It’s Only a Flesh Wound
WHEN I THINK of those defending EMH, a striking image comes to me from the English comedy film Monty Python and the Holy Grail. King Arthur and his squire are riding through the forest—well, we hear the sound of horses’ hooves, but actually the two are on foot, prancing along through the trees and meadows—when they find their path blocked by the Black Knight, who demands that the king fight to the death to pass. In the ensuing swordfight, King Arthur lops off one of the Black Knight’s arms, then the other, but the knight refuses to yield. “You haven’t got any arms left,” the king points out. “Look!”
“What! Just a flesh wound!” the knight retorts. The battle continues, and King Arthur disposes of both of the knight’s legs. Unyielding, reduced to mere head and torso, the knight still won’t give in. “The Black Knight always triumphs!” he bellows bravely. “Come back here and take what’s coming to you. I’ll bite your legs off!”
As this chapter will show, EMH is in a spot not all that dissimilar, refusing to yield no matter how battered.
Interestingly, the historical reality of England’s King Arthur has never been satisfactorily established. It’s just not verifiable history. Yet in grand novels, poems, plays, children’s books—even the satirical deflating by Monty Python—his legend is secure. With EMH we have a plethora of data, and it ought to have been simple enough to establish—or refute—the validity of its “legendary” findings by now. Yet, unlike that of King Arthur’s tales, the historical basis of EMH has undergone considerable revisionism, and with each updating, the base of its statistical observation has become shakier.
In the previous chapter I described how EMH swept through academia in the 1960s and then took Wall Street by storm. Like George Patton’s Third Army roaring through Germany in 1945, the efficient-market hypothesis overwhelmed the obsolescent weapons of Wall Street’s technicians and fundamentalists with its seemingly invincible new weaponry of powerful statistical analysis and mathematics. Because academic findings clearly showed that money managers could not outperform the market, a trillion dollars flowed into funds based on various indexes, from the S&P 500 to the Russell 2000.*24 Owing to the scope of their victory, some academics even expressed concerns that the markets might not continue to be as efficient as the realization spread that money managers and analysts could not beat the market and as a result would probably be laid off. Since these managers and analysts were essential, according to EMH, to keeping markets efficient, too many such layoffs would make them less so. This was a bad dream for those of us in the investment field but, as it turns out, only that. This chapter and the next should demonstrate that it is actually built on sand and will show some of the reasons why. In our journey we will see much of the supposedly powerful statistical documentation of the theory crumble, because either the tools did not do what they claimed or the researchers ignored or downgraded powerful data that refuted their claims.
There is a clear disconnect between real-world results and the predictions of the distinguished academic pioneers who formulated EMH. In this chapter, after we have compiled a solid reference base of major market events that refute EMH’s basic premises, we will turn to fundamental flaws in the analysis used to buttress the theory. As we’ll see, when the EMH blinders come off, the lessons are noteworthy.
Like the Black Knight’s predicament, it isn’t going to be pretty, but it will clear your path to future investing success. Just as the Black Knight loses one arm, then the other, then both legs, yet vows to fight on, EMH is going to lose one support after another yet remain—you guessed it—the academic theory that trumps all others.
Now we’re going to examine in detail three market events that EMH adherents said could not have happened. With all the financial bloodshed, a few lessons should have been learned, but that was not the case. They are:
1. The 1987 stock market crash
2. The 1998 Long-Term Capital Management debacle
3. The 2006–2008 housing bubble and market crash
1. The 1987 Stock Market CrashThe crash of 1987 was to that time the worst market panic since 1929–1932. The seeds were planted in Chicago in the early 1980s. The Chicago commodity exchanges were eager to expand their business away from wheat, soybeans, cattle futures, livestock, and other commodities. Hungriest of all was the Chicago Mercantile Exchange (the Merc), which had a reputation over the years of cornering markets and performing other high-wire acts that fell on the wrong side of the law. Over its history many attempts had been made to close it down. Scandals abounded, particularly in the onion pit. Onions were one of the major commodities traded, and as a result of the corners, squeezes, and other illegal activities, Congress finally legislated the end of trading in onion futures. The exchange limped along, with a seat in the 1960s and ’70s costing only a pittance.
That all changed in the span of a little over a decade. The Chicago exchanges, led by the lowly Merc under its dynamic chairman, Leo Melamed, were transformed from trading grain, cattle futures, and pork bellies to playing a key role in the U.S. stock and bond markets. Behind the radical reorientation of their business activities were a number of major EMH academics. Not coincidentally, most of the professors were at the University of Chicago, one of the strongest bastions of laissez-faire in the country. The academics believed that financial futures gave markets far more liquidity, providing what they thought would be much broader markets and lower trading costs, thereby enhancing markets’ efficiency.
The star of the show was the S&P 500 futures, introduced by the Merc in April 1982. Most commodity traders thought it couldn’t be done, because futures trading was commonly considered to be a form of gambling. Futures trading, because of its speculative nature, had never been allowed to interact with stock trading. Such a reaction, most investors believed, would result in greater volatility in the stock market. Even leaders in the futures industry believed that was the case. Walter E. Auch, then the chaiman and CEO of the the Chicago Board Options Exchange (CBOE), wrote a letter to the Commodity Futures Trading Commission (CFTC), the country’s top commodities regulator, warning of the potential for “sophisticated manipulation and that index futures are a dressed up form of wagering.”1
The danger was very real. We know that a major cause of the 1929 crash was excessive margin trading at razor-thin margins of 10 percent. In the congressional reforms of the early 1930s, Congress gave the Federal Reserve the power to raise margins on stock purchases, so it could never happen again. And the Fed used this power. Stock margins were never under 50 percent and have been raised in more speculative markets to as high as 100 percent on occasion in the post–World War II period. Even so, margins on stock futures today are much lower than stock margins, normally 5 percent prior to the 1987 crash and now about 7 percent.
Commodity margins were about one-tenth as high as stock margins in 1987, well below the low margins blamed for the 1929 crash, more than wiping out a good part of the congressional reforms regulating margin trading after the 1929 crash. The commodity exchanges had strong academic support from the professors because of the latter’s fixation on more liquid markets while entirely disregarding the dangers of very high leverage.
