Gavin Orok
Quantitative Finance
Cohort 2022
University of Waterloo
Quantitative Finance
Cohort 2022
University of Waterloo
Quantitative Finance
University of Waterloo
Master's
I earned my Bachelor of Math with Dean's Honours from the University of Waterloo. I have a year's worth of math research experience in pure and financial math. I also have a good computing background, having earned a Computing Option with my degree and having experience in Python, R and C.
I completed my Master's of Quantitative Finance degree at the University of Waterloo with sponsorship from the Fin-ML program. I studied improvements to reinforcement learning methods using the numerical methods RQMC and Aray-RQMC. In my free time I like playing video games, playing guitar, and drawing.
Application of GPT to automate financial newsletter production
Conference showcasing the work done during the FIn-Ml internship. This project employed the LLM GPT-4 to automate financial newsletter production and conducted research on the extent to which it improved the organization's level of efficiency.
Optimization of Policy Evaluation and Policy Improvement Methods in Portfolio Optimization using Quasi-Monte Carlo Methods
My master's thesis investigated the extent to which the numerical methods Array-RQMC and RQMC could improve the performance of policy evaluation and policy iteration methods in reinforcement learning for portfolio optimization applications. The research determined that in the context of the developed portfolio optimization environment, for a strategic choice of the reordering function Array-RQMC significantly improves on both RQMC and MC for policy iteration, and RQMC significantly reduces the variance compared to MC for policy evaluation.
