Graphs are a natural and ubiquitous representation for describing complex data structures. They are commonly used in a variety of fields, such as computer vision, bioinformatics, computer security, and social network analysis. The goal of this project is to test whether combining concepts from graph neural networks and reinforcement learning methods can provide an enhanced portfolio construction process. A key component of the project is defining how to represent the graph structure.