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Department of Computer Science and Technology

Monday, 16 October, 2023 - 13:05 to 13:55
Mihai Enache
FW26, William Gates Building


Quantitative investment firms attempt to navigate through large amounts of data in order to identify patterns and predict whether an asset is going up or down in value over a specified period of time. They employ various mathematical and statistical models to come up with efficient trading strategies tailored for a particular market or asset class.

Data collection, signal processing, risk management and order execution must be supported by state-of-the-art, impeccable technology. Staying ahead of competitors is an on-going challenge in this industry, particularly in modern assets such as crypto currencies which are riskier but can offer higher returns.

In this talk we will explore the general structure of GSA and the various teams that make up technology and research. We will also have a high-level overview of the life cycle of an order, covering some of the different stages it follows from idea to actual market execution.


Mihai Enache earned his Bachelor's Degree in Computer Science from The University of Edinburgh in 2019. He then worked at Bloomberg until September 2021. Following this, he pursued an MPhil in Advanced Computer Science at the University of Cambridge from 2021 to 2022. He joined GSA in July 2022 and has been working in the Execution Services Group (ESG) as a software developer since then. During his undergraduate studies, he focused primarily on data science, but in recent years, he has shifted towards software engineering and computer architecture. His main hobbies include playing chess and running, with the route from Cambridge to Grantchester meadows being among his favourites.

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.


We welcome students of all academic levels from the Computer Science, Engineering, Mathematics, Statistics and any other closely related disciplines. The event will start with a short presentation followed by informal chats with representatives from GSA over food and drinks.

Please sign up via our events listings at

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