Financial Modelling: options pricing, financial econometrics, stochastic processes, interest rate models, portfolio theory, energy finance, regulatory risk, credit risk.
This discipline studies the risk inherent in the financial markets in a rigorous mathematical way. Tools used range from numerical solution of partial differential equations to advanced methods in stochastic processes.
If you are interested in graduate work in this research area, direct your application to the Department of Statistical and Actuarial Sciences.
- Matt Davison - Computational finance, energy finance, real options, commodity markets, portfolio theory, risk management. (Joint with Applied Mathematics.)
- Marcos Escobar - Pricing exotic products, Dynamic portfolio optimization
- Reg Kulperger - Inference, bootstrapping, smoothing techniques, asymptotic methods, applied stochastic modelling, mathematical finance.
- Xiaoming Liu - Stochastic processes, finsurance, longevity risk.
- Roge Mamon - Hidden markov models, options pricing, stochastic processes.
- Ian McLeod - Time series analysis, data mining, bayesian analysis, statistical software development.
- Adam Metzler - Credit risk, financial regulation, coco bonds, correlation modelling. (At Wilfrid Laurier University, but actively supervises Ph.D. students in financial mathematics at Western.)
- Mark Reesor - Computational finance, options pricing, legal financial risk, credit risk. (At Wilfrid Laurier University, but actively supervises Ph.D. students at Western.)
- Hristo Sendov - Optimization, variational analysis, financial mathematics.
- Lars Stentoft - Computational finance, options pricing, longevity risk, financial econometrics. (Joint with Economics.)
- Hao Yu - Statistical computing, parallel programming, financial time series, stochastic modelling, approximation in statistics and probability.