Stock Data Mining through Fuzzy Genetic Algorithms
- Longbing Cao 0, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang
- Corresponding Author
- Longbing Cao
0Faculty of Information Technology
Available Online October 2006.
- https://doi.org/10.2991/jcis.2006.129How to use a DOI?
- stock data mining, fuzzy genetic algorithm
- 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.
- 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 - 2006/10 DA - 2006/10 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 - Cao2006/10 ER -