4.6 Article

Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price

Journal

SUSTAINABILITY
Volume 8, Issue 4, Pages -

Publisher

MDPI AG
DOI: 10.3390/su8040387

Keywords

empirical mode decomposition (EMD); multivariate EMD analysis; crude oil price forecasting; time delay embedding; multiscale analysis; ARMA model

Funding

  1. National Natural Science Foundation of China (NSFC) [71201054, 91224001, 71433001]
  2. Strategic Research Grant of City University of Hong Kong [7004574]
  3. Fundamental Research Funds for the Central Universities in BUCT [buctrc201618]

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Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD)-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in benchmark crude oil markets confirm that more diverse heterogeneous data characteristics can be revealed and modeled in the projected time delayed domain. The proposed model demonstrates the superior performance compared to the benchmark models.

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