Identifying market price levels using differential evolution

Authors:
Michael Mayo
Affiliations:
University of Waikato, Hamilton, New Zealand
Venue:
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Year:
2013

Citing 2
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Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

Journal of Global Optimization
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)

Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)

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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.