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A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting

journal contribution
posted on 17.06.2019 by Bangzhu Zhu, Shunxin Ye, Ping Wang, Kaijian He, Tao Zhang, Yi-Ming Wei
In this study, a novel multiscale nonlinear ensemble leaning paradigm incorporating empirical mode decomposition (EMD) and least square support vector machine (LSSVM) with kernel function prototype is proposed for carbon price forecasting. The EMD algorithm is used to decompose the carbon price into simple intrinsic mode functions (IMFs) and one residue, which are identified as the components of high frequency, low frequency and trend by using the Lempel-Ziv complexity algorithm. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to forecast the high frequency IMFs with ARCH effects. The LSSVM model with kernel function prototype is employed to forecast the high frequency IMFs without ARCH effects, the low frequency and trend components. The forecasting values of all the components are aggregated into the ones of original carbon price by the LSSVM with kernel function prototype-based nonlinear ensemble approach. Furthermore, particle swarm optimization is used for model selections of the LSSVM with kernel function prototype. Taking the popular prediction methods as benchmarks, the empirical analysis demonstrates that the proposed model can achieve higher level and directional predictions and higher robustness. The findings show that the proposed model seems an advanced approach for predicting the high nonstationary, nonlinear and irregular carbon price.

Funding

National Natural Science Foundation of China (71771105, 71473180, and 71303174), National Philosophy and Social Science Foundation of China (15ZDA054 and 16ZZD049), Guangdong Young Zhujiang Scholar (Yue Jiaoshi [2016]95), Natural Science Foundation for Distinguished Young Talents of Guangdong (2014A030306031), Guangdong Key Base of Humanities and Social Science—Enterprise Development Research Institute, Institute of Resource, Environment and Sustainable Development Research, and Guangzhou key Base of Humanities and Social Science—Centre for Low Carbon Economic Research.

History

School

  • Loughborough University London

Published in

Energy Economics

Volume

70

Pages

143 - 157

Citation

ZHU, B. ... et al, 2018. A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting. Energy Economics, 70, pp.143-157.

Publisher

© Elsevier

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

28/12/2017

Publication date

2018-01-06

Notes

This paper is closed access.

ISSN

0140-9883

Language

en

Exports