Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{neely:1997:JFQA,
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author = "Christopher J. Neely and Paul A. Weller and
Rob Dittmar",
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title = "Is Technical Analysis in the Foreign Exchange Market
Profitable? A Genetic Programming Approach",
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journal = "The Journal of Financial and Quantitative Analysis",
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year = "1997",
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volume = "32",
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number = "4",
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pages = "405--426",
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month = dec,
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keywords = "genetic algorithms, genetic programming",
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ISSN = "00221090",
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URL = "http://links.jstor.org/sici?sici=0022-1090%28199712%2932%3A4%3C405%3AITAITF%3E2.0.CO%3B2-T",
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size = "43 pages",
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abstract = "Using genetic programming techniques to find technical
trading rules, we find strong evidence of economically
significant out-of-sample excess returns to those rules
for each of six exchange rates over the period
1981-1995. Further, when the dollar/Deutsche mark rules
are allowed to determine trades in the other markets,
there is significant improvement in performance in all
cases, except for the Deutsche mark/yen. Betas
calculated for the returns according to various
benchmark portfolios provide no evidence that the
returns to these rules are compensation for bearing
systematic risk. Bootstrapping results on the
dollar/Deutsche mark indicate that the trading rules
detect patterns in the data that are not captured by
standard statistical models.",
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notes = "Also available as working paper 1996-006C
http://research.stlouisfed.org/wp/1996/96-006.pdf",
- }
Genetic Programming entries for
Christopher J Neely
Paul A Weller
Rob Dittmar
Citations