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Forecasting interval carbon price through a multi-scale interval-valued decomposition ensemble approach

Author

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  • Yang, Kun
  • Sun, Yuying
  • Hong, Yongmiao
  • Wang, Shouyang

Abstract

This paper proposes a novel Multi-scale Interval-valued Decomposition Ensemble (MIDE) framework for forecasting European Union Allowance (EUA) carbon futures prices, which integrates Noise-assisted Multivariate Empirical Mode Decomposition (NAMEMD), Interval-valued Vector Auto-Regressive (IVAR) model, Interval Event Analysis (IEA) method, and Interval Multi-Layer Perceptron (IMLP). First, the original interval-valued carbon prices with other interval-valued control variables are decomposed and integrated into high, medium, and low-frequency components by NAMEMD. Second, IVAR is used to investigate the dynamics of the interval-valued vector system in low-frequency components, while IMLP is employed to characterize the high-frequency components. Besides, the interval event analysis investigates typical events that significantly impact carbon prices in the medium-frequency component. Furthermore, empirical findings indicate that our proposed MIDE learning approach significantly outperforms some other benchmark models in out-of-sample forecasting.

Suggested Citation

  • Yang, Kun & Sun, Yuying & Hong, Yongmiao & Wang, Shouyang, 2024. "Forecasting interval carbon price through a multi-scale interval-valued decomposition ensemble approach," Energy Economics, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:eneeco:v:139:y:2024:i:c:s0140988324006601
    DOI: 10.1016/j.eneco.2024.107952
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    More about this item

    Keywords

    Interval carbon price; Decomposed; Event analysis; Machine learning; Forecasting;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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