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Finding the multipath propagation of multivariable crude oil prices using a wavelet-based network approach

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  • Jia, Xiaoliang
  • An, Haizhong
  • Sun, Xiaoqi
  • Huang, Xuan
  • Gao, Xiangyun

Abstract

The globalization and regionalization of crude oil trade inevitably give rise to the difference of crude oil prices. The understanding of the pattern of the crude oil prices’ mutual propagation is essential for analyzing the development of global oil trade. Previous research has focused mainly on the fuzzy long- or short-term one-to-one propagation of bivariate oil prices, generally ignoring various patterns of periodical multivariate propagation. This study presents a wavelet-based network approach to help uncover the multipath propagation of multivariable crude oil prices in a joint time–frequency period. The weekly oil spot prices of the OPEC member states from June 1999 to March 2011 are adopted as the sample data. First, we used wavelet analysis to find different subseries based on an optimal decomposing scale to describe the periodical feature of the original oil price time series. Second, a complex network model was constructed based on an optimal threshold selection to describe the structural feature of multivariable oil prices. Third, Bayesian network analysis (BNA) was conducted to find the probability causal relationship based on periodical structural features to describe the various patterns of periodical multivariable propagation. Finally, the significance of the leading and intermediary oil prices is discussed. These findings are beneficial for the implementation of periodical target-oriented pricing policies and investment strategies.

Suggested Citation

  • Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Gao, Xiangyun, 2016. "Finding the multipath propagation of multivariable crude oil prices using a wavelet-based network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 331-344.
    • Handle: RePEc:eee:phsmap:v:447:y:2016:i:c:p:331-344
    DOI: 10.1016/j.physa.2015.12.064
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    1. An, Haizhong & Gao, Xiangyun & Fang, Wei & Huang, Xuan & Ding, Yinghui, 2014. "The role of fluctuating modes of autocorrelation in crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 382-390.
    2. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    3. Lin, Sue J. & Lu, I.J. & Lewis, Charles, 2007. "Grey relation performance correlations among economics, energy use and carbon dioxide emission in Taiwan," Energy Policy, Elsevier, vol. 35(3), pages 1948-1955, March.
    4. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
    5. Bhar, Ramaprasad & Hammoudeh, Shawkat & Thompson, Mark A., 2008. "Component structure for nonstationary time series: Application to benchmark oil prices," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 971-983, December.
    6. Reboredo, Juan C. & Rivera-Castro, Miguel A., 2014. "Wavelet-based evidence of the impact of oil prices on stock returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 145-176.
    7. Silvo Dajčman, 2013. "Interdependence Between Some Major European Stock Markets - A Wavelet Lead/Lag Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2013(1), pages 28-49.
    8. Aquaro, V. & Bardoscia, M. & Bellotti, R. & Consiglio, A. & De Carlo, F. & Ferri, G., 2010. "A Bayesian Networks approach to Operational Risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1721-1728.
    9. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
    10. Fattouh, Bassam, 2010. "The dynamics of crude oil price differentials," Energy Economics, Elsevier, vol. 32(2), pages 334-342, March.
    11. An, Haizhong & Zhong, Weiqiong & Chen, Yurong & Li, Huajiao & Gao, Xiangyun, 2014. "Features and evolution of international crude oil trade relationships: A trading-based network analysis," Energy, Elsevier, vol. 74(C), pages 254-259.
    12. Weiner, R.J., 1991. "Is the World Oil Market "One Great Pool?"," Papers 9120, Laval - Recherche en Energie.
    13. Robert J. Weiner, 1991. "Is the World Oil Market "One Great Pool"?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 95-108.
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    6. Das, Debojyoti & Bhowmik, Puja & Jana, R.K., 2018. "A multiscale analysis of stock return co-movements and spillovers: Evidence from Pacific developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 379-393.
    7. Liu, Shuyu & Huang, Shupei & Chi, Yuxi & Feng, Sida & Li, Yang & Sun, Qingru, 2020. "Three-level network analysis of the North American natural gas price: A multiscale perspective," International Review of Financial Analysis, Elsevier, vol. 67(C).
    8. Li, Xiuming & Sun, Mei & Gao, Cuixia & He, Huizi, 2019. "The spillover effects between natural gas and crude oil markets: The correlation network analysis based on multi-scale approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 306-324.
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