UBS Quant Hackathon 2020

UBS Quant Hackathon 2020 is calling for registration now.

In this online hackathon, participants shall combine their innovative ideas and Quant skills to tackle real-life financial industry challenges. Participating teams, comprise of 2 – 5 members, can register for two competitions, namely Outperform the S&P 500 Index and Machine Learning for Complex Pricing Models. Teams can enter either one of the competitions or both to increases the chances to qualify for the final round. All submissions will be assessed based on below judging criteria and 4 teams will be selected per region (Asia, Europe, America) for the final round. 12 shortlisted teams are required to code and build out their proposals, and give a 10-minute presentation/demonstration followed by a 5-minute Q&A session in the final hackathon on October 30, 2020.

Judging Criteria – 1st Round

Outperform the S&P 500 index* Competition

Information Ratio (50%), Diversification (30%) and Robustness (20%)

Machine Learning for Complex Pricing Models Competition

Maximum Absolute Error (50%), Mean Squared Error (30%) and Explainability (20%)

Awards and Benefits

Champion: USD 10,000 ^

1st Runner-up: USD 7,000 ^

2nd Runner-up: USD 3,000 ^

^ Each prize may be subject to withholding and other taxes, and the amount actually received by a Winning Team may be less than as stated UBS will not be grossing up the amount of any Prize for tax.

Timeline

September 10, 2020: Research starts

September 27, 2020: Leaderboards open with ranking and points system (Points system is used to select the finalists, points start accumulating on 20 September)

October 11, 2020: Deadline for online submission

October 23, 2020: Announcement of shortlisted teams for the final live Hackathon

October 30, 2020: Final Hackathon

How to join

• Sign up HERE individually and register your team name and team members
• Each team should comprises of 2 – 5 members
• University students (including undergraduates, postgraduates and PhD students) are eligible to join

Please refer to the competition website HERE for more details.

Disclaimer:

1. Our School will not be responsible for any expenses incurred in this Competition.
2. The data collected through the online application is solely administered by the organizers. The School shall not be held liable in the case that disputes, loss or any other situations arise.