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ECGA vs. BOA in discovering stock market trading experts

Published: 07 July 2007 Publication History

Abstract

This paper presents two evolutionary algorithms, ECGA and BOA, applied to constructing stock market trading expertise, which is built on the basis of a set of specific trading rules analysing financial time series of recent price quotations. A few modifications of ECGA are proposed in order to reduce the computing time and make the algorithm applicable for real-time trading. In experiments carried out on real data from the Paris Stock Exchange, the algorithms were compared in terms of the efficiency in solving the optimization problem, in terms of the financial relevance of the investment strategies discovered as well as in terms of the computing time.

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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
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Published: 07 July 2007

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Author Tags

  1. bayesian optimization algorithm
  2. decision support systems
  3. estimation of distribution algorithms
  4. extended compact genetic algorithm
  5. financial time series
  6. stock market expertise

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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  • (2013)Usage patterns of trading rules in stock market trading strategies optimized with evolutionary methodsProceedings of the 16th European conference on Applications of Evolutionary Computation10.1007/978-3-642-37192-9_24(234-243)Online publication date: 3-Apr-2013
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