Investment portfolio design and optimal execution of automated trading strategies: An exploratory research program

Non-parametric models such as supervised and unsupervised machine learning algorithms seem to be an interesting choice when trying to extract decision-making signals out of this ever-increasing volume of information. These models have been used extensively in the last decades and are now more relevant than ever thanks to the development of new techniques in artificial intelligence and increasing power and scalability of numerical computations. In this project, we set to explore the direct application of such methods and mathematical technology in the design and testing of algorithmic trading strategies and portfolio selection and optimization. This exploratory research program seeks to gain first-hand insight as to the challenges in data collection and curation that is required as well as delivering the enhanced strategies and portfolios resulting from such implementations.

Faculty Supervisor:

Manuel Morales;Alejandro Murua;Mohamed Tarik Moutacalli;Jia Yuan Yu;Erick Delage;Christian Dorion;Frédéric Godin

Student:

Partner:

Golden Square Mile Asset Management;Quantolio Financial Technologies Inc

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

Concordia University; HEC Montréal; Université de Montréal; Université du Québec à Rimouski

Program: