Evolutionary Dynamic Data Investment Evaluator (EDDIE)
is a genetic programming (GP)-based decision support
tool for financial forecasting. EDDIE itself does not
replace forecasting experts. It serves to improve the
productivity of experts in searching the space of
decision trees, with the aim to improve the odds in its
user's favour. The efficacy of EDDIE has been reported
in the literature. However, discovering patterns in
historical data is only the first step towards building
a practical financial forecasting tool. Data
preparation, rules organisation and application are all
important issues. This paper describes an architecture
that embeds EDDIE for learning from and monitoring the
stock market.
%0 Journal Article
%1 Tsang:2004:DSS
%A Tsang, Edward
%A Yung, Paul
%A Li, Jin
%D 2004
%J Decision Support Systems
%K algorithms, genetic programming
%N 4
%P 559--565
%T EDDIE-Automation, a decision support tool for
financial forecasting
%U http://www.sciencedirect.com/science/article/B6V8S-4903GV9-1/2/d6ba531a46ce45526ff9015e4447409a
%V 37
%X Evolutionary Dynamic Data Investment Evaluator (EDDIE)
is a genetic programming (GP)-based decision support
tool for financial forecasting. EDDIE itself does not
replace forecasting experts. It serves to improve the
productivity of experts in searching the space of
decision trees, with the aim to improve the odds in its
user's favour. The efficacy of EDDIE has been reported
in the literature. However, discovering patterns in
historical data is only the first step towards building
a practical financial forecasting tool. Data
preparation, rules organisation and application are all
important issues. This paper describes an architecture
that embeds EDDIE for learning from and monitoring the
stock market.
@article{Tsang:2004:DSS,
abstract = {Evolutionary Dynamic Data Investment Evaluator (EDDIE)
is a genetic programming (GP)-based decision support
tool for financial forecasting. EDDIE itself does not
replace forecasting experts. It serves to improve the
productivity of experts in searching the space of
decision trees, with the aim to improve the odds in its
user's favour. The efficacy of EDDIE has been reported
in the literature. However, discovering patterns in
historical data is only the first step towards building
a practical financial forecasting tool. Data
preparation, rules organisation and application are all
important issues. This paper describes an architecture
that embeds EDDIE for learning from and monitoring the
stock market.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Tsang, Edward and Yung, Paul and Li, Jin},
biburl = {https://www.bibsonomy.org/bibtex/23b1ce66f7bc209519bd41c691819b6eb/brazovayeye},
interhash = {753dffa9fe329b8cfd5ffa70704497bd},
intrahash = {3b1ce66f7bc209519bd41c691819b6eb},
journal = {Decision Support Systems},
keywords = {algorithms, genetic programming},
notes = {Special Issue on Data Mining for Financial Decision
Making},
number = 4,
owner = {wlangdon},
pages = {559--565},
timestamp = {2008-06-19T17:53:20.000+0200},
title = {{EDDIE}-Automation, a decision support tool for
financial forecasting},
url = {http://www.sciencedirect.com/science/article/B6V8S-4903GV9-1/2/d6ba531a46ce45526ff9015e4447409a},
volume = 37,
year = 2004
}