In what’s called nondiscretionary trading, computers both find the inefficiencies and execute the trades. The Aite Group, a financial-services research firm, estimates that roughly 38 percent of all equities may be traded automatically, a number it expects to increase to 53 percent in three years.
Computers also underlie another developing frontier, high-frequency trading, which is a fantastically exaggerated form of day trading. The computer looks for patterns and inefficiencies over minutes or seconds rather than hours or days. An algorithm, for instance, might look for patterns in trading while the Japanese are at lunch, or in the moments before an important announcement. There is a massive amount of such data to crunch. Olsen Financial Technologies, a Zürich-based firm that offers data for sale, says it collects as many as a million price updates per day.
One trader I spoke with at a $10 billion hedge fund based in New York said that his computer executed 1,000 to 1,500 trades daily (although he noted that they were not what he called “intra-day” trades). His inch-thick employment contract precluded my using his name, but he did talk a little bit about his approach. “Our system has a touch of genetic theory and a touch of physics,” he said. By genetic theory, he meant that his computer generates algorithms randomly, in the same way that genes randomly mutate. He then tests the algorithms against historical data to see if they work. He loves the challenge of cracking the behavior of something as complex as a market; as he put it, “It’s like I’m trying to compute the universe.” Like most quants, the trader professed disdain for the “sixth sense” of the traditional trader, as well as for old-fashioned analysts who spent time interviewing executives and evaluating a company’s “story.”
High-frequency trading is likely to become more common as the New York Stock Exchange gets closer and closer to a fully automated system. Already, 1,500 trades a day is conservative; the computers of some high-frequency traders execute hundreds of thousands of trades every day.
Linked with high-frequency trading is the developing science of event processing, in which the computer reads, interprets, and acts upon the news. A trade in response to an FDA announcement, for example, could be made in milliseconds. Capitalizing on this trend, Reuters recently introduced a service called Reuters NewsScope Archive, which tags Reuters-issued articles with digital IDs so that an article can be downloaded, analyzed for useful information, and acted upon almost instantly.
All this works great, until it doesn’t. “Everything falls apart when you’re dealing with an outlier event,” says the trader at the $10 billion fund, using a statistician’s term for those events that exist at the farthest reaches of probability. “It’s easy to misjudge your results when you’re successful. Those one-in-a-hundred events can easily happen twice a year.”
The events of August were outliers, and they were of the quants’ own making. (Some dispute that verdict: see “On Quants”) To begin with, quants were indirectly responsible for the boom in housing loans offered to shaky candidates.
Derivatives allow banks to trade their mortgages like bubble-gum cards, and the separation of the holder of a loan from the writer of a loan tended to create an overgenerous breed of loan officer. The banks, in turn, were attracted by the enormous market for derivatives like CDOs. That market was fueled by hedge funds’ appetite for products that were a little riskier and would thus produce a higher return. And the quants who specialized in risk assessment abetted the decision to buy CDOs, because they assumed that the credit market would enjoy nine or so years of relatively benign volatility.
It was a perfectly rational assumption; it just happened to be wrong. Matthew Rothman, a senior analyst in quantitative strategies at Lehman Brothers, called the summer a time of “significant abnormal performance”; according to his calculations, it was the strangest in 45 years. James Simons’s Renaissance Technologies fund slid 8.7 percent in the first week of August, and in a letter to his investors, he called it a “most unusual period.” As Andrew Lo put it, “Unfortunately, life has gotten very interesting.” The Wall Street Journal called it an “August ambush.”
The damage quickly spread beyond the market for low-quality debt instruments. It was almost as if the financial world had become a market for nothing so much as standard deviations, the mathematical term for the spread of values straying from a mean. In fact, the summer might be described as a time when too many investors had purchased standard deviations that were too high for their means.