Sharp drops or crashes have often occurred in the past in both commodity and stock markets when margin requirements were too low. So, through the back door of financial futures, aided by powerful believers in EMH, the Merc and the CBOT could buy or short stocks at margins lower than those in effect in 1929. Players on the commodity exchanges—and they included large numbers of Wall Street firms and hedge funds—could leverage their positions almost ten times as high on stock futures as they could when buying stocks themselves. Since stock futures trading was about double the dollar amount of trading on the NYSE, the tail of S&P 500 futures could most definitely wag the dog, the stock market itself. Not to worry, said the professors, ignoring the numerous collapses of commodity markets in the past, it can’t happen today. Markets are efficient, and index arbitrage, an offshoot of futures trading, will make them even more so.*25
When the Merc applied to the CFTC for permission to trade S&P 500 futures, the exchange, along with powerful academic backing, made a strong case that movements of S&P 500 futures would not initiate movements of stocks in the index. This was a prediction that would cost investors many hundreds of billions of dollars by linking the speculative culture of the commodity exchanges to the far more conservative floor of the New York Stock Exchange.
The Mercantile Exchange knew it had a huge moneymaker in stock futures. It launched a giant promotional campaign featuring the S&P 500 futures, ran full-page ads in The Wall Street Journal, and hired celebrities such as Louis Rukeyser, the host of the TV show Wall Street Week, to promote the idea, as well as holding heavily attended seminars across the country conducted by some of the best-known EMH theorists to explain the benefit of S&P 500 futures to leading money managers.
The promotion paid off. By the end of 1987, trading in S&P 500 futures alone was over $300 billion a month, about double the $153 billion traded on the NYSE. The CBOE trading of the S&P 100 (a compact version of the S&P 500, limited primarily to the highest market caps in the index) amounted to another $2.4 billion.2
From being a center of trading eggs and pork bellies, Chicago had become one of the world’s largest financial markets. And the Merc controlled 75 percent of the stock index market.3 Reflecting the seemingly endless prosperity in its financial instruments division, the value of seats had climbed from a pittance to $190,000 in eleven years.4
Then there was index arbitrage (also called program trading), which allowed S&P index funds and scores of other major institutions to buy or sell either the S&P stocks or the S&P futures if the prices of either one got out of line with the other. If, for example, the value of all the stocks in the S&P 500 was at 250 and S&P futures were trading at 252, an alert institutional investor could, using computerized trading, quickly short sell the S&P futures and buy the stocks, locking in a return of 0.8 percent before commissions. When the futures and the S&P index went back to their normal value, the transaction would be reversed. Such a small return seems hardly worth the effort, but if the sums were large, say $100 million, if the purchases were on minuscule margin, and if the transactions were repeated many times in a month or two, the profits could be very large.
PORTFOLIO INSURANCE: THE FINAL COMPONENT OF THE CRASH
Portfolio insurance was a product designed to protect the capital of institutional investors in a down market while giving them all the upside in a rising one. In brief, it was a way to have your cake and eat it too. First of all, it was not insurance at all, although it was slicky marketed as such. It purported to protect an institution’s portfolio, if markets went down, by short selling S&P 500 futures. The more the market dropped, the more futures would be sold, progressively lowering the institution’s stock exposure to the market.*26 If the portfolio dropped 3 percent, the computers of Leland O’Brien Rubinstein Associates and other portfolio insurance firms, which licensed their model, would sell futures akin to 10 percent of their portfolio. If the S&P went down another 3 percent, another 10 percent of the futures would be sold. If the S&P subsequently went up 3 percent, the 10 percent futures position would be repurchased and little would be lost, and so on.
If the price of the S&P 500 went down, the futures would be sold, not the stocks of a pension fund, a hedge fund, or any other institution that owned them. Futures were considereded exceptionally liquid, and, markets being totally efficient according to EMH, could be sold in the blink of an eye. According to its adherents, it was a perfect system, said to maximize market gains and protect against losses, supposedly at only a small cost to the owner.
Why? Because the S&P futures had infinite liquidity. This is a central belief of efficient marketers and the core concept of portfolio insurance. If markets went down, swarms of sophisticated buyers would come out of the woodwork and immediately buy the futures at lower prices. If the market went still lower, even larger hordes of buyers would be there to scoop up the depressed values. After all, a cardinal EMH belief was that since markets were entirely rational, increasing numbers of buyers would appear as prices declined. End of discussion.
“Liquidity begets liquidity,” the academics chanted. But lo and behold, they turned out to be all wet.
Did portfolio insurance actually protect a portfolio? Well, no. It would lessen the institution’s losses if executed well, but it could not prevent them, nor was it designed to do so. Moreover, if a market was quite volatile it might end up costing big, even if prices did not move much, because of the small losses and commissions generated by frequently getting into and out of the market.
The keen-eyed Barron’s editor Alan Abelson cut through the hype immediately. “It is an exotically labeled version of the small speculator’s stop-loss order,” he wrote. Under its complex mathematical formulas, it was simply another market-timing device. The previous chapter briefly discussed the uninspiring record of market-timing products, but as with so many others, this one, with the backing of academics steeped in EMH lore, became wildly popular. The consistency of academic thinking on market timing might seem a touch questionable here.
The mathematical calculations for portfolio insurance were based on the Black-Scholes Option Pricing Model, which for sheer complexity possibly rivaled the mathematical formulas designed to launch a space shuttle. Designed by Fischer Black and Nobel laureate Myron Scholes, this method soon became the standard way of pricing stock options. Hayne Leland and Mark Rubinstein, both in the Department of Finance at the University of California at Berkeley, adapted the model to portfolio insurance. Leland was known as the father of portfolio insurance, partly because of an article published in 1980 in the Journal of Finance, the most prestigious academic and pro-EMH journal.5 Behind the awesome mathematics was a disarmingly simple but fallacious idea: you could all but guarantee yourself against downside by eliminating risk when the market dropped, clients were told, while reaping the benefits of a bull market by keeping a larger percentage of the portfolio in stocks.
