of market theory.  As mentioned, I believe that the behaviorist school has contributed greatly to our understanding of markets, but that it has wrongly been used as a club to beat efficient-market theory, at least partly to protect the fees of the investment industry.  I think behaviorists would agree with me that, though investment decisions are heavily influenced by emotion and gut feel, the human brain has a peculiar tendency to rationalize its decisions, with a kind of back-filling of logic.  Maybe we make most of our decisions this way.  Another fascinating aspect of bubbles is that it shows up this human weakness in stark relief, and I think part of our confusion about them may rise from our unwillingness to accept that “rationalization” drives so much.  For those who doubt this thesis, I recommend almost any well-reviewed and detailed history of the Great War in Europe (aka WWI).

I do not disagree with Schiller’s thesis in Irrational Exuberance.  In fact, his central point dovetails with mine.  An alarming percentage of the public invested in equities have little idea of either the quantity, or quality, of risks they are taking with their future security.  I would add that many institutional investors, such as pension funds, are managed by individuals with similarly naïve perceptions of risk, often leveraging the exposure of their sponsoring employers in irresponsible ways.  This topic is covered in more detail in the next chapter.  For now, I call a decision “rational” if the decider can argue his or her case when challenged, and when similar arguments can be found in books, magazines, websites, TV and radio shows that purport to provide investment advice.  Whether or not Professor Schiller and I regard such advice as a sham does not change its persuasive powers, up and down both sides of the bubble.

What of other bubbles?  We will exclude those before the 20^th Century, as they do not meet our criteria of freely traded securities, which includes widespread access to the same public information, and the relegation of insider trading to a sufficiently small group to have negligible impact upon market prices.  If we apply these criteria strictly, it is questionable whether or not the other commonly accepted bubbles within our timeframe – those of global markets in the 1920s and the Japanese market in the 1980s – qualify as of direct relevance.  There is no question that lack of the type of information flow we now take for granted in Western markets was a contributing factor.  Yet there are features of both worth examining – if only out of desperation, or else we have very little data to work on.

What’s Really Different from the 1920s?

It has been observed that P/E ratios before the Great Crash were not outrageous by today’s accepted standards.  The inability of the market to recover has since been widely blamed on a mutual destruction of international trade by countries trying to protect their workforces in the short term, and by the Federal Reserve’s refusal to reduce what had become very high real interest rates, under a severely deflationary environment.   There is no doubt that, for a generation after the crash, the market of early 1929 appeared absurdly optimistic.  Yet from today’s perspective, it would appear that the optimism was, at worst, premature.  The growth rates inherent in the valuations at the time came to be fulfilled, despite the blunders of politics and economic mismanagement.  Acknowledging this fact about the 1920s market is not a popular position, as it would seem to suggest that such a calamity to reappear today.  But it is hard to argue convincingly the sharp distinction between the optimism for equities then and the optimism today. 

In Japan, the 1980s are commonly referred to as “the Bubble Economy,” so engrained has the concept of a bubble become in the popular view.  It was an asset bubble, affecting equities and real estate at the same time.  It is now widely accepted that the image of an invincible industrial power, capturing all global markets before it, hid a corrupt and inefficient financial system which could not withstand a loss of momentum.  Loss of market value spiraled as bad loans became exposed.  The cultural tendency to seek harmony and avoid conflict, so triumphant in industrial production, became a weakness as structural problems were not tackled head on.  Over a decade after the bubble burst, observers talked about Japan’s loss of will to put things right. 

Unlike the other two bubbles described here, Japan’s did not appear to have been driven by the small investor seeking riches – shareholdings were, and still are, more heavily in the hands of institutions.  Foreign institutions, such as US and European pension funds, were major investors.  It is difficult to imagine that they did not have convincing models to justify Japanese equities in their portfolios.  There may have been an acknowledgement of high risk but, unquestionably, a commensurate yield was also there and the portion of the total portfolio so devoted was appropriate to the exposure.  Since a great many shares of Japanese companies never were traded, being “cross-held” between friendly companies, banks and insurance carriers, the leveraging effect on prices of foreign activity was all the more intense.  Foreign investors were not to know that local management would succumb to the temptation of borrowing greatly against inflated stock prices and real estate, often for investments not worthy of the name.  It had seemed plausible that Japan had, by virtue of its unique culture of dedication and cooperation, did not follow the normal investment rules that allowed for strikes, wasting competition and worker lethargy.  It was a revelation that the Japanese, whose society remains little understood by the West even today, proved to be as self-indulgent as the rest of us – just in different ways.

