Joint University Algo FX Trading Challenge 2021
Background:
The Joint-University Algo FX Trading Challenge 2021, organized by Algo Challenge Association, aims to identify and nurture the next generation of algo trading talents and advance the development of the FinTech industry in Hong Kong. The Challenge focuses on Hong Kong Equity Market, including stocks, futures, and options. Participating students implement their strategies and ideate the trading algorithms to compete with counterparts from other universities in Hong Kong and overseas on various metrics such as Return, Sharpe ratio and Strategy Design.
The competition consisted of three rounds. Participating teams submitted trading proposals in the 1st Round (Ideate). In the 2nd Round (Test), teams were required to write trading algorithms and test on the organizer’s proprietary platform. Shortlisted teams advanced to the Final Round (Compete) where participants’ strategies were competed based on a two-month live paper trading from February to March 2022, and participants were required to make a 5-minute pitch on their trading plan to judges on the final presentation day on April 3, 2022.
Website / Image URL:
https://algochallenge.org/globalfx2021/
Award(s):
2nd Place in Best Strategy Design
3rd Place in Best Return
Awardee(s):
Team List:
Mr. Lai Tsz Tong, BSc(QFin), Year 3 (photo position: 1st from right)
Mr. Tang King Hung, BSc(QFin), Year 3 (photo position: middle)
Students Sharing:
“We were able to apply the knowledge in textbooks to real-world situations to evaluate portfolio performance in the Challenge. We tried to replicate a pair trading strategy described in a book. The book described a brief trading framework and we needed to implement the details and made choices based on backtest results on our own. Besides gaining professional knowledge and practical skills in algo-trading, it was a valuable opportunity to sharpen our problem-solving skills and presentation skills. We were honored to be ranked the 2nd Place in Best Strategy Design and 3rd Place in Best Return in the Challenge. We would like to thank our alumni, Ms. Yoyo Chan (BSc(QFin) Class of 2020), for assisting us throughout the competition and guiding us in different aspects.”
(by Lai Tsz Tong and Tang King Hung)
