Is Technical Analysis in the Foreign Exchange Market
Profitable? A Genetic Programming Approach
C. Neely, P. Weller, and R. Dittmar. The Journal of Financial and Quantitative Analysis, 32 (4):
405--426(December 1997)
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.
%0 Journal Article
%1 neely:1997:JFQA
%A Neely, Christopher J.
%A Weller, Paul A.
%A Dittmar, Rob
%D 1997
%J The Journal of Financial and Quantitative Analysis
%K algorithms, genetic programming
%N 4
%P 405--426
%T Is Technical Analysis in the Foreign Exchange Market
Profitable? A Genetic Programming Approach
%U http://links.jstor.org/sici?sici=0022-1090%28199712%2932%3A4%3C405%3AITAITF%3E2.0.CO%3B2-T
%V 32
%X 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.
@article{neely:1997:JFQA,
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.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Neely, Christopher J. and Weller, Paul A. and Dittmar, Rob},
biburl = {https://www.bibsonomy.org/bibtex/271b59b1e26f803442aa42041e229fe81/brazovayeye},
interhash = {cfe07e8adeb232db3c292ca44a975b56},
intrahash = {71b59b1e26f803442aa42041e229fe81},
issn = {00221090},
journal = {The Journal of Financial and Quantitative Analysis},
keywords = {algorithms, genetic programming},
month = {December},
notes = {Also available as working paper 1996-006C
http://research.stlouisfed.org/wp/1996/96-006.pdf},
number = 4,
pages = {405--426},
size = {43 pages},
timestamp = {2008-06-19T17:48:07.000+0200},
title = {Is Technical Analysis in the Foreign Exchange Market
Profitable? {A} Genetic Programming Approach},
url = {http://links.jstor.org/sici?sici=0022-1090%28199712%2932%3A4%3C405%3AITAITF%3E2.0.CO%3B2-T},
volume = 32,
year = 1997
}