Major pension and other institutional funds were keen to line up to participate in this sure thing. At one New York investment conference in the summer of 1986, the number of institutional investors who wanted to attend a workshop on portfolio insurance became so large that the workshop was expanded into the entire meeting. “It was madness,” said John O’Brien of Leland O’Brien Rubinstein.6 But it was madness he liked, as his firm was reeling in tens of billions of dollars of institutional assets that it managed. According to the Brady Commission report on the 1987 crash, $60 billion to $90 billion of funds were invested in portfolio insurance programs just prior to the crash.
PREVIOUS WARNINGS IGNORED
Something was wrong. Perhaps it seemed coincidental at first, but the vast growth of index arbitrage, portfolio insurance, and index and stock options didn’t do what the efficient-market advocates had assured regulators and the public they would: decrease market volatility. Quite the opposite: there were violent stock market downturns of almost 100 points, first on July 7 and 8, 1986, and then came a minicrash on September 11 and 12 of the same year, followed by another near-collapse in the averages of almost 100 points in late March 1987. Concern began to mount among a number of senior investment professionals, including John Phelan, the president of the New York Stock Exchange. I wrote a column in Forbes entitled “Doomsday Machine,” with the subtitle financial index features + program trading*27 + low margins = potential disaster. The article, published on March 23, 1987, described in detail how the interaction of index arbitrage and portfolio insurance would cause a crash. Unfortunately, it happened pretty much as described six months later.
Because of the Forbes article, I was invited to sit on a panel with some eminent academics, the majority of whom strongly backed portfolio insurance and index arbitrage trading techniques. Also present were three commissioners of the SEC, all believers in efficient markets. The conference was held at the University of Rochester, New York, a bastion of EMH, in June 1987. Almost to a man, the prestigious academics on the panel scoffed when I spoke and stated why I felt a market crash could happen. Some of the great men snickered; others merely yawned politely. Who was a mere Wall Street money manager to debate with professors of their stature?
Worse was in store for the two panelists holding views similar to mine. Robert Shiller, whom we met earlier, was taken to task and practically called a heretic. “With your training, how can you subscribe to such ridiculous views?” a member of the audience demanded. Jay Patel, then a professor of finance at MIT, received similar treatment. Despite three sharp downturns caused by the violent interactions of index arbitrage and portfolio insurance, those vehicles were not only given a clean bill of health at the meeting but were considered essential to keeping markets efficient. Then the unthinkable happened.
THE CRASH THAT WAS THEORETICALLY IMPOSSIBLE
What surprised me about the 1987 crash was the ferocity of the decline, in spite of what I knew about the dangers of the interaction of portfolio insurance and index arbitrage, as well as the tens of billions of dollars in play. The darkest scenarios I could envision didn’t even come close.
Although many explanations were bandied about, there were no major events responsible for this crash, nor was the market wildly overvalued. Sure, there was some concern in the marketplace—there always is—but the anxiety level was below amber. What was disturbing was that a long-overdue correction was distorted into a disaster by the new S&P derivatives, which in times of rapidly falling prices magnified the drop sharply. That’s exactly what happened on Black Monday, October 19, 1987. The result? A minor correction in the Dow turned into a 508-point panic for the day. Wow.
The Dow Jones plummeted 22.6 percent on Black Monday alone, a plunge almost twice as large as the percentage drop on Black Tuesday, October 29, 1929. It started on Wednesday morning, October 14, 1987, with the Dow just over 2,500. By noon the next Tuesday, October 20, the Dow was slightly above 1,600, a decline of more than one-third. It was the worst crash in U.S. history to that time. (The 508-point drop on October 19 was only 60 percent of the total decline.)
What created this disaster? Let’s look more closely at the role of portfolio insurance and index arbitrage during those five terrifying days. A number of studies on market volatility, which examined index arbitrage and portfolio insurance, had previously been commissioned by the commodity exchanges after the sharp 100-point drops previously discussed. Those “impartial studies” were performed for the exchanges by consultants salivating at the giant commissions the programs were bringing them. The studies, like others we will examine later, were flawed, as they covered short and relatively quiet market periods.*28 (Remember the law of small numbers.) The researchers concluded that the interaction between the two would not affect market volatility. Famous last words.
Who started the selling? Computers, followed by humans in shock. What looks good in the lab can act like nitroglycerin when shaken. Unfortunately, the nitro was shaken. Bam! Crash!
The S&P was down 3 percent on Wednesday, October 14, and the portfolio insurance formula went into action. Leland O’Brien Rubinstein and Wells Fargo began to sell futures by October 14 or 15 as prices fell more than 3 percent. Still the S&P futures stayed at a small premium to the S&P, in line with where they were expected to be.*29 On Friday, October 16, the S&P 500 Index took a sharp drop of more than 5 percent and the futures went to a minuscule discount to the S&P 500 stocks, of less than two-tenths of 1 percent.
One would think that the EMH gurus running the portfolio insurance money management firms would have been elated with how well their portfolios were performing in a rapid market downturn. The truth was that they were terrified. The liquidity of their catchphrase “Liquidity begets liquidity” was starting to dry up. Buyers of futures were becoming increasingly scarce, and they lowered their bids as the decline in S&P futures increased. EMH theory said that this was impossible, but it was happening. The result was that the portfolio insurers could sell only a small fraction of the S&P futures their formulas called for. By Friday, October 16, with an estimated $60 billion to $90 billion in portfolio insurance and sales far behind the PI formulas required, it would turn into a serious problem if the market went lower the next week. But what if the unimaginable happened, EMH liquidity theory was wrong, and liquidity dried up? The problem would become a nightmare.
The professors at the portfolio insurance firms may or may not have known about another equally devastating problem. Like the British who used the Enigma machines in World War II to decipher the most important German military codes, thus learning exactly what the enemy would do, the major brokerage houses and S&P futures traders also knew almost precisely how much the portfolio insurance managers still were behind in their futures selling. It wasn’t nearly as complex as Enigma to decode. Remember, if the market dropped 3 percent, the insurers were supposed to sell 10 percent of the futures to reduce the equity exposure to the predetermined lower level in order to remain delta neutral (the level of stocks and bonds the formula called for).
