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Quants Caught Off Guard During the Credit Crisis
There is a mystique surrounding quantitative hedge funds that hire scientists and mathematicians to create complex models to make trading decisions. But is Wall Street becoming disillusioned with quants following the turmoil that rocked many hedge funds this summer?
When the credit crisis hit in late July and early August, quant funds that relied on complex models fell off-kilter, causing a number of hedge funds to sell off the same U.S. stocks simultaneously, leading to volatility that whipsawed the market. Even marquee brands such as Renaissance Technologies, AQR Capital and Goldman Sachs Group had quant funds that suffered steep losses. "Obviously, we saw in those moves the incredible influence that quantitatively run money has on Wall Street," says John Comerford, EVP and global head of trading research at Instinet, the global agency broker.
The 'Quant Factor'
"There's talk of this quant factor, which was global and across asset class and also tied to liquidity," continues Comerford, a quant for 17 years who in the '90s worked at hedge fund manager Symphony Asset Management. During the credit crisis, similar assets moved in the exact opposite way, he notes. "That dispersion was explained by this hard-to-quantify quant factor -- quants running very similar strategies," Comerford explains.
In addition to their models going haywire, the quants that used leverage (borrowed funds) faced margin calls from their prime brokers, which were spooked by the spread of the subprime mortgage contagion. "We had problems with hedge funds that were heavily leveraged because the credit crunch caused prime brokers to call in margin and forced people to deleverage," says Peter Fraenkel, director of quantitative services at Pragma Financial Systems, a developer of algorithmic trading systems. "I don't think it was quants per se, but quantitative tools made it possible to manage a heavily leveraged long-short portfolio."
But since many of the quant funds made money during this same period -- and some of the funds that lost money made it back again a few weeks later -- no one really is blaming the quants, according to many industry observers. "I don't think people are looking at this and saying, 'My God, the quants have let us down,'" comments Fraenkel.
Since many of these funds are shrouded in secrecy and charge a premium to run unique strategies, however, it was surprising to learn that many actually run the same strategies. "Every time there is some type of meltdown in the market, someone says, 'Why are we spending millions of dollars on Ph.D.s in the back office running their models when they didn't see this coming?'" observes Rob Meyer, CEO of Numerical Algorithms Group, which develops analytical code that is used in financial models. "The other way to look at this is to say, 'What's the alternative?'"
Some pundits say the turmoil that roiled the markets and caused the hedge funds to unwind the same positions points to the need for better models. One of the issues is that models are developed on historical data, rendering them imperfect. "Everything that involves modeling is an approximation of reality; it's not reality," says Meyer. "If we have enough data and variables, maybe we can get closer to reality. It's going to be a situation where the models don't coincide with reality."
But were the quant models flying blind? According to Tom Plaut, CEO of FX Solutions, an online foreign exchange broker, there's a lot of second-guessing going on, but quantitative methods are not to blame for the shake-up. "This showed a need for more risk management, more systems, quantitative skills and globalizing the system so they talk to each other. I don't think they understand the amount of risk on the book and the impact of dislocation," he contends, adding, "It's the outlier event that catches everyone off guard."
In the end, quant funds are not going away. Rather, they'll likely proliferate, and the quants will use the experience from the credit turmoil to develop better risk models and better risk systems to evaluate those models.
Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio