First year's salary: Pounds 23m

January 21, 2000

As increasing numbers of academics flex their mathematical muscle in the City, Thomas Bass examines the multimillion-pound prospects for two pioneers and sketches the emergence of a new field of research

Money is remaking itself in the 21st century. Financial markets are going global and electronic, and with advances in the internet, anyone with a PC can enter the fray. But the star performers are British and American academics, people who used to theorise about fluid flows and ice ages before they began using the same methods to think about money.

"Finance used to be a game for people with degrees in philosophy and history from Oxford," says mathematician Paul Wilmott. "Then it was run by East End barrow boys. Now everyone who gets hired by the banks has a maths degree and trades on computers. It is the age of the geek. My time has finally come."

Wilmott, who "solves real-world problems", such as designing turbine and razor blades, is former head of the Mathematical Finance Group at Oxford University, a job he has just left to go into finance. "Finance is the ultimate in real-world problems," he says.

"There is a huge brain drain from academia to the City," says Lenny Smith, a theoretical physicist at Oxford, who moonlights as a financial consultant. "It's quite common for the top mathematics scorers to go to work for the banks. They hire 20 per cent of our graduates, the best firsts, the prizewinners."

"We're haemorrhaging mathematical talent," concurs John Ockendon, research director at the Oxford Centre for Industrial and Applied Mathematics. Ockendon runs down a list of students who have gone to work for Nomura, Credit Suisse and Paribas. "We're prime hunting ground for these people," he says, and the reason for the head-hunters' success is not hard to understand. The starting salary for a new PhD in a research position at Oxford is Pounds 16,286. The starting salary for a research position in a bank is double or triple that. For people with a couple of years' experience, the salary and bonuses can push into six figures. "That is a lot more money than I make," Ockendon says.

Scientists remaining in academia feel beleaguered. "It is hard to find anyone to teach finance when you can quadruple your salary in the City," says Sam Howison, a former colleague of Wilmott's who is still doing research on mathematical finance at Oxford. Howison is resisting a move to the City for fear of waking up one morning "wearing a pair of golden handcuffs".

So many physicists and mathematicians have switched from academia to finance that they have started holding their own professional meetings. Their debut was a conference in Dublin last summer, attended by 200 people, called "Applications of physics in financial analysis". A second conference will be held this July in Li ge, Belgium, and about the same time the Institute of Physics in Bristol will launch the journal Quantitative Finance.

IoP journals publisher John Haynes says: "Physicists who have made the move to finance still want to contribute to research. This journal will be for academics and finance professionals."

The model for how to switch from academia to business on your own terms is provided by two United States physicists, Doyne Farmer and Norman Packard, who founded a financial forecasting company in 1991.

Farmer will be co-editor of Quantitative Finance, together with Michael Dempster of the Cambridge-based Judge Institute.

Packard and Farmer were already known for an earlier business venture in the late 1970s, when they used their predictive system to beat the roulette tables in Las Vegas with a 40 per cent advantage over the house.

The pair are also known as co-inventors of chaos theory. Farmer ran the Complex Systems Group at Los Alamos National Laboratory, while Packard, after working at the Institute for Advanced Studies, became a tenured professor at the University of Illinois.

But they never lost their gambling urge, and by the early 1990s it looked as if another lucrative game was in the offing - the world financial markets.

Packard and Farmer quit their jobs and set themselves up for business in an adobe house off the Plaza in Santa Fe, New Mexico. They took delivery of half a dozen Sun computers, stuck a satellite dish on the roof and began pulling down the numbers.

Two trillion dollars a day are traded in the foreign-exchange markets. Trillions more dollars are traded in stocks, commodities and derivatives. The numbers rise and fall, for reasons no one knows, and they are generally thought to be random. But so, too, were the spinning numbers on a roulette wheel.

These two lanky physicists, now in their late forties, are practitioners of the new science of chaos or complex systems - a branch of knowledge good at finding order within disorder.

Like any other dynamic system, financial markets generate data points moving through time. Map these points in multidimensional universes and they reveal, if only for an instant, where the system will be next month, next week or in the next five minutes.

