%0 Journal Article %1 tsang:1998:eddie %A Tsang, Edward P. K. %A Li, Jin %A Butler, James M. %D 1998 %J Software: Practice and Experience %K algorithms, finance, forecasting, genetic horse investment programming, racing, %N 10 %P 1033--1043 %R doi:10.1002/(SICI)1097-024X(199808)28:10<1033::AID-SPE198>3.0.CO;2-1 %T EDDIE beats the bookies %U http://www3.interscience.wiley.com/cgi-bin/abstract/10007354/START %V 28 %X Investment involves the maximisation of return on ones investment whilst minimising risk. Good forecasting, which often requires expert knowledge, can help to reduce risk. In this paper, we propose a genetic programming-based system, EDDIE (Evolutionary Dynamic Data Investment Evaluator), as a forecasting tool. Genetic programming is inspired by evolution theory, and has been demonstrated to be successful in other areas. EDDIE interacts with the users and generates decision trees, which can also be seen as rule sets. We argue that EDDIE is suitable for forecasting because apart from using the power of genetic programming to efficiently search the space of decision trees, it allows expert knowledge to be channelled into forecasting, and it generates rules which can easily be understood and verified. EDDIE has been applied to horse racing and achieved outstanding results. When experimented on 180 handicap races (real data) in the UK, it out-performed other common strategies used in horse race betting by great margins. The idea was then extended to financial forecasting. When tested on historical S&P-500 data EDDIE achieved a respectable annual rate of return over a three and a half year period. While luck may play a part in the success of EDDIE, our experimental results do indicate that EDDIE is a tool which deserves more research. c 1998 John Wiley & Sons, Ltd.

@article{tsang:1998:eddie, abstract = {Investment involves the maximisation of return on ones investment whilst minimising risk. Good forecasting, which often requires expert knowledge, can help to reduce risk. In this paper, we propose a genetic programming-based system, EDDIE (Evolutionary Dynamic Data Investment Evaluator), as a forecasting tool. Genetic programming is inspired by evolution theory, and has been demonstrated to be successful in other areas. EDDIE interacts with the users and generates decision trees, which can also be seen as rule sets. We argue that EDDIE is suitable for forecasting because apart from using the power of genetic programming to efficiently search the space of decision trees, it allows expert knowledge to be channelled into forecasting, and it generates rules which can easily be understood and verified. EDDIE has been applied to horse racing and achieved outstanding results. When experimented on 180 handicap races (real data) in the UK, it out-performed other common strategies used in horse race betting by great margins. The idea was then extended to financial forecasting. When tested on historical S&P-500 data EDDIE achieved a respectable annual rate of return over a three and a half year period. While luck may play a part in the success of EDDIE, our experimental results do indicate that EDDIE is a tool which deserves more research. c 1998 John Wiley & Sons, Ltd.}, added-at = {2008-06-19T17:46:40.000+0200}, author = {Tsang, Edward P. K. and Li, Jin and Butler, James M.}, biburl = {https://www.bibsonomy.org/bibtex/211934e79f1168da4ed289cb04b714a35/brazovayeye}, doi = {doi:10.1002/(SICI)1097-024X(199808)28:10<1033::AID-SPE198>3.0.CO;2-1}, interhash = {3e0cc6cbd182d64c5c63104c452d6c8f}, intrahash = {11934e79f1168da4ed289cb04b714a35}, issn = {0038-0644}, journal = {Software: Practice and Experience}, keywords = {algorithms, finance, forecasting, genetic horse investment programming, racing,}, notes = {See also \cite{butler:1995:eddie}}, number = 10, pages = {1033--1043}, size = {15 pages}, timestamp = {2008-06-19T17:53:19.000+0200}, title = {{EDDIE} beats the bookies}, url = {http://www3.interscience.wiley.com/cgi-bin/abstract/10007354/START}, volume = 28, year = 1998 }