N. K. Chidambaran, Chi-Wen Jevons Lee, Joaguin R. Trigueros
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 folow a
jump-diffusion process. We also show that the Genetic Programming model
outperforms various other models in many different settings. Other
advantages of the Genetic Programming approach include its robustness to
changing environment, its low demand for data, and its computational
speed. Since genetic programs are flexible, self-learning and
sefl-improving, they are an ideal tool for practitioners.
Chidambaran: (212) 998-0318 chiddi@stern.nyu.edu
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