The financial sector is the second largest source of income in the Canadian economy. Over the last few years, machine learning and advanced quantitative techniques are disrupting our environment. As a result, there is an increase in demand for qualified professionals who know how and where to implement these advanced tools, yet there is still an increasing gap in training and education for professionals in the field or aspiring to enter the field.
Deep unsupervised Anomaly Detection in the derivatives market
Date : 3 December 2021, from 12PM to 1PM
Cédric POUTRÉ is a Ph.D. candidate in Financial Mathematics at the Université de Montréal. He is interested in the diverse applications of Machine Learning in high-frequency trading and market microstructure. Cédric is also a recipient of Fin-ML CREATE grant under the supervision of Professor Manuel Morales.
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By assembling a strong team of internationally renowned researchers across Canada, a remarkable support from major financial institutions, and a notable backing from the Institute for Data Valorization (IVADO) and the Natural Sciences and Engineering Research Council of Canada (NSERC), Fin-ML seeks to form a new generation of finance professionals to meet the modeling and implementation needs of the quantitative spectrum of the Canadian financial industry and contribute to its global competitiveness.
Our diversified team is composed of researchers, students and professionals with an internationally recognized scientific expertise covering a wide spectrum of fields at the crossroads of mathematics, computer science, artificial intelligence, business analytics and quantitative finance applications.
We offer several activities (workshops, conferences, seminars, etc..) geared towards finance students and professionals seeking to understand and implement innovative machine learning techniques.
Our NSERC-CREATE Program in Machine Learning in Quantitative Finance and Business Analytics is offered through a competition to students in participating universities across Canada.
We aim to conduct and implement innovative and multidisciplinary collaborative research projects, small or large in scale, in order to offer our researchers multiple opportunities for industrial experience.