The academics turned portfolio insurers made another small error. They didn’t count on how cutthroat the brokers and the futures traders who acted for them, as well as other players, could be. After all, that wasn’t factored into EMH theory. But everyone in the game knew the portfolio insurance managers were well behind the predetermined selling they were required to do. If the other brokerage houses and traders sold futures en masse or shorted stocks quickly early on Monday, they would get the jump on the portfolio insurers and make jillions buying the futures back at much lower prices. The stage was set.
On Black Monday, October 19, 1987, the impossible happened: liquidity dried up completely. The market opened and began to drop rapidly, with heavy S&P 500 futures selling leading the way, dropping 3.5 percent on the first trade. Every knowledgeable pro was shorting S&P futures. As the futures dropped, computerized program traders (index arbitragers) rushed in, buying the discounted futures at increasingly lower prices and selling stocks, dropping their prices sharply. This forced the portfolio insurers to sell futures even more frantically at increasingly large discounts to the value of the S&P 500 as they fell further and further behind the amount they had to short to protect their clients’ portfolios. The death spiral continued. Major investment houses and commodity traders, knowing the desperation of the portfolio insurance managers, continued to short futures ahead of the portfolio insurers. The portfolio insurance managers were forced to sell at any price to realign their portfolios. So utter was the collapse of portfolio insurance that as the market continued to free-fall, the theory blew apart completely. S&P futures traded at such a large discount to the S&P 500 that portfolio insurance managers were forced to sell their clients’ stock, which they had never conceived of selling under any circumstances. This pushed the S&P stocks down even further.
This doomsday interaction between portfolio insurance and program trading continued through the day and was strongly reinforced by larger and larger amounts of selling by institutional and individual investors reacting to the panic and stampeding for the exits. Prices dropped more than ever before in modern times.
The panic had spread like a rampaging forest fire out of the futures pits of Chicago into the stock market itself, where it sharply magnified the impact. The crapshooting spirit of the commodity pits had been injected into the floors of the country’s major stock exchanges, with devastating results.
THE IMPOSSIBLE HAPPENS
The S&P 500 was down 20.5 percent at the close on October 19, and the S&P 500 futures dropped 28.6 percent; this left them at a 23.3-point discount (10.4 percent) to the S&P 500. According to EMH theory, futures cannot ever fall below the cash price for the same expiration date (in this case the end of December 1987). The reason is simple: when an investor buys a stock or the S&P 500 on margin, he or she has to pay the broker an interest charge to carry it. The interest (about 5 percent at the time) is priced into the S&P 500 futures contract, so it must always be at a premium to the cash price of the S&P itself. This should apply even in a panic if people are rational. If the S&P 500 futures contract goes to a discount, the trader makes an automatic profit by selling the S&P 500 stocks and immediately buying the discounted futures. When the futures contracts expire less than two months later, he pockets his gains.*30
But as we saw the S&P 500 futures didn’t stay at a premium; they dropped 10.4 percent below the cash price. This gave knowledgeable investors such as index funds and other investment firms with cash an incredible return. They simply had to buy the future and sell or short sell the S&P 500 stocks instantaneously.
Let’s go through the mechanics to see how this was done. Since they had to put only 5 percent down on the futures because of the ridiculously low margin requirement, they made nearly 228 percent on the money they actually put down in margin, on an absolutely safe, completely hedged investment. When the contract expired in late December 1987, they would sell the S&P stock portfolio at the same time the futures contract expired; this is rudimentary index arbitrage. At expiration of the futures’ contract, the price of the S&P futures, bought at a large discount to the cash price, would rise to the price of the S&P 500 stock index, capturing the full original 10.4 percent discount on the S&P 500 futures.
Take the example of an institution or brokerage firm that bought $10 million of futures for its own account. It would have put up only $500,000 in margin and would come up with $1,137,900 in profit on the contract’s expiration, or the 228 percent shown before.*31 This action makes a mockery of the omnisciently rational investor of EMH theory.
As noted, this is the type of riskless, high-return transaction that EMH theorists state can never happen in an efficient market. Occurring in one of the most widely traded, carefully followed markets in the world, large, riskless profits available to knowledgeable investors are a very serious challenge to EMH. No explanation by the EMH theorists, to my knowledge, has ever been forthcoming. This event also puts an enormous dent in Professors Roll’s and Fama’s theory of rational crashes, which we’ll look at shortly.
As I see it, many of the major pillars supporting the efficient-market hypothesis were destroyed in the 1987 crash. Five should be noted.
1. Liquidity dried up. A crucial assumption of EMH, that there is always sufficient liquidity in markets, was disproved, as the above events indicate. The lack of understanding by the academics and the portfolio insurance managers of liquidity was a primary cause of the 1987 crash.
2. The argument that rational investors keep stock prices in line with their value, another core assumption of EMH, was seriously challenged. When was the market efficient? When professional and other sophisticated investors took the S&P 500 down from 315 to 216 (31 percent) in five trading days or when it recovered all of its losses nineteen months later, with only minor changes in the underlying fundamentals?
3. Another example of glaring market inefficiency was the 28.6 percent drop in prices of S&P 500 futures to the actual 20.5 percent drop in the price of the S&P itself on October 19, allowing savvy investors to make gigantic profits on their capital in two months. The cornerstone of EMH theory states that such actions by rational investors are impossible because of their automaton-like rationality.
4. The EMH offspring, CAPM, states that risk is defined solely as volatility. The only way to lower risk is to lower volatility. But the risk that caused the 1987 crash was not volatility. The panic was caused by a serious lack of liquidity as the futures market dried up, as well as enormous excess margin. Both are measures of risk that are not part of EMH risk theory and therefore are excluded from it. This prodigious flaw in risk measurement is vitally important to your investment decisions. (Solutions will be discussed in chapter 14.)
