Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price

Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price

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 chara...

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Bibliographic Details
Main Authors: Kaijian He, Rui Zha, Jun Wu, Kin Keung Lai
Format: Article
Language:English
Published: MDPI AG 2016-04-01
Series:Sustainability
Subjects:
empirical mode decomposition (EMD)
multivariate EMD analysis
crude oil price forecasting
time delay embedding
multiscale analysis
ARMA model
Online Access:http://www.mdpi.com/2071-1050/8/4/387
Description
Summary: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.
ISSN:2071-1050

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