So, as I would define the word rational, I believe that all bubbles remain rational right up to their peak.  Of course there are warning voices during the build up, but there are always warning voices even when the market is low and about to take off again.  As I have tried to emphasize in this book, there are always equal numbers of buyers and sellers, bulls and bears, optimists and pessimists.  The free market makes sure that prices pitch themselves at such a level as to always balance these forces.  I believe that most published surveys of “bullishness” and the like have no value, as the sampling is invalid.   A survey of brokers, for example, tells us only about one limited class of investor and only what they say, not what they do. The only truly valid survey is the market itself. 

There are some special features of the hi-tech bubble that have been widely cited and demand mention.  One was the very limited initial supply of many dot-com shares available for purchase because of the sheer volume of IPOs.  To the extent that limited supply inhibits a free market, I consider this source of bubble-inflation to be outside the scope of this book.  Also, if the supply is limited, the financial impact upon the market as a whole must be small.  To meet our requirements of an efficient, free market, the buyer and seller must have an accurate idea of the deal price when making their decisions.  It is easy to see how a limited supply can create a type of auction, which has a different dynamic. 

Speculative Fever

To examine our market thesis, we will focus more on those companies which provide significant weight to the NASDAQ – the top hundred might be a convenient classification.  This approach may appear like an escape from the core of the bubble, which to some was those dot-coms which burned through cash without getting close to making money.  To the extent such stocks were freely traded, they may well also follow our analysis here.   I will be making allowance for the highly speculative end of the hi-tech market at the time.  But my inclination is to see them as a type of chaos generated by the underlying bubble in the major players.  As well as the auction factor for thin trading, we might add a gold-rush factor for pure speculation.  Though speculation is a critical part of any bubble, the investor rationalization must be anchored by the concept of investment.  We therefore need to talk in the language of investment, of which the most basic measure is the P/E ratio.

For those companies already making profits, P/E ratios were commonly above 100.  If we take a “normal” company P/E as 18, and we expect our return from equities to be 9% per year, then we are expecting about 3.5% earnings growth from that equity for every year in the future.  In other words, the same amount of capital must generate increasing profit, typically through market growth and innovation permitting greater efficiencies.  For a P/E of 100, that required growth rate is 8%.  Of course, we were seeing profit growth greatly in excess of this.  But these growth rates of 3.5% and 8% must be sustained on average for the indefinite future.  Of course, higher growth rates in the earlier years reduce the need for such growth in later years.  And some of that growth is nominal, coming simply from inflation of the currency.  If we remove that, we are left with perhaps a sustained 5% real earnings growth needed from the pre-crash technology company.

Such earnings growth is very possible for individual companies, and has been demonstrated by many over long periods of time.  However, it cannot happen for all companies, even in a very high-growth industry.  The very fact of those profits draws in competition and investment, cutting prices and challenging sales with innovation and service.  It is unrealistic to imagine that all the current companies will end up the winners in such an expanded environment, particularly when reviewing the history of competition in such environments.  What may seem like an unassailable brand can quickly become passé.  It follows that a number of the new companies will end up being worth their 100 P/E price tags, but the majority will not even make it long-term into the 18 club.

The Rationale of the One-Hundred Club

Even those at the 100 mark inevitably go through tough times as growth falters from time to time.  Such faltering is likely to affect the whole industry on occasion, given that it is largely bound together with complementary products.  The NASDAQ is now at about half its peak level.  It has been a rough ride for many late entrants, but still the majority of tech investors over the past thirty years have still enjoyed excellent returns.  We explained earlier how minor changes in interest rates and growth assumptions can halve “intrinsic value,” which makes a 50% drop par for the course in a highly volatile sector.  With this as background, it would be hard to attack the rationalization that a good-looking stock with a P/E ratio of 100 could well justify its price.  Unfortunately, this arithmetic does not factor in risk.

