Home' Technology Review : November December 2007 Contents 36 FEATURE STORY
TECHNOLOGY REVIEW /
On Wednesday, August 8, not long after the mar-
kets closed, 200 of the smartest people on Wall
Street gathered in a conference room at Four
World Financial Center, the 34-story headquar-
ters of Merrill Lynch. August is usually a slow month, but the
rows of chairs were full, and highly paid nancial engineers
were standing by the windows at the back, which looked out
over black Town Cars below and the Hudson River beyond.
They didn t look like Masters of the Universe; they looked
like members of a chess club. They were "quants," and they
had a lot to talk about, for their work was at the heart of one
of the most wor risome summer markets in decades.
The conference was sponsored by the International Asso-
ciation of Financial Engineers (IAFE), and its title asked, "Is
Subprime the Canary in the Mine?" "Subprime" borrowers
are home buyers whose poor credit history means they don t
qualify for market interest rates. Loans to subprime borrow-
ers, which have become more common in recent years, typi-
cally have variable interest rates; as those rates rose, many
borrowers were failing to meet their mortgage payments.
Their defaults, in tur n, had triggered unexpected problems in
the market for nancial instr uments known as derivatives.
A derivative is a tradable product whose value is based
on, or "derived" from, an underlying security. The classic
example of a derivative is the option to buy a stock at some
time in the future. In comparison, more recent derivatives
are extraordinarily complex, and they had been invented by
quants like the ones at the Merrill Lynch headquarters.
Things had started to go wrong in June, when the weak-
ness in the subprime market had led to the collapse of two
huge funds at the investment bank Bear Stearns, costing inves-
tors some $1.6 billion. When the quants gathered in August,
the most pessimistic among them imagined that the collapse
of the subprime market could lead to a shortage of credit
as banks dealt with defaults. That would chill the economy,
causing worldwide job losses, still more defaults, decreased
spending, and withdrawals from the stock market, culminat-
ing in a global recession, or worse.
The quants behind Wall Street s
summer of scary numbers.
By Bryant Urstadt
Illustrations by Julien Pacaud
The panel was moderated by Leslie Rahl, an MIT grad-
uate and the founder of Capital Market Risk Advisors. Her
job is to advise companies on risk and help them under-
stand the products quants invent. But understanding was in
short supply in August. Some of the quants nancial prod-
ucts had collapsed in price, with unexpected consequences
in another nancial sector: the trading of equities.
The stock market had plunged in July and had been
behaving er ratically since. In the weeks after the conference,
an organizing narrative of sorts would develop. But at the
time, the economic view was dizzying. The market would
drop precipitously over the course of a day, then rebound
nearly to its previous level in the last 45 minutes of trading.
Stranger still, stocks with strong nancial reports and a
good outlook were falling; these were the blue chips, which
normally rose in uncertain times. Stocks with weak nan-
cials and a gray future were rising. These were normally
the dogs that got dumped.
No one quite knew why, yet, but the market s odd behav-
ior would turn out to be closely linked to the work of the
quants. In addition to creating arcane nancial products,
quants have been pushing the frontiers of computer-driven
trading systems, and not enough of those systems were
working the way they were supposed to---or, to put it more
precisely, the way they were supposed to work tur ned out
to be counterproductive in volatile times like these.
Quants like the ones at the August conference were knee
deep in the troubles threatening the global nancial system.
It all raised two very good questions: Who exactly are the
quants? And what do they really do?
"Quant" is an elastic word that has meant di erent things
at di erent times. Historically, the term refer red to back-
room technicians who used quantitative analysis to sup-
port the bankers who sold nancial instruments. It came
into wider use in the 1980s, when academics---pure mathe-
maticians and physicists, mostly---began to appear in the
nancial world in larger numbers. Classic geeks, the new-
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