Father and son graduate together

Father and son graduate together – and dad shows how medical imaging tool can predict stock market

Today the Cowan family celebrate a long relationship with the University of Auckland as father Brett and youngest son Yuri graduate together from the Business School.

Brett Cowan, 54, graduates with an MBA to add to engineering and medical degrees, and his youngest son Yuri Cowan, 22, with a Bachelor of Commerce, majoring in Accounting and Commercial Law.

“It’s a great family experience,” says Brett, who is working as a general manager for UniServices, the University’s commercial arm, and an associate professor in the department of Medical Imaging in the Faculty of Medical and Health Sciences.

At this graduation, everyone in the family – Brett and his wife Tammy and their three children - will each have at least one University of Auckland degree. Yuri is currently working on the 10th qualification from this University between them – a Postgraduate Certificate in IT. After that, he will either seek a job or pursue a Master’s degree.

Older brother Andre got a degree in Mechanical Engineering, the same degree as Brett’s first degree, and father and son were taught by some of the same people.

“If you’re going to spend four years getting a degree you may as well go to the best place possible,” says Brett. “It’s about academic rankings, and quality courses, and the good people.”

For his MBA thesis, he borrowed a powerful statistical tool from medical imaging and showed it can be used to make money on the stock market. His supervisor, finance lecturer Paul Geertsema, gave him access to half a billion data points from the last 100 years of the US share market, and he applied the technology.

“The majority of stock trades on the US stock market are made by robots,” he says. “So the challenge is how do you set up the computer to optimise profit?

“When you’re choosing which shares to buy, you’re faced with a sea of possible indicators that they will be profitable – a company that’s made a past profit, a company with momentum, a very large company with a track record, a small start-up.

“This technique sifts through them all and shows you which combination of all those things might predict a good outcome and give you the best return. What a lot of people have done in the past is take just a couple of features, but this takes the totality.”

He likens it to choosing a partner. “This algorithm says give me hundreds of people and 200 features about each of them, and I’ll tell you which one is the best match for you.”

Brett now plans to continue his business career in the high-tech commercial world or senior management at the University.

ENDS

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