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

Using Data Mining to Study Upstream and Downstream Causal Relationship in Stock Market

Authors
Don-Lin Yang 0, Y.L. Hsieh, Jungpin Wu
Corresponding Author
Don-Lin Yang
0Feng Chia University
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.191How to use a DOI?
Keywords
Stock, Inter-Transaction Data Mining
Abstract
To understand the causal relationship of stock market is always a top priority for investors. Most investors use some fundamental knowledge and basic analysis techniques to analyze or predict the trends. However, there are always some other factors beyond our control or unexpected events that might affect the stock market one way or the other. After working on data mining with good results, we found inter-transaction mining can help answer the above questions in a systemic way. Our experiments show that causal relationship between upstream and downstream stocks do exist. To simplify our discussion, we focus on the electrical industrial stocks.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.191How 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  - Don-Lin Yang
AU  - Y.L. Hsieh
AU  - Jungpin Wu
PY  - 2006/10
DA  - 2006/10
TI  - Using Data Mining to Study Upstream and Downstream Causal Relationship in Stock Market
PB  - Atlantis Press
SP  - 528
EP  - 531
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.191
DO  - https://doi.org/10.2991/jcis.2006.191
ID  - Yang2006/10
ER  -