And herein lies the issue with bubbles.  Even at the bubble’s height, the logic of projected growth remains reasonable for certain companies in the bubble’s sector.  Unfortunately we cannot know which ones and, in such a fast-changing bubble world, there is no particular reason why it should be today’s leaders.   So any stock we might pick has some probability of justifying the 100 P/E or even better, but also a large probability of doing worse, all the way down to total failure.  Our SLMH model assumed every investor could be matched with an identically acting rational investor, and we assumed that such rational investors constructed probability weightings for their traded stocks.  But it was not necessary to assume that their probability weightings were scientific, or based on the kind of new-industry analysis we have done here.  By “rational” we mean that the investor has thought through to an expected return, even if he or she has poorly weighted the risks of new technology.  It is not the role of the model to judge any particular view as poor, but it is fair to say that the traditional limitations of the 8-12% annual equity yield are ignored. 

For prices to give us 100 P/E ratios, investors must break their normal bonds with the assumed equity returns, and not only for short-term gains.  The true believers in the technology revolution expected much greater returns year after year and, for a six-year period 1994-2000, they got them – almost 40% per year for the NASDAQ as a whole, let alone the dot-com leaders.  Though it is common wisdom today that such returns are unsustainable, as I have mentioned, the media as a whole gave little more air to it ending in tears than they do at any other time.  The response was largely, “This is amazing,” rather than, “This is out of control.”  For those companies which had turned profits, profits were rising relentlessly, and revenue growth was building the foundational economies of scale for sustained profit growth.  A flood of new advisors explained why this was not a passing phase.  As an anecdote, I recall an editor of Silicon Valley magazine writing on the social implications of this phenomenon.  After dismissing the doomsayers with the expression, “We’ve all been through that fire-drill,” he went on to praise the wealth effect and how this will change infrastructure investment, philanthropy, etc.

The investment industry would prefer to see the NASDAQ incident as an aberration.  Despite having fueled it and left so many exposed, the industry can turn it, at least at a subliminal level, into a reason for paying for their guidance. (Guidance is often a free service, as the payment has already been received through small percentages of vast funds.)  Yet, under the SLMH, the hi-tech bubble is the exception that undermines the conventional wisdom of normal times.  It shows that, when there’s money to be made, patterns and fundamentals are either move to one side or else twisted to conform.  Instead of guiders, they are revealed to be followers of wherever the market chooses to take them.  These market theories are too weak to penetrate professional, let alone popular, reaction to a new investment phenomenon.  This book has spent many words attempting to undermine the theoretical underpinnings of conventional market models, but it can’t hope to equal the practical blow delivered by the Internet and its entourage.

The “I” Distribution

How does the SLMH cope?  In an earlier chapter we hinted at an I-shaped distribution of expectations, as distinct from a neutral E shape, a bullish F shape or a bearish inverted F shape.  Unshackled (some would say unhinged) from conventional return expectations, the tech bulls are free to roam all over the upside.  Purely from my own anecdotal evidence, an annual return of 20% seems to have been a common expectation.  Certainly, those going out on margin or on credit cards expected returns well above their carrying costs – a 2-3% additional annual yield would not have been worth the effort and danger of fluctuation, even if they were convinced of the higher long-term return.  No doubt there were many who thought 50% per year was not expecting too much – after all, there had been plenty of examples of companies achieving this year after year.  I would guess that actual investors would translate into a set of rational investors spread all along the 10%-50% spectrum.   But many of the high-enders were not long or even medium term, and this – no surprises – is the other critical feature of bubble times.

Before considering these short-term investors, I’d like a short side-journey into what are commonly known as Ponzi and Pyramid schemes.  I do not make the case that the free market even approximates to such schemes, and this would certainly include the NASDAQ 100.  But it worth considering some of the schemes that have operated in recent times is less well-regulated countries.  We would typically assume that people enter such schemes unknowingly.   But I have read articles describing how, despite publicity that such schemes were fraudulent and would inevitably implode, people knowingly continued to invest their money.  On reflection, this should not be too surprising, given the universal love of gambling.  Human instincts, or weaknesses, for such schemes and also for Las Vegas would seem to be closely linked.  However, there is an important difference.  Las Vegas shakes out the winners and losers every few minutes and on a fairly non-discriminating basis.  Ponzi and pyramid schemes, like bubble, involve an enormous redistribution of wealth from the later participants to the earlier ones who got out at the right time.