A trader with this knowledge could walk away from the table with a lot of money. How much money? Packard and Farmer were looking for an initial investment of $100 million. Leverage this by a factor of five, secure a 30 per cent return, collect 25 per cent of this as a fee for your services and pocket a cool $37 million (Pounds 23 million) a year in profit. A nice balance sheet for year one. After that, real money.

In 1991, when Farmer and Packard opened their doors for business as Prediction Company, they had never read the financial pages of a newspaper. "I was upfront about my ignorance, because I figured there was no reason I ought to know these things," says Farmer. "We were accumulating information. We were on a fishing expedition."

In getting their company launched, they had two advantages: they were well known as gamblers and they were accomplished scientists. But then some well-timed publicity put the icing on the cake. In February 1992, Packard and Farmer and the half dozen physicists who had begun working with them were sitting in their bungalow in Santa Fe, wondering how they were going to attract $100 million in investment, when the phone began to ring. They received more than 100 calls from high-net-worth individuals - as the wealthy now call themselves - who were clamouring to put up the cash.

An article about Prediction Company had just hit the front page of The New York Times. The article, "From swords to plowshares", which ran with a photo of Farmer working at his computer, was one in a series of pieces discussing what the military-industrial complex would do with itself now that the cold war was over. The New York Times suggested that Los Alamos National Laboratory, the United States's pre-eminent weapons research facility, home of the atomic bomb, with 13,000 employees and a yearly budget of $800 million, should emulate the hang-loose hackers at Prediction Company.

Prediction Company got its investment capital and went on to do exactly what it had promised - build an automated system for predicting directional moves in the world financial markets. It has one client, UBS, the former Swiss Bank Corporation, which was renamed after it gobbled up its larger rival, the Union Bank of Switzerland. UBS is the world's third largest bank and Europe's largest player in the world markets. Prediction Company's contract has just been renewed. The company is doubling in size, from 20 to 40 people in Santa Fe, with similar numbers of people aiding its operations in Chicago, New York and London.

No statements of profit and loss are filed for this private firm, but Prediction Company is obviously doing quite well. It is one of the rare instances of an ongoing business that has allowed some of its secrets to see the light of day - not enough to quieten the sceptics, who will always believe the markets are chaotic and unpredictable - but enough to show how global finance and forecasting are in the process of remaking themselves.

Money today is bits and bytes that sweep around the world through satellite transponders and fibre-optic cables. Money is information that travels at the speed of light. By moving trillions of dollars that used to remain stationary, satellites have produced an estimated 5 per cent jump in the world credit supply.

Paralleling these transformations in money and markets is the development of what one might call the sciences of prediction, which include a grab-bag of techniques for peering into what was previously dismissed as chaotic or inexplicable behaviour. We are now good at finding order in low-dimensional chaos. We can describe non-linear systems. We have borrowed techniques from biology to develop neural networks and learning algorithms. These methods are being assembled into the new physics of complexity, whose Mecca is the Santa Fe Institute, where Farmer recently accepted a research post.

Prediction Company's trading signals are produced by what is known as a black box. This is a computer program whose operation is obscure, except to those people intimate with its design. All the major players in the world financial markets are rushing to develop black-box financial forecasting systems of their own.

"No one really knows how to eliminate all the risks," says Andrew Lo, who directs the financial-engineering programme at the Massachusetts Institute of Technology. "But less sophisticated technology will lose out over time to more sophisticated technology, which is why the old-boy network is being replaced by the computer network. Call it revenge of the nerds, but everyone on Wall Street is scrambling to develop computer-driven trading."

Thomas Bass is author of The Predictors: How a Band of Maverick Physicists Used Chaos Theory to Trade their Way to a Fortune on Wall Street (Penguin), Pounds 18.99.

Please login or register to read this article

Register to continue

Get a month's unlimited access to THE content online. Just register and complete your career summary.

Registration is free and only takes a moment. Once registered you can read a total of 3 articles each month, plus:

  • Sign up for the editor's highlights
  • Receive World University Rankings news first
  • Get job alerts, shortlist jobs and save job searches
  • Participate in reader discussions and post comments

Have your say

Log in or register to post comments