DocumentCode
2655050
Title
Notice of Retraction
Nonlinear Autoregressive model with eXogenous input for exchange rate forecasting
Author
Chuanjin Jiang ; Jing Zhang
Author_Institution
Shanghai Bus. Sch., Donghua Univ., Shanghai, China
Volume
4
fYear
2010
fDate
16-18 April 2010
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.
The exchange-rate time series is a dynamic non-linear system, whose characteristics cannot be reflected by neither the linear regression model nor the static neutral network. The Nonlinear Autoregressive with eXogenous input (NARX) includes the feedback of the network output, therefore can reflect the dynamic property of the system. This paper analyzed the chaotic property of the exchange-rate time series, calculated the embedding dimension of the series, and established the exchange-rate forecast model using the NARX network. The result shows that the NARX network has better short-term and mid-term forecast effect, comparing to the BP network and the ARIMA model.
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.
The exchange-rate time series is a dynamic non-linear system, whose characteristics cannot be reflected by neither the linear regression model nor the static neutral network. The Nonlinear Autoregressive with eXogenous input (NARX) includes the feedback of the network output, therefore can reflect the dynamic property of the system. This paper analyzed the chaotic property of the exchange-rate time series, calculated the embedding dimension of the series, and established the exchange-rate forecast model using the NARX network. The result shows that the NARX network has better short-term and mid-term forecast effect, comparing to the BP network and the ARIMA model.
Keywords
autoregressive processes; feedback; nonlinear control systems; time series; ARIMA model; BP network; NARX network; dynamic nonlinear system; exchange rate forecast model; exchange-rate time series; network output feedback; nonlinear autoregressive with exogenous input; Chaos; Economic forecasting; Exchange rates; Linear regression; Mathematical model; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Predictive models; Time series analysis; NARX; Nonlinear autoregressive model; exchange rate; mid-term forecast;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5485726
Filename
5485726
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