Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Proceedings of the 36th SIGCSE technical symposium on Computer science education
Adaptive genetic programming for option pricing
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
GP age-layer and crossover effects in bid-offer spread prediction
Proceedings of the 10th annual conference on Genetic and evolutionary computation
An Introduction to Natural Computing in Finance
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
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I examine the role of programming parameters in determining the accuracy of Genetic Programming for option pricing. I use Monte Carlo simulations to generate stock and option price data needed to develop a Genetic Option Pricing Program. I simulate data for two different stock price processes - a Geometric Brownian process and a Jump-Diffusion process. In the jump-diffusion setting, I seed the Genetic Program with the Black-Scholes equation as a starting approximation. I find that population size, fitness criteria, and the ability to seed the program with known analytical equations, are important determinants of the efficiency of Genetic Programming.