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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11424

Title: A Genetic Algorithm for Option Pricing: The American Put Option
Authors: Ackora-Prah, Joseph
Amponsah, Samuel Kwame
Andam, Perpetual Saah
Gyamerah, Samuel Asante
Keywords: Options
Geometric Brownian Motion
Genetic Algorithm
Black-Scholes Model
Issue Date: 2014
Publisher: Applied Mathematical Sciences
Citation: Applied Mathematical Sciences, Vol. 8, 2014, no. 65, 3197 - 3214; http://dx.doi.org/10.12988/ams.2014.43174
Abstract: The search for a better option pricing model continues to nd the one that outperforms the existing ones in the nancial market. In this paper, we present a Genetic Algorithm (GA) to price a xed term American put option when the underlying asset price is Geometric Brownian Motion. The Genetic Algorithm has a better approximation of the relationship between the option price and its contract terms. Our method produces a perfect and a minimum option price that outperforms other models like the Black-Scholes under the same conditions. The method requires minimum assumptions and can easily adapt to changes and uncertainties in the fi nancial environments.
Description: An article published by Applied Mathematical Sciences, Vol. 8, 2014, no. 65, 3197 - 3214; http://dx.doi.org/10.12988/ams.2014.43174
URI: http://hdl.handle.net/123456789/11424
Appears in Collections:College of Science

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