PortfolioRL’s goal is to use reinforcement learning techniques to optimize portfolio diversification allowing users to make more informed financial decisions. PortfolioRL aims to do this by providing AI, data-driven strategies that adapt to changing market conditions. We plan to achieve this by using PyTorch and existing financial datasets to create a robust RL model.
In addition to the core model, PortfolioRL would like to also develop an interactive web application (React, FastAPI, PostgreSQL) that allows users to visualize model outputs and experiment with various financial scenarios.