Genetic programming with Monte Carlo simulation for option pricing

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "N. K. Chidambaran",
  title =        "Genetic programming with Monte Carlo simulation for
                 option pricing",
  booktitle =    "Proceedings of the 2003 Winter Simulation Conference",
  year =         "2003",
  editor =       "S. Chick and P. J. Sanchez and D. Ferrin and 
                 D. J. Morrice",
  volume =       "1",
  pages =        "285--292",
  address =      "New Orleans, USA",
  month =        "7-10 " # dec,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-8132-7",
  URL =          "",
  size =         "8 pages",
  abstract =     "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.",
  notes =        "details from ieee",

Genetic Programming entries for N K Chidambaran