High order fuzzy time series for exchange rates forecasting

Fuzzy time series model has been employed by many researchers in various forecasting activities such as university enrolment, temperature, direct tax collection and the most popular stock price forecasting. However exchange rate forecasting especially using high order fuzzy time series has been give...

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Bibliographic Details
Main Authors: Abdullah, L., Taib, I.
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
exchange rate
Exchange rates
Forecasting
fuzzy set
Fuzzy sets
Pragmatics
Predictive models
square error
time series
Time series analysis
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Summary:Fuzzy time series model has been employed by many researchers in various forecasting activities such as university enrolment, temperature, direct tax collection and the most popular stock price forecasting. However exchange rate forecasting especially using high order fuzzy time series has been given less attention despite its huge contribution in business transactions. The paper aims to test the forecasting of US dollar (USD) against Malaysian Ringgit (MYR) exchange rates using high order fuzzy time series and check its accuracy. Twenty five data set of the exchange rates USD against MYR was tested to the seven-step of high fuzzy time series. The results show that higher order fuzzy time series yield very small errors thereby the model does produce a good forecasting tool for the exchange rates.
ISSN:2155-6938
2155-6946
DOI:10.1109/DMO.2011.5976496