Manning the machines

Thomas Nygaard has a long career in Finance behind him. Since he started working as a financial analyst and portfolio manager during the 90’s, he has seen huge changes in the industry.

“Especially asset management used to be based on a lot of qualitative analysis in which analysts had to travel around to visit companies and talk to the management. However, more and more of the research shows that a quantitative approach provides superior results at lower costs.”

By purely crunching numbers automatically, using what he calls a factor based approach, investment analysts are now able to use technology to make predictions with much greater accuracy than what humans can do.

“In 2009 the Norwegian Oil Fund ordered a study of how their asset management was doing. The factor based models proved to be working the best. That study got a lot of international attention. Also in 2013 Eugene Fama that works within this field became a Nobel Prize laureate. So quantitative finance has really taken off in the last decade or so.”

Leveraging technology

Nygaard became increasingly fascinated by how much more data driven and efficient the market was becoming by using advanced models and algorithms. In 2018 he decided to take advantage of the opportunity and founded the company Norquant along with his brother who is a physicist.

“We saw that there were a lot of opportunities to automate the processes within finance. What makes our asset management different is that we download tens of thousands of data points every day for stocks and funds that we organise, analyse and make available to investors.”

The technology the two brothers have developed is essentially a robot that can do what investment analysts used to have to do manually. The company also makes sure to keep up with academic research and what international companies are doing, and use new insight to its advantage.

Working with robots

“I would recommend anyone who wants to work in finance to get some level of programming experience. It’s essential to have now in order to take advantage of all the data and make the process more efficient. So we definitely see programming as a valuable skill to have when we are hiring.”

According to Nygaard, the link between financial theory and quantitative skills is growing stronger by the day, increasing the demand for quantitative analysts that can automate big amounts of data. The good thing about data science skills is that they are transferable, he says. Programming is also increasing in demand in other areas of the market.

“Of course, there is a lot of domain specific knowledge in finance that you need to have a good grasp of before you start automating and writing algorithms. What would make you attractive on the job market is having good fundamental understanding of the field, and knowing how to use quantitative methods to implement it.”