TY - GEN
T1 - Multi scale nonlinear ensemble model for foreign exchange rate prediction
AU - Kaijian, He
AU - Chi, Xie
AU - Kin, Keung Lai
PY - 2008
Y1 - 2008
N2 - This paper proposes a novel multi scale nonlinear ensemble methodology for analyzing and modeling the complex exchange rate behaviors. Using several techniques integrated under the proposed unified framework, it deals with data characteristics such as autocorrelation, multi scale heterogeneity and parameter instability during the modeling process. The multi scale heterogeneity property is modeled using wavelet analysis while autocorrelation property is modeled under ARMA framework. Combining independent component analysis, the proposed approach improves the model specification stability using support vector regression based nonlinear ensemble framework. Euro market is chosen as the test case for the performance evaluation of the proposed approach. Empirical studies results suggest that the proposed approach improves the forecasting accuracy and stability. It also offers valuable information as to the underlying micro market structure. © 2008 IEEE.
AB - This paper proposes a novel multi scale nonlinear ensemble methodology for analyzing and modeling the complex exchange rate behaviors. Using several techniques integrated under the proposed unified framework, it deals with data characteristics such as autocorrelation, multi scale heterogeneity and parameter instability during the modeling process. The multi scale heterogeneity property is modeled using wavelet analysis while autocorrelation property is modeled under ARMA framework. Combining independent component analysis, the proposed approach improves the model specification stability using support vector regression based nonlinear ensemble framework. Euro market is chosen as the test case for the performance evaluation of the proposed approach. Empirical studies results suggest that the proposed approach improves the forecasting accuracy and stability. It also offers valuable information as to the underlying micro market structure. © 2008 IEEE.
KW - Independent component analysis
KW - Nonlinear ensemble
KW - Support vector regression
KW - Wavelet analysis
UR - http://www.scopus.com/inward/record.url?scp=57649181782&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-57649181782&origin=recordpage
U2 - 10.1109/ICNC.2008.525
DO - 10.1109/ICNC.2008.525
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9780769533049
VL - 7
SP - 43
EP - 47
BT - Proceedings - 4th International Conference on Natural Computation, ICNC 2008
T2 - 4th International Conference on Natural Computation, ICNC 2008
Y2 - 18 October 2008 through 20 October 2008
ER -