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

DOI

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.

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/).

Download article (PDF)

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
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SP  - 528
EP  - 531
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.191
DO  - 10.2991/jcis.2006.191
ID  - Yang2006/10
ER  -