Portfolio Optimizer

Portfolio managers evaluate stocks to find those with the best expected returns, but they need risk measures to complete their decision-making process.
The project has the objective to give adequate risk metrics to portfolio managers for a given portfolio and a list of potential candidates.

Historical price values are useful to determine risk, but they could be better optimized to reflect the uncertainty given that historical values may not reflect future values.

The model which uses reinforcement learning should give portfolio managers better insights on their risk when they add a new stock to their portfolio.

The goal of the partner organization is to improve its knowledge on the matter as well as offering free access to the research made by the intern.

Faculty Supervisor:

Jose Garrido

Student:

Partner:

Inovestor

Discipline:

Mathematics

Sector:

Information and cultural industries

University:

Concordia University