The editor who wrote about the “fire drill” clearly thought there was a chance of a downswing, but dismissed its probability to the level of a building fire.  Nevertheless, he thought that he and other could prepare for it, as if the stock market could give a clear warning of the difference between the start of its ultimate swan-dive and a buy-on-the-dip break.  Maybe he even thought that first the technology industry would confess it was in sudden recession, and that then there would be a sufficient market pause for him and other to get out before the crash.  That is, after all, what the fire-drill analogy implies.  In any event, there must have been a widespread sense that it was possible to avoid going over a cliff, whether or not that cliff was inevitable.  And that is the essence of entering a Ponzi or Pyramid scheme knowingly.  The end does not appear imminent.  If I am “nimble” I can get in and out before disaster strikes.  As a colleague remarked after saying her husband wanted to stay out because of an impending crash, “But I told him, hey, why don’t we make some money now?”  If I am brave, I can linger in there a little longer and make a killing.  In fact, those getting out too quickly are “panicking.”  As one good friend told me in the nicest way when I resolved to stay out, “Don’t be a wimp.”  (I think this is a relevant anecdote even though the remark may have been justified for other reasons.)

Day Trader As Icon

Of course, the day-trader became the icon of this movement.  Whereas sticky luck may take years to select winning fund managers, it took only months to create the illusion that there was a talent to playing the market with dot-com stocks.  Just as the day-trader relies formally on the chart to imagine where the market is expected to go next, all the fire-drill graduates had some instinct that certain market movements would – to mix metaphors – be their canary in the mine.  In other words, belief in the rescuing virtues of patterns because the solace of all those who wagered enough on the tech revolution to drive up prices into the new P/E regime.  The irony is that, far from denting efficient-market theory, the tech bubble showed how much things can go wrong when investors abandon the core concept of efficient-market theory, no matter how vaguely understood.  The market offers no warnings before it takes you money.  And its feints are indistinguishable from the real thing. 

A layer of short-term profit-taking is always to be expected from any stock at any time, but is largely confined to professional traders.  The difference during the hi-tech bubble was the public’s participation, both in the form of something like day-trading, and also with the thought, “This may be chancy, but I can always exit before I make a loss.”  The psychological difficulties of maintaining such a strategy are severe, but do not concern us here.  The key point is that, if Ponzi investors are willing to roll the dice, it is not difficult to see the attraction of a similar gamble where selling out at a profit is technically available at any time.  Many people would have been attracted by the sheer thrill of the quick and easy payoff, without any real interest in the business behind the ticker symbol.  P/E ratios would have been irrelevant, as the issue was simply a matter of price movement.  Some professionals somewhere were no doubt checking on fundamentals, keeping the contest fair.  Such investor behavior is no more irrational than a week in Las Vegas.  In fact, it is the same kind of activity that investment houses get up to, but with one critical difference:  it is not backed by the same mountain of data analysis.  The activity therefore reduces to a horse race, and we plan to leave the track as soon as we stop having fun.  It makes little difference that we bothered to find out what this company actually makes – that is merely the equivalent of an amateur punter checking the horse’s gait in the paddock.

Now, let’s examine the SLMH critically in the context of the bubble.  First, the descriptive side of sticky luck, which we considered in the earlier chapters.  The reality of a free flowing Internet with unlimited bandwidth, and of powerful searches to bring order to unimaginable scale, took time to prove itself.  Looking back, we now know it was all technically quite feasible – per my analogy, we had entered a deep new forest.  The existence of the forest justified, in the eyes of the market, the NASDAQ we see at the time of writing, sustained above the 2000 mark for some two years and beginning to look like just any other sector in a modest bull market.  The technology market therefore, in retrospect, was a sector which had a boom period and temporary overshot the mark in price.  Compared to gold in the late 1970s the overshoot looks modest indeed.  The technology boom itself was real enough and even now, through its facilitation of offshoring, we are discovering how profound its revolution is turning out to be.  If there was a mistake, it was not guessing the extent of the forest, but to which player the value of that forest would accrue.

The revelation to investors that this technology could allow India-based engineers to work directly with US supervisors on new software products, and those products to prove reliable, is a classic example of sticky luck.  Once the end result is known to be achievable, the long price rise is confirmed.  Prior to that time, the achievement is subject to a probability weighting, which “discounts” the ultimate price less and less as more successes decrease the uncertainty.  Yet the expected price gain in any one year remains the same, as the value of likelihood of the success (which may be very likely) is balanced by the smaller likelihood of a major setback – a sudden thinning of those thick trees we’ve been counting.

