title: |
Using Data Mining to Study Upstream and Downstream Causal Relationship in Stock Market |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-01-7 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/jcis.2006.191 (how to use a DOI) | |
author(s): |
Don-Lin Yang, Y.L. Hsieh, Jungpin Wu |
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corresponding author: |
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publication date: |
October 2006 |
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keywords: |
Stock, Inter-Transaction Data Mining |
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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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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |