Pascal Letourneau Ph.D. Finance, Assistant Professor, Risk Management, Option pricing, Numerical methods

About
I am a quantitative problem solver operating at the intersection of academic rigor and active trading.
My career is defined by a balance of foundational theory and market reality. As an Associate Professor (soon Full Professor) of Finance, I specialize in the computational complexities of derivatives, with a deep expertise in numerical methods and American option pricing. I apply my knowledge in my teaching and my trading.

For over six years, I have actively traded options, using my own capital to validate forecasting models and refine applied risk management strategies in real-time. This experience grounds my work; whether I am teaching investments or consulting on quantitative methods, I combine the precision of a researcher with the practicality of a trader.

Currently, I am focused on applying Machine Learning and forecasting models to the implied volatility surface. This work has sparked a new curiosity in behavioral finance, specifically investigating how investor psychology drives pricing anomalies in the option markets. I help organizations and students alike look past the standard models to find sharper, data-driven solutions to complex pricing puzzles.