A Genetic Algorithm for option pricing
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Date
2014-10-30
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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),