High Order Fuzzy Time Series for Exchange Rates Forecasting

被引：0

作者：

Abdullah, Lazim ^{[1
]}

Taib, Imran ^{[1
]}

机构：

[1] Univ Malaysia Terengganu, Dept Math, Fac Sci & Technol, Kuala Terengganu 21030, Malaysia

来源：

2011 3RD CONFERENCE ON DATA MINING AND OPTIMIZATION (DMO) | 2011年

关键词：

exchange rate; fuzzy set; time series; forecasting; square error; ENROLLMENTS; MODEL;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1 / 5

页数：5

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