Building a code and data repository for teaching algorithmic trading

An all-in-one pocket guide to algorithmic trading, with database and code implementations in Python

Methodology

Part 1.1

Microeconomic analysis

Historical stock tick data and financial statements from six selected stock markets will be collected. Code for technical and fundamental analysis will be written in Python and Julia.

Part 1.2

Macroeconomic analysis

Current and historical residential property prices of Hong Kong will be collected. They be analysed by machine learning in order to capture price dynamics over different districts of Hong Kong.

Part 1.3

Sentiment anaylsis

Facebook and Twitter data will be collected to analyse the market sentiment in Hong Kong and the US. Machine learning will be applied to categorise texts into positive, negative or neutral.

Part 2

Trade signal prediction with multi-source features & Trade execution

Leveraging the respository, we will conduct experiments on implementing a machine learning model that takes multi-source features, namely technical, fundamental, macroeconomic and market sentiment indicators as inputs. The output will be a daily trading signal (buy, sell, or neutral). We will also include code examples of making and managing orders with the Interactive Brokers API in the repository.

Timeline

Start

August 2020

Ideation & research

  • Background study on existing resources for learning algo trading
  • Data collection for all three subparts in Part 1

    • 4 October 2020

    1st deliverable: Project plan, project website

    October 2020

    Project development

  • Part 1 code implementation (50% done)
  • Literature review
  • Documentation
    • 2021

    January 2020

    Project development (cont'd)

  • Part 1 code implementation (100% done)
  • Part 2 research & experimentation

    • 11-24 January 2021

    2nd deliverable: Interim report, 1st presentation

    March 2020

    Testing and evaluation

  • Organise and visualise findings in Part 2
  • Final review of repository
  • Project exhibition

    • 19 - 23 April 2021

    Final deliverable: Final report, final presentation

    End

    Reports

    Project plan

    4th October 2020

    A proposal of what will be achieved in the project, and the corresponding schedule.

    Interim report

    24th January 2021

    An intermediate detailed project report summarising the tasks accomplished in the first semester.

    Final report

    23rd April 2021

    A report presenting the details of our repository and concluding our findings during experiments.

    Team

    Dr. Luo Ruibang

    Supervisor

    Angel Woo

    BEng(CompSc)&BBA, IV

    Wu Xue

    BEng(CompSc), V

    Lee Kwanyoung

    BEng(CompSc), V