WatStreet is UW’s only quantitative finance team. We are focused on educating members about financial investment strategies and also are pushing to develop new novel alogrithms, where we seek to write papers and present them in upcoming conferences.
This is my first term being part of a design team! Design teams are generally smaller and more focused compared to being a club exec, due to not needing to appeal to general members. I joined the team to further scratch the itch of creation and to get more invovled in the world of ML research, after my positive experience at Western University.
ML Engineer (S25)
For this term, I worked on the Correlation Testing subteam. We explored this paper, which leveraged Reinforcement Learning to find correlated stock pairings to apply statistical arbitrage. We perfomed a proof-of-concept by using the same hyper-parameters to create a similar neural network to find these pairs. We also investigated the given pairings and found that they are in fact heavily correlated.
It was really inspiring to meet a new team of cracked students who are applying ML techniques to real-world scenarios, and I found the development cycle to be a lot more formal than when I worked alone. It reminded me heavily of my work terms and I’ll be sure to rejoin, as the WatStreet projects generally have a lifecycle longer than a term.