1. You are Here：

Full metadata record
DC FieldValueLanguage
dc.contributor.authorTseng, FMen_US
dc.contributor.authorTzeng, GHen_US
dc.contributor.authorYu, HCen_US
dc.contributor.authorYuan, BJCen_US
dc.date.accessioned2014-12-08T15:44:11Z-
dc.date.available2014-12-08T15:44:11Z-
dc.date.issued2001-02-16en_US
dc.identifier.issn0165-0114en_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0165-0114(98)00286-3en_US
dc.identifier.urihttp://hdl.handle.net/11536/29839-
dc.description.abstractConsidering the time-series ARTMA (p,d,q) model and fuzzy regression model, this paper develops a fuzzy ARIMA (FARIMA) model and applies it to forecasting the exchange rate of NT dollars to US dollars. This model includes interval models with interval parameters and the possibility distribution of future values is provided by FARIMA. This model makes it possible for decision makers to forecast the best- and worst-possible situations based on fewer observations than the ARIMA model. (C) 2001 Elsevier Science B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectARIMAen_US
dc.subjectforeign exchange marketen_US
dc.subjectfuzzy regressionen_US
dc.subjectfuzzy ARIMAen_US
dc.subjecttime seriesen_US
dc.titleFuzzy ARIMA model for forecasting the foreign exchange marketen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0165-0114(98)00286-3en_US
dc.identifier.journalFUZZY SETS AND SYSTEMSen_US
dc.citation.volume118en_US
dc.citation.issue1en_US
dc.citation.spage9en_US
dc.citation.epage19en_US
dc.contributor.department管理學院zh_TW
dc.contributor.departmentCollege of Managementen_US
dc.identifier.wosnumberWOS:000166268000002-
dc.citation.woscount65-
Appears in Collections:Articles


Files in This Item:

  1. 000166268000002.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.

Related Contents
Loading...