TY - JOUR
T1 - A genetic algorithm for option pricing
T2 - The American put option
AU - Ackora-Prah, Joseph
AU - Amponsah, Samuel Kwame
AU - Andam, Perpetual Saah
AU - Gyamerah, Samuel Asante
N1 - Publisher Copyright:
© 2014 Joseph Ackora-Prah et al.
PY - 2014
Y1 - 2014
N2 - The search for a better option pricing model continues to find the one that outperforms the existing ones in the financial market. In this paper, we present a Genetic Algorithm (GA) to price a fixed 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 financial environments.
AB - The search for a better option pricing model continues to find the one that outperforms the existing ones in the financial market. In this paper, we present a Genetic Algorithm (GA) to price a fixed 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 financial environments.
KW - Black-Scholes model
KW - Genetic algorithm
KW - Geometric brownian motion
KW - Options
UR - https://www.scopus.com/pages/publications/84902355194
U2 - 10.12988/ams.2014.43174
DO - 10.12988/ams.2014.43174
M3 - Article
AN - SCOPUS:84902355194
SN - 1312-885X
SP - 3197
EP - 3214
JO - Applied Mathematical Sciences
JF - Applied Mathematical Sciences
IS - 65-68
ER -