GoldMiner: A Genetic Programming based algorithm applied to Brazilian Stock Market

被引：0
|
作者：
Pimenta, Alexandre [1 ,2 ]
Guimaraes, Frederico Gadelha [3 ]
Carrano, Eduardo G. [3 ]
Leite Nametala, Ciniro Aparecido [4 ]
Takahashi, Ricardo H. C. [5 ]
机构：
[1] Univ Fed Minas Gerais, PPGEE, Belo Horizonte, MG, Brazil
[2] Inst Fed Minas Gerais, Dept Comp, Formiga, MG, Brazil
[3] Univ Fed Minas Gerais, Dept Elect Engn, Belo Horizonte, MG, Brazil
[4] Inst Fed Minas Gerais, Dept Engn & Comp, Bambui, MG, Brazil
[5] Univ Fed Minas Gerais, Dept Math, Belo Horizonte, MG, Brazil
来源：
2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM) | 2014年
关键词：
genetic programming; technical analysis; exchange market; decision making;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The possibility of obtaining financial gain by investing in the Stock Markets is a hard task since it is under constant influence of economical, political and social factors. This paper aims to address the financial technical analysis of Stock Markets, focusing on time series data instead of subjective parameters. An algorithm based on genetic programming, named GoldMiner, has been proposed to perform retrospective study in order to get predictions about the best time for trading top stocks on the BOVESPA, the Brazilian stock exchange market.
引用
收藏
页码：397 / 402
页数：6
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