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Price fluctuation in the energy stock market based on fluctuation and co-fluctuation matrix transmission networks

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  • Li, Huajiao
  • An, Haizhong
  • Liu, Xueyong
  • Gao, Xiangyun
  • Fang, Wei
  • An, Feng

Abstract

Few studies address fluctuation and co-fluctuation patterns in the short term or their roles and transmission pathways over the long term. Here, we used the 10-year daily price of the NASDAQ Top 10 listed energy companies to obtain daily returns of each energy stock. The daily fluctuation and co-fluctuation patterns, roles and relationships were studied based on the fluctuation transmission network (FTN) and co-fluctuation matrix transmission network (CMTN). We found that each energy stock has a different price fluctuation feature, and any two of them have obvious positive correlations; however, only four-ninths of them have spillover relations. For the FTN, we transformed each daily return into a symbol and combined the symbols into a fluctuation pattern; next, the fluctuation pattern was taken as a node and the pattern adjacent relations as edges to construct the network. For the CMTN, we transferred the daily return relations for any two energy stocks to the daily co-fluctuation matrices and then constructed the network based on the time adjacent relations. Then, we used and also defined some coefficients to analyze the roles of each fluctuation and co-fluctuation pattern and their relationships. This paper provides a novel method for researching fluctuations in energy financial market.

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  • Li, Huajiao & An, Haizhong & Liu, Xueyong & Gao, Xiangyun & Fang, Wei & An, Feng, 2016. "Price fluctuation in the energy stock market based on fluctuation and co-fluctuation matrix transmission networks," Energy, Elsevier, vol. 117(P1), pages 73-83.
  • Handle: RePEc:eee:energy:v:117:y:2016:i:p1:p:73-83
    DOI: 10.1016/j.energy.2016.10.054
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    References listed on IDEAS

    as
    1. Huajiao Li & Haizhong An & Xiangyun Gao & Wei Fang, 2015. "Characteristics of the co-fluctuation matrix transmission network based on financial multi-time series," Palgrave Communications, Palgrave Macmillan, vol. 1(palcomms2), pages 15023-15023, September.
    2. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    3. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2014. "Competition, transmission and pattern evolution: A network analysis of global oil trade," Energy Policy, Elsevier, vol. 73(C), pages 312-322.
    4. Sadorsky, Perry, 2012. "Modeling renewable energy company risk," Energy Policy, Elsevier, vol. 40(C), pages 39-48.
    5. Bouri, Elie, 2015. "Return and volatility linkages between oil prices and the Lebanese stock market in crisis periods," Energy, Elsevier, vol. 89(C), pages 365-371.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    8. He, Ling-Yun & Chen, Shu-Peng, 2011. "A new approach to quantify power-law cross-correlation and its application to commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3806-3814.
    9. He, Ling-Yun & Chen, Shu-Peng, 2011. "Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 297-308.
    10. 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.
    11. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2013. "An evaluation framework for oil import security based on the supply chain with a case study focused on China," Energy Economics, Elsevier, vol. 38(C), pages 87-95.
    12. Wu, Chih-Chiang & Chung, Huimin & Chang, Yu-Hsien, 2012. "The economic value of co-movement between oil price and exchange rate using copula-based GARCH models," Energy Economics, Elsevier, vol. 34(1), pages 270-282.
    13. He, Ling-Yun & Fan, Ying & Wei, Yi-Ming, 2009. "Impact of speculator's expectations of returns and time scales of investment on crude oil price behaviors," Energy Economics, Elsevier, vol. 31(1), pages 77-84, January.
    14. 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.
    15. Wen, Xiaoqian & Wei, Yu & Huang, Dengshi, 2012. "Measuring contagion between energy market and stock market during financial crisis: A copula approach," Energy Economics, Elsevier, vol. 34(5), pages 1435-1446.
    16. Gao, Xiangyun & An, Haizhong & Fang, Wei & Li, Huajiao & Sun, Xiaoqi, 2014. "The transmission of fluctuant patterns of the forex burden based on international crude oil prices," Energy, Elsevier, vol. 73(C), pages 380-386.
    17. Li, Huajiao & Fang, Wei & An, Haizhong & Yan, LiLi, 2014. "The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 525-532.
    18. Liming, Huang, 2009. "Financing rural renewable energy: A comparison between China and India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 1096-1103, June.
    19. Sun, Xiaoqi & An, Haizhong & Gao, Xiangyun & Jia, Xiaoliang & Liu, Xiaojia, 2016. "Indirect energy flow between industrial sectors in China: A complex network approach," Energy, Elsevier, vol. 94(C), pages 195-205.
    20. He, Ling-Yun & Chen, Shu-Peng, 2010. "Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3218-3229.
    21. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
    22. He, Ling-Yun & Chen, Shu-Peng, 2011. "Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets," Chaos, Solitons & Fractals, Elsevier, vol. 44(6), pages 355-361.
    23. 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.
    24. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    25. Zhao, Xiaojun & Shang, Pengjian & Lin, Aijing & Chen, Gang, 2011. "Multifractal Fourier detrended cross-correlation analysis of traffic signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3670-3678.
    26. Moreno, Blanca & Pereira da Silva, Patrícia, 2016. "How do Spanish polluting sectors' stock market returns react to European Union allowances prices? A panel data approach," Energy, Elsevier, vol. 103(C), pages 240-250.
    27. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
    28. Roger D. Huang & Ronald W. Masulis & Hans R. Stoll, 1996. "Energy shocks and financial markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(1), pages 1-27, February.
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