What was the project about?

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The goals of this project were to (1) to develop a technique that can help investors, including small wealth management offices, to take informed investment decisions that optimise a portfolio’s Environmental, Social, and Governance (ESG) impact, and, in particular, minimises the CO2 emissions of underlying portfolio assets and (2) to create a prototype implementation that, with sufficient computing power, accessed through massive-parallel programming technology targeting GPGPUs, provides decision makers with valuable tools for optimising and managing portfolio ESG factors, for realistic portfolios, while at the same managing portfolio risk and performance through classic portfolio optimisation techniques.

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​The project was realised partly through 9 BSc thesis projects (15 BSc students) and one MSc thesis project (one student). Whereas the BSc thesis projects mainly served to investigate the usability of utilising the combination of traditional asset time-series data and ESG data in decision processes, the MSc project investigated techniques, based on GPGPU computing, for efficient problem solving, utilising the Futhark programming language, a parallel programming language developed at DIKU.

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Professor Martin Elsman served as project supervisor for all student projects and Associate Professor Omri Ross served as an additional project counselor providing expertise in modern portfolio theory. ​

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The project was based on current research developed at the Department of Computer Science at the University of Copenhagen and done in collaboration with FinE and Invest Fondsmæglerselskab A/S.​ The industrial partners e.g. provided essential ESG data that was used in all student projects.

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Host Institution(s):​

University of Copenhagen​

Principal Investigator:​

Martin Elsman, Professor, Department of Computer Science​

Partners:​

FinE Analytics

Optimal Invest Fondsmæglerselskab A/S ​

Grant:​

200.000 DKK​

Project Period

1.1.23-31.12.23

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