Publication:
Identifying Market Price Levels Using Differential Evolution

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price levels.pdf (321.88 KB)

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https://hdl.handle.net/10289/7607

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10.1007/978-3-642-37192-9_21

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This is an author’s accepted version. The original publication is available at www.springerlink.com.
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Abstract

Evolutionary data mining is used in this paper to investigate the concept of support and resistance levels in financial markets. Specifically, Differential Evolution is used to learn support/resistance levels from price data. The presence of these levels is then tested in out-of-sample data. Our results from a set of experiments covering five years worth of daily data across nine different US markets show that there is statistical evidence for price levels in certain markets, and that Differential Evolution can uncover them.

Citation

Mayo, M. (2013). Identifying market price levels using differential evolution. In A.I. A.I. Esparcia-Alc´azar et al. (Eds.): 16th European Conference, EvoApplications 2013, Vienna, Austria, April 3-5, 2013, Lecture Notes in Computer Science, Volume 7835 (pp. 203-212). Berlin, Germany: Springer-Verlag Berlin Heidelberg.

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Conference Contribution

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2013

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Springer Berlin Heidelberg

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Keywords

differential evolution, finance, support and resistance, Machine learning

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Computing and Mathematical Sciences Papers