Applications of Genetic Programming to Finance and Economics: Past, Present, Future

While the origins of Genetic Programming (GP) stretch back over fifty years, the field of GP was invigorated by John Koza’s popularisation of the methodology in the 1990s. A particular feature of the GP literature since then has been a strong interest in the application of GP to real-world problem domains. One application domain which has attracted significant attention is that of finance and economics, with several hundred papers from this subfield being listed in the Genetic Programming Bibliography. In this article we outline why finance and economics has been a popular application area for GP and briefly indicate the wide span of this work. However, despite this research effort there is relatively scant evidence of the usage of GP by the mainstream finance community in academia or industry. We speculate why this may be the case, describe what is needed to make this research more relevant from a finance perspective, and suggest some future directions for the application of GP in finance and economics

Dynamic environments can speed up evolution with genetic programming

We present a study of dynamic environments with genetic programming to ascertain if a dynamic environment can speed up evolution when compared to an equivalent static environment. We present an analysis of the types of dynamic variation which can occur with a variable-length representation such as adopted in genetic programming identifying modular varying, structural varying and incremental varying goals. An empirical investigation comparing these three types of varying goals on dynamic symbolic regression benchmarks reveals an advantage for goals which vary in terms of increasing structural complexity. This provides evidence to support the added difficulty variable length representations incur due to their requirement to search structural and parametric space concurrently, and how directing search through varying structural goals with increasing complexity can speed up search with genetic programming.Science Foundation Irelandti, ab - TS 28.03.1

Product invention as a complex adaptive system : an investigation of the impact of inventors' searh heuristics on the rate of invention

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Recent patents on genetic programming

Genetic Programming is a form of Natural Computing which adopts principles from neo-Darwinian evolution to automatically solve problems. It is a model induction method in that both the structure and parameters of the solution are explored simultaneously. Genetic Programming is a particularly interesting method as it is claimed to be an invention machine, producing solutions to problems that are competitive and in some cases superior to those produced by human experts. Its best solutions have become patentable inventions in their own right. In this article, we overview some of the recent patents relating to Genetic Programming over the past three years. In light of the number and diversity of patent applications during this period, it is clear that Genetic Programming is a vibrant field of research, which is having a significant impact on real-world applications, and is demonstrating clear commercial potential.Science Foundation IrelandLink to journal homepage is a condition set by the publisher - AV 29/10/2010 ti, ke - TS 18.11.1