Abstract
This chapter describes the Genetic Programming methodology and illustrates its application for the pricing of options. I describe the various critical elements of a Genetic Program – population size, the complexity of individual formulas in a population, and the fitness and selection criterion. As an example, I implement the Genetic Programming methodology for developing an option pricing model. Using Monte Carlo simulations, I generate a data set of stock prices that follow a Geometric Brownian motion and use the Black–Scholes model to price options off the simulated prices. The Black–Scholes model is a known solution and serves as the benchmark for measuring the accuracy of the Genetic Program. The Genetic Program developed for pricing options well captures the relationship between option prices, the terms of the option contract, and properties of the underlying stock price.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