5. EMH theorists thought that increased leverage would facilitate more efficient markets by strongly encouraging futures trading on stocks at low margins. These academics played an important role by having their recommendation to drastically lower stock future margins about 90 percent below stock margins accepted by the regulators, the SEC, and CFTC. They apparently did not consider that in a major downturn low leverage could unleash massive selling that could cause markets to plummet as they did both in 1929 and again in 1987.
What lessons did EMH theorists, as well as true believers, including then Fed Chairman Greenspan, learn from this crash? As noted, none. The theorists tried to explain away all the causes, although their explanations ranged from skimpy to downright foolish. As a result, the mistakes were repeated and contributed to two more market collapses, as we will see next.
2. The 1998 Long-Term Capital Management DebacleYou’d think that after the 1987 crash EMH would have undergone some serious revisions if not outright rejection by Wall Street analysts, as well as questioning by its adherents. But that didn’t happen. By 1998, a new crisis was beginning to reach the boiling point, owing to the actions of a monster hedge fund’s investment strategies. The firm was “too big to fail” long before the term became popular. The mixture of EMH theory, the increasing belief in the almost godlike investment capabilities of rising efficient market superstars, and serious amounts of money produced a crisis that was stunning in both its speed and its scope.
Long-Term Capital Management (LTCM) was the world’s largest hedge fund. Beginning operations in March 1994, by early 1998 it had acquired assets of more than $100 billion, as well as more than $1 trillion in derivatives. More than fifty of the largest banks and investment banks in the United States and abroad scrambled to do business with it in spite of the almost impossibly tough terms it demanded, concessions that no other hedge fund was given. By 1998, it was the envy of Wall Street, more than quadrupling its original investment in less than four years.
LTCM, led by its chairman, John Meriwether, was considered the crème de la crème for the exceptionally high level of its traders, but mostly because it hired some of the superb efficient-market superstars, led by Robert Merton and Myron Scholes, the latter of whom was instrumental in developing the Black-Scholes model. They shared the Nobel Prize in Economics in 1997. In addition, a group of brilliant Ph.D.s, several of whom were excellent traders, surrounded the two masters. On paper there wasn’t another firm with this kind of dazzling cast, as its record from the start seemed to prove.
LTCM concentrated on “relative value” trades in both domestic and global bond markets. If two high-quality bonds, for example, had almost the same maturity but one yielded 25 basis points (one-quarter of 1 percent) more than the other, LTCM would buy the higher-yielding bond and short the lower-yielding one. Or if a highly rated bond in Spain provided a higher yield than one in the United Kingdom, again with nearly the same maturities, the fund would buy the Spanish bond and short the U.K. issue. These were called “paired trades.”
The fund was also highly diversified, owning and shorting thousands of issues. Another feature of LTCM’s strategy was to buy somewhat riskier and more illiquid bonds in its trades than the ones it shorted to increase the spread. This increased the return on each paired transaction, as less liquid and slightly riskier bonds commanded a somewhat higher yield than bonds with the same risk and liquidity. LTCM believed that this was a low-risk strategy because interest rates tend to rise or fall in sync, so spreads move only a fraction as much as the value of the bonds themselves; LTCM should fare well no matter whether bonds rose or fell or even if the market crashed. One of the academics calculated the risk in a spread transaction at only about 4 percent of owning a bond outright.
The paired-trade strategy that was a good part of LTCM’s portfolio was in essence a nickel-and-dime business. Myron Scholes, aside from being an outstanding academician, was also the firm’s top marketer. As he explained it, “the fund would be earning a tiny amount on thousands of trades as if it were vacuuming up nickels that nobody else could see.”7 In essence it would be like a giant penny arcade making big money on the volume of nickels and quarters thrown into the wide variety of game machines on the premises.
The confidence so many felt in the strategy was premised on work by Robert Merton, who was considered one of the outstanding experts on risk. He had made major breakthroughs in EMH theory in risk, which eventually earned him the Nobel Prize. Merton was convinced, as were almost all EMH believers, that volatility was the sole measure of risk; this was the bedrock of LTCM’s approach. He was equally sure that volatility remained stable over time. If a stock or bond had a certain volatility, it might swing higher or lower temporarily but would always return to its calculated rate. Since that was the case, LTCM could use volatility as its most important tool. If volatility was higher than it should be for the bond bought in a pair trade and lower than normal for the one sold short, it would return in each case to its normal level. The higher the volatility on the bond purchased and the lower the volatility on the bond sold, the greater the added return to the trade when the risk swung back to its normal level. That this assumption was never proved was of no consequence.
The strategy was also premised on the belief that volatility was mathematically predictable. A large amount of testing was done on volatility, as well as the chance that something could go wrong. Using the cardinal Merton principle that volatility did not change, LTCM was convinced that it could calculate precisely the odds of what the best, average, and worst days would return, as well as the odds that the portfolio could take serious or mortal losses. Even worst-case calculations showed that the firm could sail through the most punishing financial hurricanes.
The belief that volatility was mathematically predictable was not held only at LTCM; it was a core belief throughout the Street. The Black-Scholes pricing model was anchored on the predictability of volatility, and trading rooms on Wall Street and in every major financial center globally monitored volatility as if it were the Holy Grail. Every major trading floor was staffed by bright young Ph.D.s who had studied under Fama, Merton, Scholes, or other strong EMH believers, and they didn’t question the unproved premise that yesterday’s prices were reliable and predictable indicators that would determine today’s value. When Genius Failed, Roger Lowenstein’s first-rate book on Long-Term Capital Management, quotes Peter Rosenthal, LTCM’s press spokesman, as glibly stating “Risk is a function of volatility. These things are quantifiable.”8 “Meriwether, Merton, Scholes and Company had no more earnest belief.”9 The LTCM portfolio contained thousands of paired trades with precise data on the volatility and expected return of each.
