Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

Stock Data Mining through Fuzzy Genetic Algorithms

Authors
Longbing Cao1, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang
1Faculty of Information Technology
Corresponding Author
Longbing Cao
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.129How to use a DOI?
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
© 2006, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
Series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
10.2991/jcis.2006.129
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.129How to use a DOI?
Copyright
© 2006, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Longbing Cao
AU  - Chao Luo
AU  - Jiarui Ni
AU  - Dan Luo
AU  - Chengqi Zhang
PY  - 2006/10
DA  - 2006/10
TI  - Stock Data Mining through Fuzzy Genetic Algorithms
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.129
DO  - https://doi.org/10.2991/jcis.2006.129
ID  - Cao2006/10
ER  -