Pricing American Options by Using Particle Swarm Optimization

Abstract

In this ever-changing world there are a lot of new derivatives which we never learn or know Therefore the pricing of derivatives has became an important issue Most early scholars and investors used traditional evaluation models such as Black-Scholes model (BSM) and the Binomial Trees to price derivatives many assumptions or applications of which may not be true but also provide a standard for us In recent years more and more scholars have tried to obtain more accurate commodity values through novel algorithms such as bio-inspired or biological algorithms This paper would like to evaluate the option by particle swarm optimization and the particle swarm optimization is an algorithm developed by the behavior of birds foraging and is used to solve optimization problems The advantage of particle swarm optimization is that it can calculate two variables at the same time (stock price and time ) and make the evaluation of American option more efficient PSO can also be used to calculate European options and can also improve some of the shortcomings of the traditional model

Date of Award	2020
Original language	English
Supervisor	Yu-Hong Liu (Supervisor)