Developing industry-ready automated trading systems to conduct EcoFin analysis using deep learning algorithms
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Host institution: Bucharest University of Economic Studies, Romania (ASE)
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Starting month: M12
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Duration: 36 months
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Pillar 1: Introduction to AI for financial applications (WU Vienna University of Economics and Business, 4 ECTs), Work Package 2
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Work Packages: WP2, WP6, WP7, WP8
Objectives
This IRP will focus on addressing the challenges associated with automated trading systems in the direction of industry-ready platforms, i.e. minimising the risks of mechanical failures, improving the explainability of the underlying AI/ML models used in automated trading systems to better address performance-related issues, and also addressing ESG/CSR and ethical issues. This area will contribute significantly to Green Finance, thereby addressing the European Green Deal.
Expected Results
The project's outcomes will provide financial institutions with new automated trading tools. The primary anticipated outcome of the project is the design of new trading algorithm solutions for mitigating the risks of mechanical failures, enhancing the explainability of the underlying AI/ML models used in automated trading systems to better address performance-related issues, as well as ESG/CSR and ethical concerns. The anticipated results will be disseminated through the following channels: 1) Publications in prestigious journals made widely accessible through public repositories; 2) Presentations at prestigious conferences; and 3) Knowledge exchange with project partners.
Planned Secondments
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Royalton Partners (ROY), Dr. Michael Althof, M24, 18 months, research on crypto assets for prototype and user acceptance
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Athena Research and Innovation Centre (ARC) Greece, Prof. Dr. Ioannis Emiris, M18, 4 months, applied industry-research, exposure to world-leading research centre and infrastructu
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