The collaboration between Brunel University London and Advanced Logic Analytics seeks to investigate the role of emotions in the decision-making process related to stock market movement using AI/ML concepts and tools.
The interplay between emotion and sentiments are the basis of many trading decision. Thus, this FinTech-AI project will aim to utilise novel AI and semantic techniques to develop new predictive emotion-based algorithms that utilise financial news.
The project will enable partners to co-create novel fintech solutions with:
- Automated techniques for market-specific corpus generation that support more effective emotion recognition
- New Machine Learning (ML) algorithms for emotion detection in a range of financial markets
- Novel models for depicting emotional journeys within discrete trading communities
Additionally, understanding different financial products and conducting market segmentation will enable the project to develop new more specialised predictive models and algorithms.
The research will help ALA create a unique solution that will utilise sentiment analysis to accurately predict future market movements, to improve fund performance, and enhance the company’s systematic trading products marketed to the Financial Services sector.
More specifically, the following phases constitute the project lifecycle:
- Qualitative research to understand different market segments and the effects of emotions on these segments
- Creating market-specific corpus relevant for emotion recognition
- Developing the new Machine Learning (ML) algorithm for emotion detection in the financial market domain based on the outcomes of the two previous phases
- Utilising the newly developed algorithms to uncover the emotional journey of the traders in the financial market domain
- Integrating the developed algorithms within exiting ALA’s products
The project will run from 2021-2023 and will be in partnership with Advanced Logic Analytics (ALA) Limited.
Meet the Principal Investigator(s) for the project
Related Research Group(s)
Intelligent Data Analysis - Concerned with effective analysis of data involving artificial intelligence, dynamic systems, image and signal processing, optimisation, pattern recognition, statistics and visualisation.
Project last modified 25/06/2021