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

Stock Data Mining through Fuzzy Genetic Algorithms

Authors
Longbing Cao 0, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang
Corresponding Author
Longbing Cao
0Faculty of Information Technology
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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.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Publication Date
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ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.129How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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