2014Applied Mathematical SciencesOpen access

A genetic algorithm for option pricing: the American put option

Joseph Ackora-Prah, S. K. Amponsah, Perpetual Saah Andam, Samuel Asante Gyamerah

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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. 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

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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

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Available 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

Key concepts: Valuation of options, Computer science, Algorithm, Economics, Financial economics

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