FAILED WIZARDS OF WALL STREET
Can you devise surefire ways to beat the markets? The rocket scientists
thought they could. Boy, were they ever wrong
Smart people aren’t supposed to get into this kind of a mess. With two Nobel prize
winners among its partners, Long–Term Capital Management L.P. was considered too
clever to get caught in a market downdraft. The Greenwich (Conn.) hedge fund nearly
tripled the money of its wealthy investors between its inception in March, 1994, and
the end of 1997.
Its sophisticated arbitrage strategy was avowedly ”market–neutral”—
designed to make money whether prices were rising or falling. Indeed, until last
spring its net asset value never fell more than 3% in a single month.
Then came the guns of August. Long–Term Capital’s rocket science exploded on the
launchpad. Its portfolio’s value fell 44%, giving it a year–to–date decline of 52%.
That’s a loss of almost $2 billion. ”August has been very painful for all of us,” Chief
Executive John W. Meriwether, a legendary bond trader, said in a letter to investors.
(Long–Term’s executives declined to speak on the record.)
Long–Term Capital and its Nobel laureates in economics, Robert H. Merton and
Myron S. Scholes, weren’t the only ones who got creamed. Locating the losses is hard
because Wall Street and the hedge–fund world don’t disclose them. According to
Andrew W. Lo, a finance professor at Massachusetts Institute of Technology who
advises several so–called quant funds, as much as 20% of hedge funds, which control
some $295 billion, are quantitatively oriented.
LONG–TERM DAMAGE. The losses didn’t stop there. Nearly every major
investment house and bank in the U.S. and abroad has a group of highly paid rocket
scientists in its proprietary trading department trying to beat the market with complex, computer–aided trading strategies. In an announcement on Sept. 2, Salomon Smith Barney Holdings (NXS) disclosed that it had realized $300 million in losses from fixed income and global arbitrage—five times its $60 million in Russia–related credit losses.
Then, on Sept. 9, Merrill Lynch & Co. (MER)announced that it had lost $135
million from trading and said that the losses had hurt its own stock price.
August may go down as a watershed in the history of high–tech investing. That’s
because the losses suffered weren’t just financial: The reputation of quantitative
investing itself has been dealt long–term damage.
Merton and Scholes, after all, are two of the most esteemed figures in finance—co–inventors with the late Fischer Black of the options–pricing model that underpins much of rocket science. They and their counterparts seemed to have developed a clean, rational way to earn high returns with little risk. Instead of betting which way a market is headed, they typically search for ingenious arbitrage plays—chances to cash in on temporary disparities in the prices of related assets.
Wall Street warmed to rocket science not because it was impressed with PhDs in
physics or Nobel prize winners in economics. The Street was impressed by the money
these quants were making without having to be a George Soros—placing informed bets on the direction of assets like gold, oil, or the British pound. The beauty of rocket
science was that though the gambles were huge, the risks were minimal.
In August, though, many of these delicately constructed bets collapsed like a house of
cards. Even if the quants do spring back this autumn, it will be impossible for many of
them to claim that they can reliably produce low–volatility profits, because the
volatility they’ve experienced this year is anything but low. Suddenly, many market–
neutral funds aren’t looking any safer than ”directional” funds run by wizards like
Soros.
To be sure, the performance of many quantitative hedge funds doesn’t tar all of
financial rocket science. Some quantitative firms don’t use leverage and seek merely
to outperform some benchmark such as the Standard & Poor’s 500–stock index. By
their own lights, many of those firms came through August fine—sinking, to be sure,
but not as much as the benchmarks they measure themselves against. ”Our first
objective is to control risk,” says Stephen A. Ross, a professor at MIT and co–head of
Roll & Ross Asset Management Corp., whose return is up for the year and for the
month of August against its benchmarks.
”NAUSEATING.” That’s fine for Roll & Ross, but the dark days of August weren’t
so kind to the quants that take bigger gambles in pursuit of bigger rewards. Turmoil
enveloped almost every market. Real estate magnate Samuel Zell says that the market
for commercial mortgage–backed securities, in which traders rely heavily on computer
modeling, is in ”meltdown.” Invictus Partners, an eight–month–old arbitrage hedge
fund, began June ranked among the top–performing hedge funds in the country, but
then lost all of its gains over the summer—and more. ”What began to happen in June,
July, and August was hypnotic, nauseating, and awesome,” says Gregory van Kipnis,
the fund’s founder and CEO.
One prominent victim was the High Risk Opportunities Fund, a bond–arbitrage hedge
fund. It was put into liquidation in the Cayman Islands on Sept. 1. Its $850 million in
Russian investments went bad after Moscow suspended bond and currency trading on.