THE FAIL-SAFE STRATEGY
What the professors and traders didn’t focus on was leverage or liquidity. Since they had volatility completely under control and that was the only source of risk, liquidity and leverage did not matter a hoot. So focused were they on volatility, and so strong was their belief that volatility was risk, that leverage and liquidity as independent risk elements were considered inconsequential. They were not even a punctuation mark in the EMH-inspired formulas LTCM used.
The question most often asked by LTCM academics and portfolio managers was how much volatility (“Vol”) it took to optimize returns. The answer that almost consistently came back was that the Vol could be raised, with little addition to risk. The leverage went from 20 to 1 to 30 to 1, but Vol, they believed, could still go higher.
The gods continued to smile on Long-Term Capital Management. In 1994, it earned 20 percent; in 1995, its net return was 43 percent. By the spring of 1996, it had $140 billion in assets under management, and its capital had tripled to $3.6 billion. After only two years of operations, its assets were larger than those of Lehman Brothers or Morgan Stanley and were approaching those of the giant Salomon Brothers. In 1996, it earned 41 percent net of fees or $2.1 billion, more than giant blue-chip growth companies such as Walt Disney, McDonald’s, and American Express.
But there were other somewhat less appetizing aspects to this sizzling growth. By early 1996, the firm’s leverage had, as noted, climbed to 30 to 1. Leverage works well, as we saw, when markets are going up, as they were before the 1929 and 1987 crashes, but when markets go down, it’s death. At 30-to-1 leverage LTCM had to lose only 3.3 percent of its market value to have its capital wiped out entirely. Meanwhile, its return on total assets was less than 2.5 percent, before counting its large derivative positions in the many hundreds of billions of dollars. Including those, it was probably less than 1 percent.10 A ninety-day Treasury bill at that time yielded 4.5 percent, which was approximately 4.5 times LTCM’s return on total assets. Almost all of LTCM’s return came from levels of leverage that defied gravity.
Then, in mid-1997, the Asian economies began to melt, first Cambodia, then the Philippines, then Malaysia, then South Korea, followed by Singapore and Indonesia. Enormous amounts of stock were dumped. And markets crashed while currencies went into free fall. The Asian Tigers became terrified kitty cats. The contagion spread to South America, Eastern Europe, and Mother Russia.
LTCM determined to make its signature bet in the crisis. Because volatility was very high, the company decided to short sell volatility options not only on the S&P 500 but on major indexes in Europe and other major markets.*32 Volatility, Merton and the group were certain, would revert to the mean, and this meant that volatility futures would fall sharply. And here the biggest error in volatility measurement LTCM ever made mortally wounded the fund.
Merton was taking an enormous chance. EMH theory, the Black-Scholes model, and Merton’s models say only that a stock’s volatility is consistent over time. They do not say in what time period volatility securities or derivatives will revert to the mean. It’s like crossing a river that’s four feet deep on average, carrying a fifty-pound backpack: it might be three feet deep in some places and fifteen feet deep in others. Not good survival odds, but precisely the odds Merton the supermathematician had chosen.
In a bad crash or a bear market, would it take six months, twelve months, or even years before volatility went back to its normal level, as Merton and EMH believers fervently believed would occur? The efficient-market theory had no answer for that. How could it have one? The belief appears to have come from an EMH theory, not rigorous testing. But LTCM was leveraged 30 to 1, so the return to normal volatility had to come very soon, because leverage—not recognized by EMH as a risk factor—will gobble capital up almost at the speed of light if the markets continue to go against it. Unfortunately, that’s exactly what could happen to LTCM. Merton and Scholes were making the same kinds of bets that any desperate amateur deeply out of pocket might make: LTCM could fail on the toss of a coin.
Maybe the gods were not major EMH adherents after all. LTCM’s spreads on its paired trades did not narrow; they widened. Through 1998, a flight to safety occurred in almost every sector it was invested in. Remember, the firm was always invested in the riskier, not safer, bonds and was short of the safest bonds. To add to its problem, the volatility indices it short sold skyrocketed as volatility increased. In May, problems with the Asian Tigers flared up again. By early June, the Russian financial system was near collapse. World markets turned down sharply. LTCM was hit even harder because the dash to the safest securities rapidly widened the spreads between its long holdings and its short positions, while volatility increased further.
LTCM reported a loss of 18 percent for the first half of 1998. More important, as its capital dropped, its leverage increased dramatically, making it less and less able to meet margin calls. Then, in August 1998, Russia defaulted on its debt and market fear heightened across the board. LTCM’s capital of more than $5 billion near year-end 1997 fell to the hundreds of millions within four months. The two risks not even considered punctuation marks by EMH theorists and by Merton and Scholes—leverage and liquidity—came to the forefront, just as they had done in the 1987 crash.
As the markets tumbled, the enormous short positions the firm owned resulted in gigantic losses; the increasing flight to safety continued to cause the more risky bonds it held to drop significantly more than the higher-quality bonds it had shorted in the paired swaps. Too, the volatility swaps that Merton and his team had shorted heavily because they believed Vol was much too high soared higher. Calls for more margin poured in to cover the flood of new losses, and consequently the firm’s capital was hemorrhaging rapidly.
As a result of the firm’s gigantic margin calls and its inability to sell most major positions because they were very illiquid, the fund’s leverage shot up to 100 to 1, which meant that even a 1 percent drop in assets would bankrupt it. But it couldn’t sell to protect itself because its positions were gigantic and always less liquid than the positions it sold short. In the good times its capital, enormously magnified by leverage, made it huge profits. But in those brutal markets, selling even a small fraction of any holding would reduce prices sharply (lack of liquidity again). LTCM was doomed!
August was a cruel month for Long-Term Capital Management. It lost $1.9 billion, or 45 percent of its capital. It had $155 billion in assets, with a leverage ratio of 55 times its shrunken capital. Mathematicians calculated that the odds of the losses LTCM incurred in August were so freakish as to be unlikely to occur over many repetitions of the life of the universe.*33 11 Its position was untenable. The leverage could not be reduced because of the enormous size of its trades and the complete loss of liquidity. As with subprime bonds almost a decade later, any attempt to sell would see the already wafer-thin markets for the securities it held collapse.
