Synthetic Data: A New Regulatory Tool
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Joint Event hosted by the Global Risk Institute and Rotman FinHub
Please join us for this webinar.
Using machine learning tools to generate synthetic data, Professor John Hull and his research team (Jay Cao, Jacky Chen, Zissis Poulos, Dorothy Zhang) have some promising results that suggest that synthetic data can be used to determine the capital requirements of banks. Professor Hull will walk through the research and discuss the opportunity to apply this research to real-time capital calculations.
Academic Director, Rotman FinHub; Maple Financial Group Chair in Derivatives and Risk Management
BIO: He is an internationally recognized authority on derivatives and risk management and has many publications in this area. His work has an applied focus. His areas of research have included the impact of stochastic volatility on the pricing and hedging of options, the valuation of interest rate derivatives and credit derivatives, the calculation of value at risk, the evaluation of model risk, and the regulation of financial institutions. He was, with Alan White, one of the winners of the Nikko-LOR research competition for his work on the Hull-White interest rate model, which is widely used by practitioners. In 1999 he was voted Financial Engineer of the Year by the International Association of Financial Engineers. He has acted as consultant to many North American, Japanese, and European financial institutions. He has won many teaching awards, including University of Toronto’s prestigious Northrop Frye award.
He has written three books: “Risk Management and Financial Institutions” (now in its 4th edition), “Options, Futures, and Other Derivatives” (now in its 9th edition) and “Fundamentals of Futures and Options Markets” (now in its 9th edition). The books have been translated into many languages and are widely used in trading rooms throughout the world, as well as in the classroom.
Dr. Hull is co-director of Rotman’s Master of Finance program and Rotman’s new Master of Financial Risk Management program. In addition to the University of Toronto, Dr. Hull has taught at York University, University of British Columbia, New York University, Cranfield University, and London Business School.
Assistant Director, Data Science Applications, Bank of Canada;, Professor, School of Mathematics and Statistics and School of Computer Science, Carleton University
BIO: Dave Campbell runs a research lab and train the next generation talent for data science, computational statistics, and machine learning positions. I extract evidence based decisions while paying attention to data quality and operational constraints. I open black boxes to see how things work and fix them where they fail.
I work at the intersections of statistics with computer science, numerical analysis, applied mathematics, and optimization. My research area is statistical modelling and algorithms.
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