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
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.
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