Intraday FX Trading: An Evolutionary Reinforcement Learning Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{DBLP:conf/ideal/DempsterR02,
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author = "M. A. H. Dempster and Y. S. Romahi",
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title = "Intraday {FX} Trading: An Evolutionary Reinforcement
Learning Approach",
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booktitle = "Proceedings of Third International Conference on
Intelligent Data Engineering and Automated Learning -
IDEAL 2002",
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year = "2002",
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editor = "Hujun Yin and Nigel M. Allinson and
Richard T. Freeman and John A. Keane and Simon J. Hubbard",
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publisher = "Springer",
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series = "Lecture Notes in Computer Science",
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volume = "2412",
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pages = "347--358",
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address = "Manchester",
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month = "12-14 " # aug,
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keywords = "genetic algorithms, genetic programming, RL, GA",
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ISBN = "3-540-44025-9",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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URL = "http://mahd-pc.jbs.cam.ac.uk/archive/PAPERS/2002/WP3-2002.pdf",
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URL = "https://rdcu.be/djwpR",
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DOI = "doi:10.1007/3-540-45675-9_52",
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size = "12 pages",
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abstract = "We have previously described trading systems based on
unsupervised learning approaches such as reinforcement
learning and genetic algorithms which take as input a
collection of commonly used technical indicators and
generate profitable trading decisions from them. This
article demonstrates the advantages of applying
evolutionary algorithms to the reinforcement learning
problem using a hybrid credit assignment approach. In
earlier work, the temporal difference reinforcement
learning approach suffered from problems with
overfitting the in-sample data. This motivated the
present approach.
Technical analysis has been shown previously to have
predictive value regarding future movements of foreign
exchange prices and this article presents methods for
automated high-frequency FX trading based on
evolutionary reinforcement learning about signals from
a variety of technical indicators. These methods are
applied to GBPUSD, USDCHF and USDJPY exchange rates at
various frequencies. Statistically significant profits
are made consistently at transaction costs of up to 4bp
for the hybrid system while the standard RL is only
able to trade profitably up to about 1bp slippage per
trade.",
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notes = "Location: technical report WP03/2002
",
- }
Genetic Programming entries for
Michael Dempster
Yazann Romahi
Citations