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Sustainability 2016, 8(6), 534; doi:10.3390/su8060534

The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock

1,2,3,4
,
1,2,3,* , 1,2,3
and
1,2,3
1
School of Humanities and Economic Management, China University of Geosciences, Beijing, China
2
Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources, Beijing 100083, China
3
Open Lab of Talents Evaluation, Ministry of Land and Resources, Beijing 100083, China
4
Department of Science and Technology, Parthenope University of Naples, Centro Direzionale-Isola C4, Napoli 80143, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Lin Lu
Received: 27 November 2015 / Revised: 26 April 2016 / Accepted: 26 May 2016 / Published: 4 June 2016
(This article belongs to the Special Issue Renewable Energy Applications and Energy Saving in Buildings)
View Full-Text   |   Download PDF [2856 KB, uploaded 4 June 2016]   |  

Abstract

Wind energy is considered a clear and sustainable substitution for fossil fuel, and the stock index of the wind energy industry is closely related to the oil price fluctuation. Their relationship is characterized by multiscale and time-varying features based on a variety of stakeholders who have different objectives within various time horizons, which makes it difficult to identify the factor in which time scale could be the most influential one in the market. Aiming to explore the correlation between oil price and the wind energy stock index from the time–frequency domain in a dynamic perspective, we propose an algorithm combining the wavelet transform, complex network, and gray correlation analyses and choose the Brent oil price and the international securities exchange (ISE) global wind energy index from January 2006 to October 2015 in daily frequency as data sample. First, we define the multiscale conformation by a set of fluctuation information with different time horizons to represent the fluctuation status of the correlation of the oil–wind nexus rather than by a single original correlation value. Then, we transform the multiscale conformation evolution into a network model, and only 270 multiscale conformations and 710 transmissions could characterize 2451 data points. We find that only 30% of conformations and transmissions work as a backbone of the entire correlation series; through these major conformations, we identify that the main factor that could influence the oil–wind nexus are long-term components, such as policies, the status of the global economy and demand–supply issues. In addition, there is a clustering effect and transmissions among conformations that mainly happen inside clusters and rarely among clusters, which means the interaction of the oil–wind nexus is stable over a short period of time. View Full-Text
Keywords: wind energy; oil price; multiscale; complex network wind energy; oil price; multiscale; complex network
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Huang, S.; An, H.; Gao, X.; Jiang, M. The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock. Sustainability 2016, 8, 534.

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