Faculty Advisor

Wang, Gu

Faculty Advisor

Song, Qingshuo

Faculty Advisor

Li, Yanhua

Abstract

As computers increase their power, machine learning gains an important role in various industries. We consider how to apply this method of analysis and pattern identification to complement extant financial models, specifically option pricing methods. We first prove the discussed model is arbitrage-free to confirm it will yield appropriate results. Next, we apply a neural network algorithm and study its ability to approximate option prices from existing models. The results show great potential for applying machine learning where traditional methods fail. As an example, we study the implied volatility surface of highly liquid stocks using real data, which is computationally intensive, to justify the practical impact of the methods proposed.

Publisher

Worcester Polytechnic Institute

Date Accepted

2020-05-01

Major

Mathematical Sciences

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

Mathematical Sciences

Advisor Department

Computer Science

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