Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach

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@Article{neely:1997:JFQA,

• author = "Christopher J. Neely and Paul A. Weller and Rob Dittmar",
• title = "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach",
• journal = "The Journal of Financial and Quantitative Analysis",
• year = "1997",
• volume = "32",
• number = "4",
• pages = "405--426",
• month = dec,
• keywords = "genetic algorithms, genetic programming",
• ISSN = "00221090",
• URL = "http://links.jstor.org/sici?sici=0022-1090%28199712%2932%3A4%3C405%3AITAITF%3E2.0.CO%3B2-T",
• size = "43 pages",
• 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.",
• 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