DocumentCode
2303103
Title
Notice of Retraction
A Modified Model of Fuzzy Time Series for Forecasting Exchange Rates
Author
Kai Chi ; Fang-Ping Fu ; Wen-Gang Che
Author_Institution
Sch. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Volume
3
fYear
2010
fDate
6-7 March 2010
Firstpage
40
Lastpage
43
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Financial forecasting has become an important and challenging task for both researchers and investors. In order to improve the forecasting accuracy rate, in this paper, a modified heuristic model of fuzzy time series using FCM is proposed. Using the daily prices of USD/JPY and USD/CHY exchange rates as testing data, the empirical results show that the proposed method is able to get better forecasting results and higher accuracy than those of traditional econometric methods and some existing models of fuzzy time series.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Financial forecasting has become an important and challenging task for both researchers and investors. In order to improve the forecasting accuracy rate, in this paper, a modified heuristic model of fuzzy time series using FCM is proposed. Using the daily prices of USD/JPY and USD/CHY exchange rates as testing data, the empirical results show that the proposed method is able to get better forecasting results and higher accuracy than those of traditional econometric methods and some existing models of fuzzy time series.
Keywords
exchange rates; fuzzy logic; fuzzy set theory; pattern clustering; time series; FCM; USD-CHY exchange rate; USD-JPY exchange rate; exchange rates forecast; forecasting accuracy rate; fuzzy c-means clustering algorithm; fuzzy time series; modified heuristic model; testing data; Autoregressive processes; Computer science education; Econometrics; Economic forecasting; Educational technology; Exchange rates; Fuzzy logic; Fuzzy sets; Predictive models; Technology forecasting; exchange rate; forecasting; fuzzy c-means clustering; fuzzy time series; heuristic model;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.120
Filename
5460027
Link To Document