Technical analysis is aimed at devising trading rules
capable of exploiting short-term fluctuations on the
financial markets. Recent results indicate that this
market timing approach may be a viable alternative to
the buy-and-hold approach, where the assets are kept
over a relatively long time period. we propose genetic
programming as a means to automatically generate such
short-term trading rules on the stock markets. Rather
than using a composite stock index for this purpose,
the trading rules are adjusted to individual stocks.
Computational results, based on historical pricing and
transaction volume data, are reported for 14 Canadian
companies listed on the Toronto stock exchange
market.
%0 Journal Article
%1 Potvin:2004:COR
%A Potvin, Jean-Yves
%A Soriano, Patrick
%A Vallee, Maxime
%D 2004
%J Computers & Operations Research
%K algorithms, genetic programming
%N 7
%P 1033--1047
%T Generating trading rules on the stock markets with
genetic programming
%U http://www.sciencedirect.com/science/article/B6VC5-48GVPS3-1/2/a068a76df94cb8449f6ef7782615fc87
%V 31
%X Technical analysis is aimed at devising trading rules
capable of exploiting short-term fluctuations on the
financial markets. Recent results indicate that this
market timing approach may be a viable alternative to
the buy-and-hold approach, where the assets are kept
over a relatively long time period. we propose genetic
programming as a means to automatically generate such
short-term trading rules on the stock markets. Rather
than using a composite stock index for this purpose,
the trading rules are adjusted to individual stocks.
Computational results, based on historical pricing and
transaction volume data, are reported for 14 Canadian
companies listed on the Toronto stock exchange
market.
@article{Potvin:2004:COR,
abstract = {Technical analysis is aimed at devising trading rules
capable of exploiting short-term fluctuations on the
financial markets. Recent results indicate that this
market timing approach may be a viable alternative to
the buy-and-hold approach, where the assets are kept
over a relatively long time period. we propose genetic
programming as a means to automatically generate such
short-term trading rules on the stock markets. Rather
than using a composite stock index for this purpose,
the trading rules are adjusted to individual stocks.
Computational results, based on historical pricing and
transaction volume data, are reported for 14 Canadian
companies listed on the Toronto stock exchange
market.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Potvin, Jean-Yves and Soriano, Patrick and Vallee, Maxime},
biburl = {https://www.bibsonomy.org/bibtex/2e0abb53a8ee80d64510c4bf63b98e911/brazovayeye},
interhash = {207c5afe803e32a348d7dccccf828bae},
intrahash = {e0abb53a8ee80d64510c4bf63b98e911},
journal = {Computers \& Operations Research},
keywords = {algorithms, genetic programming},
number = 7,
owner = {wlangdon},
pages = {1033--1047},
timestamp = {2008-06-19T17:49:52.000+0200},
title = {Generating trading rules on the stock markets with
genetic programming},
url = {http://www.sciencedirect.com/science/article/B6VC5-48GVPS3-1/2/a068a76df94cb8449f6ef7782615fc87},
volume = 31,
year = 2004
}