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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/6663

Title: A Genetic Algorithm for option pricing
Authors: Saah, Andam Perpetual
Issue Date: 30-Oct-2014
Abstract: The search for a better option pricing model continues to nd the one that outperforms the existing ones in the nancial market. We present a Genetic Algorithm 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. Our method requires minimum assumptions and can easily adapt to changes and uncertainties in the nancial environments.
Description: A thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fufillment of the requirement for the Degree of Master of Philosophy (Applied Mathematics), 2014
URI: http://hdl.handle.net/123456789/6663
Appears in Collections:College of Science

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