The markets were in a state of near-panic. Meanwhile, LTCM was surrounded by a pack of predators: bankers and brokers who knew that its liquidity and leverage problems would put it under. They began shorting LTCM’s positions, well aware that in a forced liquidation, when it was compelled to sell, prices would drop drastically and the bankers could cover their shorts at bargain prices. The parallels between the portfolio insurers in 1987 and LTCM are remarkable. Both were undone by a massive lack of liquidity when it was most needed, in a bear market.
By September 1998, the Federal Reserve Bank of New York, under William McDonough, its talented president, was concerned about the plight of LTCM. Although he had no authority to inspect the books of a hedge fund, LTCM gave the New York Fed permission to do so. What he saw alarmed him. Not only did he see that the collapse of LTCM was imminent; he also realized that the enormous positions in many thousands of holdings, if dumped on the market to sell at any price, could severely disrupt the already badly shaken financial system and possibly lead to disaster. He and his chief aides called numerous meetings with the leaders of the largest banks and investment firms in the United States, as well as important banks abroad that held large LTCM loans against the securities swaps and other holdings of the fund.
An agreement to take over all of LTCM’s positions would need the support of amost all of the major banks and investment bankers on Wall Street. In the end, after much haggling, its positions were sold to a consortium of sixteen banks that anted up more than $260 million each. The fund’s shareholders saw their investments drop 92 percent in five months. By comparison, over the four-year period that Long-Term Capital Management existed, the S&P 500 had doubled.
Despite this massive failure of EMH, neither of the two Nobel laureates who had championed the fund’s strategy questioned the theory. Although Merton admitted that the fund’s risk measurements hadn’t worked, he stated that the principles it had followed were right. What was needed, he argued, was more sophisticated modeling. He went back to teaching at Harvard and, perhaps ironically, was hired by J. P. Morgan as a risk consultant.
In a speech a year later, Scholes concluded that the change in volatility must be attributed to a permanent change in what investors would pay for the more risky investments LTCM made. This meant that all the theory about volatility that had been used up to then must have changed permanently by events at the time LTCM went down, which is not unlike saying that the weight of the supports necessary to build an expansion bridge of a certain length and width had suddenly and permanently been altered by a sudden change in the laws of physics. Scholes never doubted the efficacy of EMH’s supporting volatility theory. Since the permanent changes he discussed were reversed within a few years, his theory may have a few minor holes in it.
Indeed, no questions were raised by EMH supporters generally about LTCM’s premises on volatility or whether leverage or liquidity was also a possible risk factor. How could they be?
3. The 2006–2008 Housing Bubble and Market CrashBy now we are all familiar with the housing bubble of the early to mid-2000s. The interactivity of so much of our financial system and the complexity and the unethical practices carried out by far too many of the large institutions involved are well beyond the scope of this work. What can be sketched out briefly is the part EMH theory played in fueling this bubble to the gigantic proportions it reached. This crisis was not dissimilar to the destruction of Long-Term Capital Management but on a colossal scale.
In spite of the 1987 crash and the LTCM debacle, investment institutions still had almost blind faith that volatility was the sole measure of risk. Leverage, although extremely high on subprime and other lower-quality residential mortgage-backed securities (RMBSs),*34 was of almost no concern to the portfolio managers or the risk-control departments of these institutions, who were all trained in the EMH and CAPM theories of risk. Nor, for that matter, was their liquidity questioned. There were many thousands of series of home mortgages, whose quality varied enormously, from good to very poor. Normally liquidity was low, because each mortgage issue usually contained a number of series of RMBS issues ranging from AAA, the highest rating, to series that were toxic at best. Most required substantial analysis to determine even a rough price range, so dealers’ spreads between bids and offers were normally large. Still, volatility was the only risk factor considered, and as housing prices boomed consistently higher, it was very low indeed.
After 2002, leverage began to soar to as high as 35 to 1 to 40 to 1 for some of the mortgage lenders, investment bankers, and hedge funds and up to 30 percent for some of the most aggressive banks. Margin was plentiful and, with cheap rates almost effortless to obtain, it encouraged leverage, much as it had for LTCM or in the 1987 crash. Mortgage originators*35and mortgage companies almost had the banks throwing money at them.
Finally, banks and investment bankers also financed a large number of innovative, often complex investment companies that owned large holdings of such bonds as well as often extremely obtuse derivatives. Forget that the security for many of the loans was subprime mortgages or that the investment bankers leveraged their capital enormously. The banks’ risk-control departments thought all this was fine. After all, near the top of the bubble the volatility of the RMBS portfolios continued to be very low, and they had also learned from Professors Merton, Scholes, and Fama that volatility never changes for long. Risk was in an iron cage, so they could relax and make big money for their firms and themselves.
But despite the assurances of Fed chairmen Alan Greenspan and Ben Bernanke after him, as well as many other experts, that everything was just peachy, the nation’s frenetic housing bubble was coming to an end. By late summer 2006, home prices began to drop, and they fell steadily through 2007. By early 2007, the home mortgage market began to disintegrate. Housing prices continued to drop in 2008 to April 2009, accompanied by a flood of homeowners who went into arrears on their mortgages, along with a rising tide of foreclosures. Not surprisingly, the market for mortgage bonds collapsed. Beginning in 2007, liquidity began to freeze, and by 2008 it had dried up almost completely. Residential mortgage-backed securities, which had started turning down in August 2006, collapsed in the following two years. The damage was worse than that caused by any stock market crash in the nation’s history. Interesting that Standard & Poor’s, which gave AAA ratings to thousands of issues of subprime trash, gave U.S. Treasuries a lower rating in 2011. But that’s another story.
Figure 5-1 shows that the supposedly low-volatility ABX-HE-BBB investment mortgage index, rated as investment quality (one of the higher bond ratings), sank into a black hole, dropping almost 98 percent from its July 19, 2006, price to its April 2009 low. To take another example, even AAA mortgage-backed subprime securities, the highest credit rating, fell 70 percent or more during this period.
