University of Cambridge > > Technical Talks - Department of Computer Science and Technology  > Dealing with the 3 V's: Bigger, Faster, Weirder

Dealing with the 3 V's: Bigger, Faster, Weirder

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Quantitative finance is a highly competitive environment, leveraging statistical analysis to gain a small but repeatable edge in the markets. Throughout the decades, many innovative algorithms have come and gone – initially successful but eventually losing their power, as they become publicly known and widely traded. In a way, systematic funds are engaged in a never-ending arms race of turning publicly available information as quickly and as accurately as possible into a fair price, and efficiently acting on those opportunities that are currently over- or undervalued.

Like many industries, the last decade has seen an explosion of available data. The volume is starting to be measured in petabytes (bigger), the incoming velocities reaching multiple GB/s (faster), carrying an ever-growing variety of alternative data (weirder). More data really just means a bigger haystack, though, and research is intensified to continue distilling useful information from this torrent. In tandem, technology solutions need to become more sophisticated, more autonomous and more performant.

In this talk, we’ll discuss how GSA is handling these challenges. We’ll mainly focus on the technological aspects, as experienced by one of the teams – the Data Services Group. Slightly sensationalist abstract aside, this has been an exciting journey, and continues to be.


Joris completed his PhD in Applied Physics from Ghent University, Belgium, in 2011. He subsequently spent three years in Nuremberg, Germany, designing algorithms and software for computational fluid dynamics simulations, with a focus on aeroplane wing icing and race car engines. After moving to London, he joined Winton Capital Management in 2014 and subsequently GSA Capital in 2017. His time in the wondrous world of finance is mostly spent building technology for trading systems, data pipelines, risk calculations and historical back-testing. Outside of work he enjoys quantitative sports betting and anything to do with computational neuroscience. He also has a passion – but sadly no talent – for playing the trumpet.

This talk is part of the Technical Talks - Department of Computer Science and Technology series.

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