NEW YORK (Reuters) - Wall Street is looking beyond business schools for its new masters of the universe.
In the high-speed, high-stakes world of algorithmic trading, math geeks rule, and universities are churning out scores of graduates from newly designed financial engineering programs to meet banks’ and hedge funds’ demand for quantitative experts.
The most cutting-edge work in the field is still being done by physicists and mathematicians with Ph.D.s, but financial engineering programs are providing Wall Street with a growing number of traders and analysts who can crunch numbers and generate complicated market strategies.
Financial engineering programs didn’t exist in the mid-1990s, but now they graduate an estimated 500 students in the United States every year, and one expert sees the number of programs growing by some 30 to 50 percent over the next five years.
Even with that growth, the United States is generating far more MBA’s than financial engineers -- about 140,000 master’s in business administration degrees were awarded in 2004, according to the Department of Education.
There are still plenty of jobs for MBAs on Wall Street. But financial engineering graduates from top schools -- including New York University, Columbia, the University of Chicago and Stanford -- can earn more than $100,000 a year in their first year of work, on a par with MBAs from those and other top schools.
The programs are meeting demand from banks and hedge funds that need thousands of quantitative experts for their trading desks as financial markets have grown more complex and trading strategies more abstruse.
Algorithmic trading, or trading based on complex formulas executed by computer programs, accounts for about a third of U.S. equity trading volume, a percentage that is growing rapidly. The London Stock Exchange estimates that around 40 percent of its trading is algorithmic.
IS IT SMART?
A decade ago, many trading-desk jobs would have gone to holders of doctorates in physics and computer science, but times have changed, said Steve Allen, deputy director of the mathematics in finance program at New York University’s Courant Institute.
“People started to ask themselves, ‘Is it smart to have people take seven years to complete a physics Ph.D., and then think about a finance career?’”
A student in a one- or two-year financial engineering program typically majored in mathematics or physics as an undergraduate, and takes classes in areas like optimization and risk management as part of the master’s degree.
Graduates of financial engineering programs can find jobs at banks’ trading desks, helping with areas like valuing securities, generating new trading strategies, or tweaking existing automated trading systems.
But when it comes to creating completely new systems that will give proprietary traders a real edge over competitors, firms still usually look for Ph.D.s, NYU’s Allen said.
For example, Jim Simons, founder of the $30 billion Renaissance Technologies Corp. hedge fund manager, who earned an estimated $1.7 billion last year, said he looks above all else for scientists.
“We hire physicists, mathematicians, astronomers and computer scientists, and they typically know nothing about finance,” Simons said in a keynote address at the International Association of Financial Engineers annual conference in May. “We haven’t hired out of Wall Street at all.”
It often takes a broad range of skills to create a truly new trading system, so it makes sense to recruit widely, said Marian Munz, chief executive of Media Sentiment Inc., a San Francisco-based company that developed an algorithmic system that predicts stock moves based on market sentiment.
Munz interviews doctoral students and industry specialists from areas including cognitive science, artificial intelligence, natural language processing, Internet development, trading and even English, where a Ph.D.’s expertise can be useful when writing programs that analyze reports and written statements.
“You put together a team that in aggregate has all the skills you need. It’s the team effort that does the job,” Munz said.
For creating quantitative trading systems, the ideal set of skills includes the ability to write commercial-caliber software programs, a passion and talent for solving complex mathematical problems, and a deep understanding of financial markets, said Drew Myers, a Seattle-based recruiter.
Doctoral students in areas like computer science, physics, or mathematics may often need to learn more about financial markets, but they still are often strong candidates for Wall Street jobs, said Myers, who focuses on quantitative experts and algorithmic trading system developers.
“The original motivation for their getting a degree was a fascination with problems, and they have a gift for solving them,” Myers said.
“Someone in a financial engineering program is usually motivated to get a job at a hedge fund, which might not be enough to really drive them once they have the job,” he said.
Additional reporting by Dane Hamilton and Jennifer Ablan in New York
Our Standards: The Thomson Reuters Trust Principles.