Mark Reesor
After receiving my bachelor’s degree in Mathematics from McGill University, I earned a master’s and PhD degree in Statistics from the University of Waterloo.
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Prior to joining Laurier, I worked as a consultant with federal government ministries, Alberta Treasury Branches, and as an analyst in the Financial Markets Department at the Bank of Canada.
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From 2002 until 2016, I was a tenured associate professor in the Department of Statistics and Actuarial Science at Western University, jointly appointed to the finance area at the Richard Ivey School of Business.
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In addition, I was a founding member of the Committee to Establish the National Institute of Finance, leading to the creation of the U.S. Office of Financial Research.
Areas of Interest
I have a varied research program that focuses on problems lying at the intersection of finance, actuarial science, risk management, operations research, statistics, simulation, economics, and law. Particular interest lies in the application of stochastic models in finance and financial regulations, and in problems with public policy implications.
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My works include investigations in personal finance, corporate finance, financial stability, securities class actions, risk management, and derivatives.
One line of research has focused on enhanced Monte Carlo methods for pricing and hedging complex financial derivatives while another line of research centers on calculating damages in secondary market securities class actions.
Publications
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Zhou, Alan (Xingua) and R. Mark Reesor. “Misrepresentation and Capital Structure: Quantifying the Impact on Corporate Debt Value.” Journal of Corporate Finance (2015).
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Metzler, Adam and R. Mark Reesor. “Valuation and Analysis of Zero-Coupon Contingent Capital Bonds.” Mathematics and Financial Economics (2015).
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Naseem, Almas and R. Mark Reesor. “Risk and Reward of Home Equity Borrowing for Investment in Canada, A Stochastic Analysis.” Computational Management Science (2015).
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Kan, Felix (Kin Hung) and R. Mark Reesor. “Bias Reduction for Pricing American Options by Least-Squares Monte Carlo.” Applied Mathematical Finance (2012).
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Whitehead, Tyson, Matt Davison and R. Mark Reesor. “A Bias Reduction Technique for Monte Carlo Pricing of Early-exercise Options.” Journal of Computational Finance (2012).