About the Challenge

Welcome to Algo Equity Trading Challenge 2022 (Global).

Ideate your trading algorithms, test on a robust back-testing platform, and compete to make a name for yourself! Gain professional industry knowledge and practical skills to prepare yourself as the next-gen algo-trading professional.

This Challenge is open to public. Create teams of 1~4 members with diverse skills (maths, statistics, finance, coding, presentation) and register by 17 Jun 2023.



ideate

1st Round: Ideate

Registered teams of 1-4 members will prepare a ppt less than 15 slides consisting of:

  • Executive summary
  • Trading idea description
  • Trading logic
  • Team biography
  • Implementation detail

Coding is not required in this round


Submission deadline: 21 Jul 2023

Result announced: 31 Jul 2023


test

2nd Round: Test

Teams will code their trading algorithm and test on ALGOGENE's back-testing engine, then submit the code


Judges will backtest trading algorithms for return, volatility, robustness and practicality to select advancing teams


Submission deadline: 23 Sep 2023

Result announced: 31 Sep 2023


compete

Final Round: Compete

Each team need to compete in out-sample forward test and live paper trading


Live paper trading will last for 2 months from 1-Oct-2023 to 30-Nov-2023


Teams will present trading plan to judges in a 5-minute pitch session on final day


Judges will select winners in each of these categories:

  • Best Sharpe
  • Best Market Return
  • Best Strategy Design

Final Day: 10 Dec 2023


Judging Criteria

Registration

Form a team of 1~4 members with diverse skills (maths, statistics, finance, coding, presentation) and register by 17 Jun 2023.

Resources

The dataset provided includes the tick level bid-ask updates, and covers data from normal trading days from Jan 2016 to Dec 2021. Kindly note that data provided is strictly for trading strategy prototyping purposes only. Final round evaluations will be carried out using a new data set with the same structure but from a different time period. Thus, over-fitting of the data set is discouraged.


Trading Products

  • US & HK Large Cap
  • ETF

Datasets

Provide access to required historical data for model development and testing

  • Market data
  • Corporate data
  • News
  • Economic Statistics

System

Access to ALGOGENE's back-testing engine, cloud simulation environment and relevant technical documents


Parties

Event Sponsors:

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