Expected Goliath-Slayers

For hi-tech during its bubble years, the stakes get very high.  The potential successes are increasing all the time with new investment.  Not only do we have the likely successes, but also the less likely, greater successes.  One of the possibilities which turned out not to be true after a long run of increasing likelihood, and so contributed in a major way to the sawtooth shape of the NASDAQ, was the supposed destruction of “brick” franchises by “click” franchises.  The fact that conventional businesses reaped  this advantage, by combining their conventional know-how with what proved to be a transferable technology, both reduced expected returns for hi-tech and improved them in retail and other sectors.  Before this outcome became clear, it was understandable that dot-coms were seen by many investors as Goliath slayers.  Sticky luck on this score may have lasted for maybe a couple of years, increasing the expected gains of these new faithful still further. 

On the lower side of the I-shaped probability distribution, we have the sellers.  It may seem particularly strange to claim that all the buyers with their inflated expectations, combined with the sellers, should conveniently average out to the risk-free rate of return.  Surely treasuries are the last thing on the minds of these players, particularly because I have drawn analogies from Ponzi schemes and Las Vegas?  But these analogies serve only to illustrate the risk-tolerance of the players.  We need to remind ourselves that, in terms of freely traded securities, we can assemble the market along a risk spectrum such that each security has a closely definable relationship with the ones either side of it.  In other words, for every security we can find one with a fraction more, and one with a fraction less risk, as perceived by the market.  That relative risk would be evidenced by the spread of the buyer/seller expectations, which is in turn evidenced by the nature of market action.  As we work our way along the spectrum from the risk-free end, there is no point of discontinuity until we reach the most volatile, freely traded tech stock.  There is therefore no point along that spectrum where it would be appropriate to abandon the logic of the SLMH.

Our typical bullish market was characterized by the F shape.  If, for a bubble, we have no concentration at the top end so the distribution looks more like an “I,” then I believe the bottom end is stretched even thinner.  The main body of bulls may be expecting 15-30% returns, while the same number of bears will be stretched perhaps all the way between a negative 20%-80%.  Remember, we are talking about stocks that have increased their market values often by a factor of 20-100, so a drop back to respective factors of 4-20 is certainly possible.  Even a proven industry giant such as Cisco Systems saw its price drop by 80% in a two-year period, though there was no question of it remaining a strong, profitable business.  Many stocks lost more than 95% of their peak value and for many who became convinced of a bubble, this had been expected for a long time.

Why were such people still holding these stocks and selling them?  Again, we must remember the Ponzi phenomenon.  Even those convinced of a bubble were not always adverse to trying their luck, and many such individuals were bound to succeed.  Someone will always win at musical chairs.  An interesting additional factor would be sales by founders and employees with large stock grants.  Of course, we hope that such sellers were not expecting huge future price declines.  Yet their actions may well have mirrored the behavior of such a “rational” investor.  Consider an owner whose stock is currently locked and carries a market value of $500 million.  The individual knows that even a realized value of $50 million will give him or her a future lifestyle previously unimagined.  But $5-10 million would be a different story.  If the market was starting to drop sharply, such a person’s pace of sale might be no different from a group of fund managers who believed this would be their last chance to bail.

Willing Ponzi Players

In a sense, therefore, a bubble creates a much elongated F, or perhaps even a long “P” because the concentration at the top of the range is over a much broader range.  The distribution still tends to drive sticky luck, as in the classic bull F.  As long as news does not disturb the positive climate for the tech revolution, more investors will enter the 20-30% expectation range.  Many will be converts to the tech revolution, but many will be Ponzi players.  Some of the Ponzi players will relish the gamble.  Others will actually hate it, but find it a less painful choice that staying out of the fortune-making machine.  Typically, after a month or so and a 10% gain, these nervous players get more comfortable.  They’ve joined the party.  And if it loses 10% then – hey – they can always get their money back.  (This postpones the agonizing choice when the moment arrives and others are still “buying on the dip.”)

