How Wall Street learned to love computers

Published by John Wiley & Sons

Even after the 2008 crisis proved that many of the banks' computer-based models were flawed, computers and "rocket scientists" still play a major role on Wall Street. They have pioneers like 70-year-old Michael Goodkin to thank.

On paper, Goodkin was an unlikely revolutionary. In his memoir, The Wrong Answer Faster, he admits that, "all I really knew about computers was that they were fast". Indeed, while at Columbia University in the late 1960s, he only passed the mathematics part of his MBA degree because student riots forced the university to change the exam to a pass/fail test.

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Despite all this, he was one of the first to spot that computers could be used to automate trading. His inspiration came from two sources. Firstly, a meeting with Salim Lewis, the head of Bear Stearns, brought home to him the extent to which Wall Street was behind other industries in the use of technology. Secondly, a lecture on convertible bonds made him aware of how econometrics could be used to predict prices.

Goodkin quickly hired some leading economists, including three future Nobel Prize winners, Paul Samuelson among them, to produce programs that could trade bonds faster than human traders. The key was not to make the right' trade it was to predict the trades that the other players would make and get there first. They set up an experimental hedge fund to test their ideas.

Today, even after the crash, any hedge fund with a half-decent idea can quickly attract millions, or even hundreds of millions, of dollars. However, things were very different in the late 1960s. Not only were regulators extremely wary, institutions and major investors refused to invest.

As the author recounts, "everyone was dismissive of our paper track record, Samuelson's Nobel Prize nomination, and the team's academic pedigrees". Although able to raise enough money to show that they could make real profits, potential buyers continued to be reluctant. A meeting in 1970 with Sigmund Warburg ended in disaster. "It was obvious that Sir Sigmund didn't take kindly to the notion of doing business with someone of such unequal stature".

In the end, things came down to a crunch meeting with legendary Wall Street investor Leon Levy. Things were going badly until one of the traders asked whether Goodkin's model had spotted an opportunity that he had found earlier that day. After a phone call to check, the answer came back: not only had the computer spotted it it had done so the day before. This answer persuaded Levy's Oppenheimer fund to invest, and eventually Goodkin sold the hedge fund company for a lot of money.

Goodwin made millions, but he received little public credit: shortly after selling up, he attended a lecture at his old university that focused solely on the role of the two economists, and did not even mention him by name.

With no need to work, Goodkin spent the next two decades playing high-stakes backgammon around the world. Although he had some memorable times, recounted in the final part of his book, Goodkin tried to get back in the game. His attempts to use chaos theory to perfectly price more complex derivatives hit a brick wall. But then he had another revelation.

Instead of building the perfect model, he just had to find a way to allow traders to apply their own models more quickly - the "wrong answer faster" of the title. While this meant he was selling software rather than running money, it enabled him to make a second fortune. His company's programs also had uses in medical fields like cancer treatment.

There are no trading tips or secret formulae in the book. Instead, it's what Jordan Simm in Canadian Business calls a "traditional coming-of-age tale". But, as Simm points out, "the story is anything but conventional", providing a window into a time when Wall Street was a very different place. Goodkin's blunt style makes him an engaging writer, while few others have gone from street hustler to high finance via such an interesting path.