Applying Genetic Regulatory Networks to Index Trading

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Title: Applying Genetic Regulatory Networks to Index Trading
Authors: Nicolau, Miguel
O'Neill, Michael
Brabazon, Anthony
Permanent link: http://hdl.handle.net/10197/8148
Date: 5-Sep-2012
Abstract: This paper explores the computational power of genetic regulatory network models, and the practicalities of applying these to real-world problems. The specific domain of financial trading is tackled; this is a problem where time-dependent decisions are critical, and as such benefits from the differential gene expression that these networks provide. The results obtained are on par with the best found in the literature, and highlight the applicability of these models to this type of problem.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): Springer 2012
Keywords: Evolutionary computation;Natural computing;Genetic regulatory networks;Financial prediction;Index trading
DOI: 10.1007/978-3-642-32964-7_43
Language: en
Status of Item: Peer reviewed
Is part of: Coelle Coello, C.A., Cutello, V., Deb, K., Forest, S., Giuseppe, N. and Pavone, M. (eds.). Proceedings (Part 2): Parallel Problem Solving from Nature - PPSN XII (Lecture Notes in Computer science Volume 3492)
Conference Details: 12th International Conference on Parallel Problem Solving from Nature, Taormina, Italy, 1-5 September 2012
Appears in Collections:Business Research Collection

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