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