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GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
13 years 8 months ago
Genetic programming for quantitative stock selection
We provide an overview of using genetic programming (GP) to model stock returns. Our models employ GP terminals (model decision variables) that are financial factors identified by...
Ying L. Becker, Una-May O'Reilly
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
14 years 2 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
GECCO
2000
Springer
122views Optimization» more  GECCO 2000»
14 years 2 months ago
Genetic Programming with Statically Scoped Local Variables
This paper presents an extension to genetic programming to allow the evolution of programs containing local variables with static scope which obey the invariant that all variables...
Evan Kirshenbaum
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
14 years 5 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 prob...
Zheng Yin, Anthony Brabazon, Conall O'Sullivan
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 3 months ago
Evolving stochastic processes using feature tests and genetic programming
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Brian J. Ross, Janine H. Imada