DocumentCode :
2570389
Title :
A new method for forecasting the TAIEX based on high-order fuzzy logical relationships
Author :
Chen, Chao-Dian ; Chen, Shyi-Ming
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
3456
Lastpage :
3460
Abstract :
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.
Keywords :
fuzzy set theory; stock markets; TAIEX; Taiwan stock exchange capitalization weighted stock index; adjacent fuzzy sets; high-order fuzzy logical relationships; Chaos; Computer science; Cybernetics; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Stock markets; Technology forecasting; USA Councils; fuzzy forecasting; fuzzy sets; fuzzy time series; high-order fuzzy logical relationships; high-order fuzzy time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5346231
Filename :
5346231
Link To Document :
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