Frequency-Weighted Fuzzy Time-Series Based on Fibonacci Sequence for TAIEX Forecasting

摘要

This paper proposes a new fuzzy time-series model for promoting the stock price forecasting, which provides two refined approaches, a frequency-weighted method, and the concept of Fibonacci sequence in forecasting processes. In empirical analysis, two different types of financial datasets, TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index and HSI (Hong Kong Heng Seng Index) stock index are used as model verification. By comparing the forecasting results with those derived from Chen's, Yu's, and Hurang's models, the authors conclude that the research goal has been reached.