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Type	Master's Thesis
Scope	Discipline-based scholarship
Title	Pricing of American Options in a Market Making Environment Using Artificial Neural Networks
Organization Unit	Quantitative Finance (Erich Walter Farkas)
Authors	David Anderson
Supervisors	Erich Walter Farkas Urban Ulrych
Language	English
Institution	University of Zurich
Faculty	Faculty of Business, Economics and Informatics
Date	2020
Abstract Text	Traditional Monte Carlo pricing methods for American options in a market making environment are too slow, impeding the ability to quote prices consistent with an ever-changing market environment. We propose a novel method for the valuation of American options by which market information, passed in the form of an implied volatility surface, is evaluated instantaneously using a feed-forward neural network. Utilising data generated using Monte Carlo methods, we propose a beginning-to-end framework for the creation of a neural network pricing system for a market making environment.
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