How could this happen? There are numerous reasons, but most of the damage was once again caused by leverage and lack of liquidity. As we saw, banks, investment banks, hedge funds, and other mortgage buyers were all very highly leveraged.
Table 5-1 illustrates the destruction caused to highly leveraged owners of mortgage-backed securities or any other type of investment, for that matter. The table assumes that the speculator borrows thirty times his capital, in the range of mortgage security borrowing noted a few pages back. If the prices of his RMBS securities dropped only 3.3 percent, his capital would be wiped out entirely. If the bonds dropped 5 percent, he would lose his capital plus an additional 50 percent.
But as we know, housing prices didn’t go down 5 percent; they went down 33 percent to their lows in April 2009, and the drop in RMBS securities was significantly higher. If the buyer had owned ABX AAA RMBS subprime securities (the highest rating the agencies gave), on margin, he would have lost 70 percent of his principal to the low. If he had leveraged them thirty times, he would have lost twenty-one times his original investment in margin calls. If he owned the ABX issue we looked at in Figure 5-1, he would have lost thirty times his initial investment. To put this into numbers, if an institution had invested $10 million in this bond, leveraging it thirty times, the loss would have been $294 million.
That’s why Bear Stearns, Lehman Brothers, and Washington Mutual, all heavily leveraged in toxic bonds, no longer exist. That’s also why the Treasury, under Hank Paulson, needed $700 billion of Troubled Assets Relief Program (TARP) funds to bail out the banks and investment bankers. Without that fund, many more would not exist today.
But why couldn’t investors just sell the toxic securities? Again, the answer was a complete lack of liquidity. The portfolios normally held a wide variety of mortgage-backed securities with dozens of different pools. Nobody knew what they were really worth. In a bottomless market, why take the risk? Leverage and liquidity targeted mortgage bonds with the devastating power of a nuclear bomb. Thank you again, EMH and CAPM.
Granted, not all mortgage bonds fared quite this badly, but these figures make clear why the massive bailout of financial institutions was undertaken. Whether it was right or wrong to rescue the banks and investment bankers, given the shocking incompetence of many of their senior executives, is a question the reader should answer. But after three severe wipeouts caused by excessive leverage and lack of liquidity, shouldn’t they, too, at least have been aware of the enormous danger to the financial system of too much leverage and too little liquidity?
In their defense, I would say only that they were completely wedded to the idea that volatility was the only measure of risk to worry about and therefore did not factor in liquidity, leverage, or other risk factors. This held even though some of the largest of them, including Citigroup, owned a dozen or more mortgage originators (companies that underwrote the mortgages) and clearly knew how bad the product really was. As for Professor Fama and his colleagues, did this experience shake their belief that volatility is the only measure of risk or that the market is efficient? Apparently not. In 2007, with mortgage-backed security prices already dropping rapidly, Fama said in an interview, “The word ‘bubble’ drives me nuts,” and went on to explain why people could trust housing market values. “Housing markets are less liquid, but people are very careful when they buy houses. . . . The bidding process is very detailed.”12 Amen.
Rational Markets Don’t Have Bubbles or CrashesIn spite of what we’ve just seen on bubbles in this chapter and in earlier ones, most EMH believers still deny that bubbles and crashes exist. “I don’t even know what a bubble means. These words have become popular. I don’t think they have any meaning.”13 That’s Professor Fama, trying to defend the central core of the efficient-market hypothesis, that prices are always where they should be. He denies the existence of manias and crashes. Still, bubbles and IPOs present a particularly vexing point to EMH because they seem to defy consistently rational behavior. Fama and other EMH adherents are backed into a corner. EMH has to deny the existence of manias and panics, or it will be pierced by a fatal arrow—not a particularly pleasant way for a popular hypothesis to die. There was only one escape, and Professor Fama, never accused of not being highly intelligent, found it.
He states emphatically that bubbles don’t exist. Why? Because rational investors always keep prices where they should be. In the New Yorker article, Fama dodges, ducks, or sidesteps the volley of arrows the well-versed financial reporter John Cassidy fires at him. But in doing so he steps into a position even more challenging that to my knowledge has never been examined.
Continuing with EMH logic, if, as Fama says, there are no bubbles or panics, we have to look more closely at the rational investors who perform this extraordinary feat. We already examined this question in some detail in chapter 2*36 and again briefly in this chapter and found there are no widely followed fundamental analytical methods used by security analysts, money managers, and other rational investors that condone buying stocks at prices anywhere from 10 to 100 times or more normal valuation levels in a bubble. What is apparent from chapter 2 is that analysts and money managers do move away en masse from their analytical methods and pay bizarre prices. By doing so they are not acting with the automaton-like rationality EMH assumes. If they did follow their fundamental training, prices could not reach bubble levels.
EMH believers seem to have put themselves into an untenable position. They state that it is professionals and other sophisticated investors who keep prices where they should be. But as we see, obviously the logic doesn’t work. Could it be that once again EMH theory has made a bold assumption about the behavior of sophisticated investors without a shred of evidence that it is correct? A statement that seriously threatens the central premise of EMH theory is that it is highly knowledgeable investors that keep prices where they should be. Perhaps a little more research on how highly sophisticated investors act, rather than how they should act in theory, might prove very helpful.
Have We Learned Anything Yet?You can now judge how accurate EMH has been in its core assumptions:
About liquidity
About leverage
About the correlation between volatility and returns
About whether volatility is stable over time
About rational investment “automatons” always keeping prices right
All the theoretical pillars of EMH and CAPM appear to have been knocked down. We have also seen the enormous damage done to the markets and economy during the long and celebrated reign of EMH.
What now? Should we just walk away from the markets, and forget about investing except under the mattress? EMH has led many millions of people to disastrous investment decisions. But there is a better way. It lies not far ahead of us, now that we are past the Black Knight and rode beyond the worst of the efficient-market forest. There are still major opportunities in the markets, I assure you, if we know how to identify them.
First, though, we need to equip ourselves with stronger armor and new broadswords forged by psychology and the new contrarian strategies. This done, we will learn how to dispose of the EMH dragon for good.