Master's in Statistics Oral Thesis Defense: "Comparing Reinforcement Learning and Statistical Learning Methods for American option pricing."

Speaker: Chenshan Hu, Washington University in Saint Louis

Abstract: American option is an option contract, call (i.e. buy) or put (i.e. sell), that allows the owner to exercise whenever it is in the money before expiry, or leave it to expire if out of the money. This would be the option of interest we would like to study. The associated option pricing problem plays an important role in the modern financial markets and one way to solve this is by searching for an optimal policy, i.e., find the optimal time to exercise so that maximal reward is achieved.

In this thesis, we shall discuss and compare different methods, both Refinforcement Learning methods (RL) and classical Statistical Learning methods, to solve the Optimal Stopping Problems for the American Options.

Host: Jose Figueroa-Lopez

(Access Zoom Presentation HERE)