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  Deep learning for Intelligent Stock Trading [Self Funded Students Only]

   Cardiff School of Computer Science & Informatics

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  Dr Xianfang Sun  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Stock market is traditionally highly volatile, affected by various kinds of economic, political, social, and psychological factors. It is hard to predict the stock market change and make investment decision for even a high experienced trader. Quantitative trading techniques based on computer algorithms have been developed to support decision making in stock market. However, existing quantitative trading techniques are still not satisfactory in many cases. This project aimed to develop an intelligent stock trading decision support system that can outperform existing techniques based on publicly available textual and numerical stock market information.

To achieve the project aim, different methods of stock market information collection, dataset building, quantitative and qualitative analysis, and decision support algorithm design will be investigated. Data mining techniques are used to extract useful data from various publicly accessible data sources. Natural language processing techniques are used to extract qualitative information from related textual data. Deep learning methods are used to predict stock price changes based on both qualitative and quantitative information of the stock markets, including news about business stakeholders and stock price history. The decision support model is built using deep reinforcement learning methods based on stock prediction. On completion of this project, a stock trading decision system will be built that can automatically collect stock market information from a variety of internet sources and make decisions on stock trading that can maximise the profit with financial constraints. 

Keywords: Fintech, Quantitative Trading, Deep Learning, Reinforcement Learning, Natural Language Processing, Decision Support System.

Contact for information on the project: [Email Address Removed]

Academic criteria:  

A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject.  Applicants with appropriate professional experience are also considered. Degree-level mathematics (or equivalent) is required for research in some project areas. 

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component. 

This application is open to students worldwide. 

How to apply

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below 

This project is accepting applications all year round, for self-funded candidates via  

In order to be considered candidates must submit the following information:  

  • Supporting statement  
  • CV  
  • In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD 
  • Qualification certificates and Transcripts 
  • Proof of Funding. For example, a letter of intent from your sponsor or confirmation of self-funded status (In the funding field of your application, insert Self-Funded) 
  • References x 2  
  • Proof of English language (if applicable) 

If you have any questions or need more information, please contact [Email Address Removed] 

Computer Science (8)

Funding Notes

This project is offered for self-funded students only, or those with their own sponsorship or scholarship award.

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