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GECCO
2007
Springer

Adaptive genetic programming for option pricing

9 years 7 months ago
Adaptive genetic programming for option pricing
Genetic Programming (GP) is an automated computational programming methodology, inspired by the workings of natural evolution techniques. It has been applied to solve complex problems in multiple domains including finance. This paper illustrates the application of an adaptive form of GP, where the probability of crossover and mutation is adapted dynamically during the GP run, to the important real-world problem of options pricing. The tests are carried out using market option price data and the results illustrate that the new method yields better results than are obtained from GP with fixed crossover and mutation rates. The developed method has potential for implementation across a range of dynamic problem environments. Categories and Subject Descriptors J.m [Miscellaneous]: Finance; I.2.6 [Artificial Intelligence]: Parameter learning General Terms Economics Keywords Genetic Programming, option pricing
Zheng Yin, Anthony Brabazon, Conall O'Sullivan
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Zheng Yin, Anthony Brabazon, Conall O'Sullivan
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