We model international short-term capital flow by
identifying technical trading rules in short-term
capital markets using Genetic Programming (GP). The
simulation results suggest that the international
short-term markets was quite efficient during the
period of 1997-2002, with most GP generated trading
strategies recommending buy-and-hold on one or two
assets. The out-of-sample performance of GP trading
strategies varies from year to year. However, many of
the strategies are able to forecast Taiwan stock market
down time and avoid making futile investment.
Investigation of Automatically Defined Functions shows
that they do not give advantages or disadvantages to
the GP results.
%0 Book Section
%1 TinaYu:2004:
%A Yu, Tina
%A Chen, Shu-Heng
%A Kuo, Tzu-Wen
%B Applications of Artificial Intelligence in Finance and
Economics
%D 2004
%E Binner, Jane M.
%E Kendall, Graham
%E Chen, Shu-Heng
%I Jai Pr
%K ADF algorithms, genetic programming,
%P 45--70
%R doi:10.1016/S0731-9053(04)19002-6
%T A Genetic Programming approach to Model International
Short-term Capital Flow
%U http://www.sciencedirect.com/science/article/B75F0-4DW2XG4-5/2/091cf27244b360ecf18b04ca79a1d1ad
%V 19
%X We model international short-term capital flow by
identifying technical trading rules in short-term
capital markets using Genetic Programming (GP). The
simulation results suggest that the international
short-term markets was quite efficient during the
period of 1997-2002, with most GP generated trading
strategies recommending buy-and-hold on one or two
assets. The out-of-sample performance of GP trading
strategies varies from year to year. However, many of
the strategies are able to forecast Taiwan stock market
down time and avoid making futile investment.
Investigation of Automatically Defined Functions shows
that they do not give advantages or disadvantages to
the GP results.
%& 2
%@ 0-7623-1150-9
@incollection{TinaYu:2004:,
abstract = {We model international short-term capital flow by
identifying technical trading rules in short-term
capital markets using Genetic Programming (GP). The
simulation results suggest that the international
short-term markets was quite efficient during the
period of 1997-2002, with most GP generated trading
strategies recommending buy-and-hold on one or two
assets. The out-of-sample performance of GP trading
strategies varies from year to year. However, many of
the strategies are able to forecast Taiwan stock market
down time and avoid making futile investment.
Investigation of Automatically Defined Functions shows
that they do not give advantages or disadvantages to
the GP results.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Yu, Tina and Chen, Shu-Heng and Kuo, Tzu-Wen},
biburl = {https://www.bibsonomy.org/bibtex/275daae9b270d6776afe0198549be9933/brazovayeye},
booktitle = {Applications of Artificial Intelligence in Finance and
Economics},
chapter = 2,
doi = {doi:10.1016/S0731-9053(04)19002-6},
editor = {Binner, Jane M. and Kendall, Graham and Chen, Shu-Heng},
interhash = {a60d1884a7f5eecbd787ce127dbc4444},
intrahash = {75daae9b270d6776afe0198549be9933},
isbn = {0-7623-1150-9},
keywords = {ADF algorithms, genetic programming,},
notes = {may be available via Elsevier?},
pages = {45--70},
publisher = {Jai Pr},
series = {Advances in Econometrics},
timestamp = {2008-06-19T17:55:04.000+0200},
title = {A Genetic Programming approach to Model International
Short-term Capital Flow},
url = {http://www.sciencedirect.com/science/article/B75F0-4DW2XG4-5/2/091cf27244b360ecf18b04ca79a1d1ad},
volume = 19,
year = 2004
}