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GSA Capital: Staying Competitive

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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.

In order to maintain our edge GSA is exploring new markets (Crypto), investing into increasingly faster trading models, and using more available data. While this creates new opportunities, it also comes with new challenges requiring our technology to become more sophisticated, more autonomous and more performant.

In this talk we will discuss how GSA is handling these challenges. We will focus on the work done by an engineering team working closely with both researchers and other engineers. In a closer look we will explore both the technological and research side of our work on feature engineering of new, alternative data (e.g. SEC filings, credit card transaction data, social media sentiment, ...) for the use in downstream models.

Speaker: Julian completed his MSc. in Computer Science from Oxford in 2020. He then spent one year in Cambridge working for Amazon Alexa where he researched Text-to-Speech machine learning models before joining GSA Capital in 2021.His time at GSA is spent pre-processing data for research models, preparing risk calculations & reports for Portfolio Managers, running GSA ’s discretionary trading platform and engineering features for researchers. Outside of work he enjoys rowing and plays the guitar.

About GSA : GSA Capital is a multi-award winning investment manager that has been delivering exceptional results for over 15 years. With offices in London and New York, GSA Capital combines a world-class proprietary platform with innovative thinking to develop and deploy systematic and process-driven investment strategies across all asset classes, geographies and timescales.

Audience: We welcome students of all academic levels from the Computer Science, Engineering, Mathematics, Statistics and any other closely related disciplines.

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Some catering will be provided outside the room before the talk.

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

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