Genetic Algorithms and Genetic Programming in Computational Finance

By Shu-Heng Chen. 2002

222 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Agent-Based Models and Human Subject Experiments (2004, unknown): “24 Chen et al. (2002) use a genetic programming algorithm to reach a similar conclusion in a median effort”
Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects (2014, background): “Thus GP applies the Darwinian theory of evolution to a population of computer programs of varying sizes and shapes, which run in various environments in order to produce forecasts at a high level of accuracy (Chen, 2002).”
Contemporary Symbolic Regression Methods and their Relative Performance (2021, methodology): “These attractive properties of SR have led to its application in a number of areas, such as physics [3], biology [4], clinical informatics [5], climate modeling [6], ﬁnance [7], and many ﬁelds of engineering [8–10].”
Oppositional biogeography-based optimization (2009, methodology): “In geophysics, EC has been applied to seismic wave inversion [90, 91, 92] and groundwater monitoring [93, 94].”