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A new method for forecasting the TAIEX based on high-order fuzzy logical relationships

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2 Author(s)
Chao-Dian Chen ; Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan ; Shyi-Ming Chen

In this paper, we present a new method to forecast the Taiwan stock exchange capitalization weighted stock index (TAIEX) based on high-order fuzzy logical relationships. First, the proposed method fuzzifies the historical data into fuzzy sets to form high-order fuzzy logical relationships. Then, it calculates the value of the variable between the subscripts of adjacent fuzzy sets appearing in the antecedents of high-order fuzzy logical relationships. Then, it lets the high-order fuzzy logical relationships having the same antecedent to form a high-order fuzzy logical relationship group. Finally, it chooses a high-order fuzzy logical relationship group to forecast the TAIEX. The proposed method gets a higher average forecasting accuracy rate than the existing methods to forecast the TAIEX.

Published in:

Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on

Date of Conference:

11-14 Oct. 2009