abstract = "We propose a methodology of Genetic Programming to
approximate the relationship between the option price,
its contract terms and the properties of the underlying
stock price. An important advantage of the Genetic
Programming approach is that we can incorporate
currently known formulas, such as the Black-Scholes
model, in the search for the best approximation to the
true pricing formula. Using Monte Carlo simulations, we
show that the Genetic Programming model approximates
the true solution better than the Black-Scholes model
when stock prices follow a jump-diffusion process. We
also show that the Genetic Programming model
outperforms various other models when pricing options
in the real world. Other advantages of the Genetic
Programming approach include its low demand for data,
and its computational speed.
Published previously in: Computational Finance
Proceedings of the Sixth International Conference,
Leonard N. Stern School of Business, January 1999. MIT
Press, Cambridge, MA",