As befits a hedge fund of its type, High Risk Opportunities wasn’t betting for
or against the Russian economy—it was simply playing the 4% spread between the
ruble–denominated Russian Treasury bills, known as GKOs, and the lower cost of
borrowing rubles from banks. This seemed a safe bet because it didn’t depend on
Russia forking over dollars. The fund manager—III Offshore Advisors—was blindsided
twice. First, the Russians halted trading in their domestic government debt market.
”Nobody in the history of the world has ever done anything this foolish,” says Warren
B. Mosler, the firm’s West Palm Beach (Fla.)–based director of economic analysis.
Then, several European banks that had sold currency hedges against the plunging
ruble abruptly suspended an estimated $400 million in payments that Mosler contends the hedge fund is owed.
History is what underlies most of the quant models—however, it is not the history of
governments, but of markets and prices. Their models are based on identifying
historical relationships between the prices of kindred assets, be they bonds, stocks, or
currencies. Mountains of data that reflect decades of market behavior are fed into
computers. The computer models sift through the data to find the precise relationships between the prices of these assets. Sometimes, the prices move in the same direction.
At other times, they diverge. When the assets move out of their normal alignment, the
bell rings.
That’s a signal to trade on the expectation that prices will revert to historic patterns.
The trades can focus on markets throughout the world. It can be two related U.S.
stocks, a basket of 15 U.S. biotechnology stocks, two Italian bonds of different
maturities, or a basket of foreign currencies. But that’s not always where the bet ends.
In order to minimize the risk, the computer then spits out what other trades should be
made to hedge against any accompanying risks that the arb doesn’t want to take on.
Normally, the price discrepancies that the models seek to exploit are tiny—and indeed, have become smaller and smaller as more and more players comb the markets.
The result has been bigger and bigger bets. The computer model predicts the exact price points at which to enter the deal and the size of the bet to get the highest returns with an acceptable level of risk. This had led to the use of more and more borrowed money, resulting in many trades leveraged to the hilt. ”Hedge funds with mathematically driven strategies may use far higher than average leverage because of the perceived lower level of risk inherent in their using a large number of diversified positions,” says George Van of fund–tracker Van Hedge Fund Advisors International.
Why did rocket science backfire? Sure, the models do take into consideration the
possibilities of some failures occurring in the market system that upset normal
historical relationships. Indeed, that’s why these bets usually involve a series of
hedges. What occurred, however, was the financial world’s equivalent of a ”perfect storm”—everything went wrong at once.
Interest rates moved the wrong way, stocks and bond prices that were supposed to converge diverged, and liquidity dried up in some crucial markets. As Long–Term’s Meriwether told his shareholders in a Sept. 3 letter: ”We expected that sooner or later…we as a firm would be tested. I did not anticipate, however, how severe the test would be.”
At the heart of the breakdown was a global ”flight to quality” that was far more
intense than the wizards’ computer models predicted. They had been forecasting that
differences in the interest rates of safe securities and risky ones, which had widened,
would return to their normal range, as they almost always had before. But as Russia
unraveled and parts of Asia fell deeper into crisis, investors around the world switched their money into the safest securities they could find, such as U.S.Treasury bonds.
Many of the quant firms were betting on riskier, less liquid securities such as junk
bonds, and they got crushed. Instead of narrowing, the spreads between safe and risky securities widened drastically in virtually every market around the world.
The unexpected widening of spreads wreaked havoc on supposedly low–risk
portfolios. For example, some quant firms were betting that junk–bond yields in
Britain had gotten too high in relation to those of high–grade corporate bonds, and that the spread would narrow. If the yield spread had narrowed, as forecast, the quants would have earned a bundle. But that’s not what happened: The yield spreads widened and the quants owed a ton of money.
To work, the quant models need liquid markets on all sides of the trade. But markets
in August are thin, as Meriwether noted in his letter to fundholders. Wrote
Meriwether: ”…volatility and the flight to liquidity were magnified by the time of year
when markets were seasonally thin.” That’s the trouble with liquidity: It’s never there
when you really need it, as buyers of so–called portfolio insurance discovered in the
1987 stock market crash.
A liquidity drought is basically panic in slow motion. ”It wasn’t just the big hedge
funds,” says D. Sykes Wilford, a managing director of New York–based CDC
Investment Management Corp. ”This summer, it affected lots of people, particularly
investment banks, banks, fund managers. They had to reduce their capital exposures.
When they do that, other trades that may have looked smart all of a sudden were
subjected to this liquidity shock, too, and it fed on itself.”
WORLDWIDE PHENOMENON. The stinger is that liquidity dried up across
markets. It was a worldwide phenomenon, so the geographic diversification employed
by so many quant firms did them not a whit of good. Late August was actually worse
for some market–neutral arbitragers than the 1987 crash, admit some quants.
Review the article
Discuss how this situation might have been avoided by using good project risk management techniques.
