Invited Speakers

Thomas F. Coleman

Ophelia Lazaridis University Research Chair
Professor, Combinatorics and Optimization, Waterloo
Director, Waterloo Research Institute in Insurance, Securities and Quantitative Finance (WatRISQ)
Fellow, Society for Industrial and Applied Mathematics (SIAM)

 

 

 

 

 

 

Matt Davison

Professor, Statistical and Actuarial Sciences, Western University
Director – School of Mathematical & Statistical Sciences
Fields Institute Fellow


Title: Where Data Science meets the Dismal Science   

Abstract
Banks and other financial institutions grant “Small” loans (up to and including half million dollar mortgages) are typically granted to applicants as the result of an automatic process in which the responses to a set of questions (about income, other assets debts, etc)  are combined into a score which is then compared to a threshold.  Applicants with a score better than a certain threshold are granted a loan with a given set of terms.   Exactly how the scoring algorithm works is, of course, to some degree confidential, but incentives to “game” the loan granting system nonetheless remain. In this talk I give an introduction to modern data-driven retail credit and discuss an iterated game in which some borrowers (or their agents) deliberately falsifies aspect of her application, while other borrowers do not. The third player here is the bank. High level strategy and policy conclusions are drawn.  (Joint with Cristian Bravo and Mimi Chong)

Bio
Formerly (2006-2016) Tier 2 Canada Research Chair in Quantitative Finance, Matt Davison is the director of the new School of Mathematical & Statistical Sciences at Western University in London Ontario. He has co-authored 67 papers, 9 book chapters, 13 refereed conference proceedings, and a patent, and is the author of the financial mathematics textbook   Quantitative Finance: A Simulation-based introduction using Excel. Matt works in the areas of commodities trading, green energy finance, financial risk management, and industrial mathematics, and draws upon techniques and insights from business, economics, engineering, mathematics, and statistics.


Bruno Rémillard

Professor, Decision Sciences, HEC Montréal


Title: Replication methods for financial indexes 

Abstract
In this talk I will present statistical tools that can be used in asset management either to track financial indexes or to create synthetic ones. These tools include copula models, optimal hedging, regression and filtering techniques. At first, these replication techniques were used to try to replicate hedge funds indexes, but nowadays they can also be used to construct Exchange Traded Funds.

Bio
Professor Rémillard did his PhD at Carleton University (Ottawa) and MSc in Mathematics at the University of Laval. Before joining HEC Montreal in 2001, he was a professor at the University of Trois-Rivières. He is a member of the GERAD research group. He is elected fellow of the International Statistical Institute. In 2003 he received the prize for the Best Paper published in Canadian Journal of Statistics, while in 1987 Pierre Robillard Award of Statistical Society of Canada (best Ph.D. thesis in probability or statistics defended at a Canadian university). He is the author of the book Statistical Methods for Financial Engineering, Chapman & Hall/CRC.

Le professeur Rémillard possède un doctorat en mathématiques de la Carleton University (Ottawa) et une maîtrise en mathématiques de l’Université Laval. Avant de se joindre à HEC Montréal en 2001, Bruno Rémillard a été professeur à l’Université du Québec à Trois-Rivières pendant plus de 10 ans. Membre du Groupe d’études et de recherche en analyse des décisions (GERAD) et détenteur du professorship en ingénierie financière de HEC Montréal, il a reçu en 2003 le prix du meilleur article de la part du Canadian Journal of Statistics et, en 2007, le prix Pierre-Laurin remis par HEC Montréal, ex æquo avec son collègue Bernard Sinclair-Desgagné. Ses domaines d’expertise ont trait à la volatilité stochastique, l’ingénierie financière, les processus empiriques, les séries chronologiques et le filtrage non linéaire. Il est auteur et coauteur de plusieurs publications.

 

Luis Seco

Professor, Department of Mathematics, University of Toronto
Director, Mathematical Finance Program
Director of RiskLab Toronto
President and CEO Sigma Analysis and Management


Title: Postmodernism in Finance: The Mathematics of Management Fees

Abstract
Low negative rates and the low performance environment are putting pressure on the investment business. In this talk we will analyze the valuations of fee structures, and propose frameworks where the Black- Scholes valuation of new fee structures delivers value to managers and investors alike.

Bio
Luis Seco is Professor of Mathematics at the University of Toronto, where he also directs the Mathematical Finance program and the RiskLab, a research laboratory in financial risk management. He is also the President and CEO of Sigma Analysis & Management, an asset management firm that specializes in hedge fund investments for institutional investors. He obtained his PhD at Princeton University and worked at Caltech.