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
相关论文
共 50 条
  • [21] DEHypGpOls: a genetic programming with evolutionary hyperparameter optimization and its application for stock market trend prediction
    Davut Ari
    Baris Baykant Alagoz
    Soft Computing, 2023, 27 : 2553 - 2574
  • [22] An integrated framework of genetic network programming and multi-layer perceptron neural network for prediction of daily stock return: An application in Tehran stock exchange market
    Ramezanian, Reza
    Peymanfar, Arsalan
    Ebrahimi, Seyed Babak
    APPLIED SOFT COMPUTING, 2019, 82
  • [23] Genetic Programming Applied to Programmable Logic Controllers Programming
    Carneiro, M. L.
    Brito, L. da C.
    Araujo, S. G.
    Machado, P. C. M.
    Carvalho, P. H. P.
    IEEE LATIN AMERICA TRANSACTIONS, 2011, 9 (03) : 270 - 279
  • [24] Stock market prediction using Multi Expression Programming
    Grosan, Crina
    Abraham, Ajith
    Ramos, Vitorino
    Han, Sang Yong
    2005 PORTUGUESE CONFERENCE ON ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2005, : 73 - 78
  • [25] Genetic programming applied to automatic algorithm design in multi-scale inspection systems
    Burla, Avinash
    Haist, Tobias
    Lyda, Wolfram
    Osten, Wolfgang
    OPTICAL ENGINEERING, 2012, 51 (06)
  • [26] Co-evolved genetic programs for stock market trading
    Nicholls, Jason F.
    Engelbrech, Andries P.
    INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT, 2019, 26 (03) : 117 - 136
  • [27] Genetic programming algorithm based on cluster tournament and parent matching
    Fang W.
    Liang J.
    Lu H.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2023, 45 (08): : 2405 - 2414
  • [28] Improved Genetic Programming Algorithm
    Cheng, Huifang
    Zhang, Yongqiang
    Li, Fangping
    2009 INTERNATIONAL ASIA SYMPOSIUM ON INTELLIGENT INTERACTION AND AFFECTIVE COMPUTING, 2009, : 168 - +
  • [29] Application of genetic programming coupling with genetic algorithm
    Zhou, XD
    Li, TH
    Bian, F
    Quian, JL
    CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE, 2000, 21 (02): : 216 - 218
  • [30] A Genetic Programming-based Algorithm for Composing Web Services
    Mucientes, Manuel
    Lama, Manuel
    Couto, Miguel I.
    2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, 2009, : 379 - 384
12345