title:
 
Stock Data Mining through Fuzzy Genetic Algorithms
publication:
 
JCIS-2006 Proceedings
part of series:
  Advances in Intelligent Systems Research
ISBN:
  978-90-78677-01-7
ISSN:
  1951-6851
DOI:
  doi:10.2991/jcis.2006.129 (how to use a DOI)
author(s):
 
Longbing Cao, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang
corresponding author:
 
Longbing Cao
publication date:
 
October 2006
keywords:
 
stock data mining, fuzzy genetic algorithm
abstract:
 
Stock data mining such as financial pairs mining is useful for trading supports and market surveillance. Financial pairs mining targets mining pair relationships between financial entities such as stocks and markets. This paper introduces a fuzzy genetic algorithm framework and strategies for discovering pair relationship in stock data such as in high dimensional trading data by considering user preference. The developed techniques have a potential to mine pairs between stocks, between stock-trading rules, and between markets. Experiments in real stock data show that the proposed approach is useful for mining pairs helpful for real trading decision-support and market surveillance.
copyright:
 
© The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
full text: