JACIII Vol.15 No.4 pp. 449-453
doi: 10.20965/jaciii.2011.p0449


Rough Sets Based Prediction Model of Tick-Wise Price Fluctuations

Yoshiyuki Matsumoto* and Junzo Watada**

*Department of Economics, Shimonoseki City University, 2-1-1 Daigaku-cho, Shimonoseki, Yamaguchi 751-8510, Japan

**Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka 808-0135, Japan

January 7, 2011
March 1, 2011
June 20, 2011
rough sets, tick-wise price, time-series data
Rough sets theory was proposed by Z. Pawlak in 1982. This theory enables us to mine knowledge granules through a decision rule from a database, a web base, a set and so on. We can apply the decision rule to reason, estimate, evaluate, or forecast unknown objects. In this paper, the rough set model is used to analyze of time series data of tick-wise price fluctuation, where knowledge granules are mined from the data set of tick-wise price fluctuations.
Cite this article as:
Y. Matsumoto and J. Watada, “Rough Sets Based Prediction Model of Tick-Wise Price Fluctuations,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.4, pp. 449-453, 2011.
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