As the bubble progresses, the top end tends not to stretch up but rather to fatten around the 20-30%, range, maybe even dropping down a bit.  The early price leaps are replaced by steadier climbing, as if the market were treating it as a stable phenomenon.  Meanwhile, the range of sellers dig deeper and deeper, more becoming convinced of the eventual catastrophe.  Our P shape is now showing the evidence of steroids.  All this time, the financial media is producing many articles which can be summarized with the word, “Wow!” while offering some space to the bears’ warnings.   A judgment might be passed on their cumulative wisdom if we imagine some initially neutral reader trying to use them to decide precisely what to do.  He or she reads of occasional froth but excellent fundaments, reads of a new world up for grabs, reads of a depression coming of untold proportions.  The debate takes on a religious quality, the investor being asked to choose between two faiths.  If he or she can’t choose, there’s always some homely quote from celebrity advisors.  “Sometimes, ya just gotta close your eyes and jump in.”  Such phrases are not wrong – it’s actually good advice when faced with a dip in a cold lake – they are just meaningless and even pernicious when it comes to the complex world of investment.

Now let’s put the SLMH under the microscope.  At any point in the bubble, it tells us that the market-expected rate of return remains the risk-free return.  So even when the NASDAQ passed 5000, its expected return was qualitatively no different from when it was at 500, or 55 (its lowest point) – only the risk-free return was different.  This hypothesis tells us that the sum total of market wisdom, balancing the rational expectations implied by the sincerity of weight of money, amounted not to a Wow but to a Yawn. 

By itself, this is not a particularly helpful observation.  The steroid P we have described adds the observation that the market is exceptionally unstable.  It could continue gang-busters forever, as long as good news keeps coming in.  But bad news, such as a spike in inflation and the Fed raising interest rates, can cause a wobble that draws in the ultra-grizzlies at the bottom tip of the P.  Some are gambling just as much as the high-end Ponzis, and bunches of them have been hammered by “false signals” on prior dates.  But there’s always another wave ready to come over the hill.  Many of the Ponzis start to turn coats and become grizzlies, just as they had always expected to.  It’s left to the true believers to hold on and keep buying, hoping to be reinforced by fresh battalion of Ponzis who spy a discount.  Anything could happen and, as they say, usually does. 

Instability, Not Inevitability

The end of a so-called “bubble” is therefore not inevitable.   As this book is trying to emphasize, the core difference between the NASDAQ performance between 1994 and 2000, and the entire stock market since conception, is a matter of time.  And in a sticky-luck world, time is quite irrelevant, as we don’t know how sticky our luck happens to be.  It is true that the overall market is much more stable, as represented by the classic F, E and occasional inverted F shapes.  The belief that equities will return 9-12% is entrenched and will be barely shaken for many even by a series of bad years.  Yet it is based on no better science than that of the true tech believers expecting 20-30%, especially those who were looking for a few more years of high returns until the industry “matured.”  There is no reason why the bonanza should not have continued even until today, as “brick” businesses crumbled and people embraced the top dot-com brands.  There might have been a continuum through Google which, sporting a P/E of around 50 despite record-breaking profit growth, maintains the same type of expectation of continuous good news.   The simple fact was that, based on market expectations evidence throughout the bubble, there was clearly a very high risk that the bubble could burst at any time.  Such a level of risk, as we will discuss later, has nothing to do with what I will call “true investment” and everything to do with speculation, which is a nice word for gambling.

The lesson that the SLMH draws from bubbles is that they are a kind of extreme parody of normal stockmarket beliefs.  If we expect a 4-6% equity premium then, well, why not expect a 15-25% equity premium for the next ten years at least?  Averaging out the constant turmoil of the market for the last century surely invites the joke about the man with his head in the oven and feet in the fridge.  If we group years in the return-ranges 30-40%, 20-30%, 10-20%, 0-10%, negative 10%-0% and “below negative 10%” we get a fairly even number of years in each group.   If we chose individual industry sectors, or even smaller companies as a focus, the ranges are much wider.  It makes little sense to question the rationality of the NASDAQ phenomenon without dealing with the underlying misperception of the market as a whole.  When people express their expectations about market returns, and/or invest their money to express their expectations, consciously or unconsciously, they are largely discounting the risks inherent in their investments.  No matter how rational they are being (as I defined the term) their rationalization typically ignores the only reliable data we have about risk – the collective votes of the market.