Date of Award
Spring 5-15-2020
Degree Name
Master of Arts (AM/MA)
Degree Type
Thesis
Abstract
An American call (put) option is a contract that gives the holder the right, but not the obligation, to buy (sell) one unit of an asset (typically, stock) at a prespecified price (called strike price) at any desired time before a preset expiration time of the contract. The associated option pricing problem plays an important role in modern financial markets and one way to solve this is by searching for the optimal exercise policy, i.e., find the optimal time to exercise so that maximal reward is achieved. In this thesis, we shall discuss the modern Least Square Policy Iteration Method to solve the American option pricing problem based on Reinforcement Learning and compare it to the method of the Longstaff-Schwartz Method and the Finite Difference Method.
Language
English (en)
Chair and Committee
Professor José E. Figueroa-López.
Committee Members
Professor Mladen Victor Wickerhauser and Professor Jimin Ding.
Recommended Citation
Hu, Chenshan, "American Option Pricing: From PDE Numerical Solutions to Simulation-Based Methods and Reinforcement Learning." (2020). Arts & Sciences Electronic Theses and Dissertations. 2035.
https://openscholarship.wustl.edu/art_sci_etds/2035