Project description
Can a robot be trained as a stock trader?
Machine learning has spurred advancement in numerous fields as diverse as image recognition and self-driving cars. The EU-funded DataABM project wants to step up this potential by training a computer to simulate investor behaviour in the stock market. To do this, researchers will create an Agent-Based Model (ABM) that will be trained by machine learning on a large investor data set. The model could improve understanding about the investor decision-making process as well as provide a tool to better predict and simulate stock market fluctuations. This could aid regulators and policymakers in estimating the impact of economic measures in the future.
Fields of science
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineeringautonomous vehicles
- natural sciencescomputer and information sciencesartificial intelligencemachine learningsupervised learning
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesmathematicsapplied mathematicsnumerical analysis
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-AG-UN - HORIZON Unit GrantCoordinator
33100 Tampere
Finland
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Partners (1)
8000 Aarhus C
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