Regularizing BWGC/NGARCH Model by Quantum Minimization

Authors:
Bao Rong Chang;Hsiu Fen Tsai;Shi Huang Chen;Yu Chang Chen;Yu-Kuo Tseng
Affiliations:
National Taitung University, Taiwan;Sue-Te University, Taiwan;Sue-Te University, Taiwan;Sue-Te University, Taiwan;Sue-Te University, Taiwan
Venue:
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2
Year:
2006

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Abstract

A hybrid BPNN-weighted GREY-C3LSP prediction (BWGC) is used for resolving the overshooting phenomenon significantly; however, it may lose the localization once volatility clustering occurs. Thus, we propose a compensation to deal with the time-varying variance in the residual errors, that is, incorporating a non-linear generalized autoregressive conditional heteroscedasticity (NGARCH) into BWGC, and quantum minimization is employed to regularize the smoothing coefficients for both BWGC and NGARCH to effectively improve model's robustness as well as to highly balance the generalization and the localization.