Systems, Man, and Cybernetics

 

Home

• [P423] A New Method to Forecast the TAIEX Based on Fuzzy Time Series
  Author(s): Shyi-Ming Chen, Chao-Dian Chen
  
  

  Abstract
  In this paper, we present a new method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy time series, where the main factor is the TAIEX and the secondary factors are either the Dow Jones, the NASDAQ, the M1b (Taiwan), or their combinations. First, we fuzzify the historical data of the main factor into fuzzy sets with a fixed length of intervals to form fuzzy logical relationships. Then, we group the fuzzy logical relationships into fuzzy logical relationship groups. Then, we evaluate the leverage of fuzzy variations between the main factor and the secondary factor to forecast the TAIEX. The experimental results show that the proposed method gets a higher average forecasting accuracy rate than Chen's method [1] and Huarng et al.'s method [9] to forecast the TAIEX.

  
   

Full Text (PDF)