Marc Levitt has been interested in trading and building quantitative models since taking graduate level courses in chaos theory at the University of Illinois, but it took him a long time to launch his commodity trading advisor (CTA), Silicon Valley Quantitative Advisors, and an even longer time before focusing on it full-time.
Though he devoted much of his academic effort to applying chaos theory to financial markets, after he earned his doctorate in electrical engineering in 1990, Levitt took a position with Sun Microsystems to learn about business and technology.
"I kept my interest up in financial markets research while working at Sun," Levitt says. He would correspond with hedge funds and CTAs, exchanging system ideas with them while working in Silicon Valley and looking to get more involved in trading.
"Sooner or later I had to decide what to do," Levitt says. "That is when I decided to start High Frequency Finance, my software company, to develop software that could help traders."
Levitt worked with hedge funds and developing overlays concentrating on forex markets, actually developing his own carry trade benchmark. He left Sun in 1997 to concentrate on his software business, which helped several hedge funds improve their risk-adjusted returns. But, the Russian debt and Long-Term Capital Management crises in 1998 caused business to dry up and Levitt decided to develop his own trading program.
He went back to the semiconductor field during the day and moonlighted developing his CTA that would look at a longer time frame as opposed to his high-frequency research. "That was the time frame that fit my profile, working with daily data. It had nothing to do with those [high-frequency] techniques not being successful; it was just not how I decided to go about building a CTA," Levitt says.
His U.S. Quantitative Program (UQP), which trades 36 U.S. futures markets in every sector except stock indexes, got off to a great start, earning 83.08% in 2000, its first full year of trading. UQP basically takes a medium-term systematic trend-following approach, but Levitt built in some countertrend elements that helped it outperform classic trend followers.