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

Published online by Cambridge University Press:  06 April 2009

Christopher Neely,
Paul Weller and
Rob Dittmar
Christopher Neely
Affiliation:
Research Department, Federal Reserve Bank of St. Louis, St. Louis, MO 63011
Paul Weller
Affiliation:
Department of Finance, College of Business Administration, University of Iowa, Iowa City, IA 52242.
Rob Dittmar
Affiliation:
Research Department, Federal Reserve Bank of St. Louis, St. Louis, MO 63011
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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.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 32 , Issue 4 , December 1997, pp. 405 - 426
Copyright
Copyright © School of Business Administration, University of Washington 1997

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