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Volatility and Risk in the Energy Market: A Trade Network Approach

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  • Germán G. Creamer

    (School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, USA)

  • Tal Ben-Zvi

    (School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, USA)

Abstract

This paper evaluates the effect of energy trade networks on the price volatility of coal, oil, natural gas, and electricity. This research conducts a longitudinal analysis using a time series of static coal trade networks to generate a dynamic trade network. It uses the component causality index as a leading indicator of the price volatility of the energy market. This research finds out that the component causality index, based on degree centrality, anticipates or moves together with coal volatility and, to a lesser degree, with natural gas and electricity volatility for the period 1998–2014. The proposed index could be integrated into a risk management system for investors and regulators. The broad impact of this research lies in the understanding of mechanisms of the instability and risk of the energy sector as a result of a complex interaction of the network of producers and traders.

Suggested Citation

  • Germán G. Creamer & Tal Ben-Zvi, 2021. "Volatility and Risk in the Energy Market: A Trade Network Approach," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10199-:d:634210
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    as
    1. Lance J. Bachmeier & James M. Griffin, 2006. "Testing for Market Integration: Crude Oil, Coal, and Natural Gas," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 55-72.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    3. Stephen P. A. Brown & Mine K. Yucel, 2008. "What Drives Natural Gas Prices?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 45-60.
    4. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    5. Peter R. Hartley & Kenneth B Medlock III & Jennifer E. Rosthal, 2008. "The Relationship of Natural Gas to Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 47-66.
    6. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    7. Cesar A. Hidalgo & Ricardo Hausmann, 2009. "The Building Blocks of Economic Complexity," Papers 0909.3890, arXiv.org.
    8. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    9. Dror Y Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2012. "Evolvement of Uniformity and Volatility in the Stressed Global Financial Village," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    10. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
    11. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    12. Cole, Matthew A. & Elliott, Robert J.R. & Okubo, Toshihiro & Zhou, Ying, 2013. "The carbon dioxide emissions of firms: A spatial analysis," Journal of Environmental Economics and Management, Elsevier, vol. 65(2), pages 290-309.
    13. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1121-1141.
    14. Hassan Mohammadi, 2011. "Long-run relations and short-run dynamics among coal, natural gas and oil prices," Applied Economics, Taylor & Francis Journals, vol. 43(2), pages 129-137.
    15. Kentaka Aruga & Shunsuke Managi, 2013. "Linkages among the US energy futures markets," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 36(1), pages 13-26.
    16. Blake LeBaron, "undated". "Persistence of the Dow Jones Index on Rising Volume," Working papers _006, University of Wisconsin - Madison.
    17. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    18. Mohammadi, Hassan, 2009. "Electricity prices and fuel costs: Long-run relations and short-run dynamics," Energy Economics, Elsevier, vol. 31(3), pages 503-509, May.
    19. Gregory R. Duffee, 1992. "Trading volume and return reversals," Finance and Economics Discussion Series 192, Board of Governors of the Federal Reserve System (U.S.).
    20. Dror Y. Kenett & Sary Levy-Carciente & Adam Avakian & H. Eugene Stanley & Shlomo Havlin, 2015. "Dynamical Macroprudential Stress Testing Using Network Theory," Working Papers 15-12, Office of Financial Research, US Department of the Treasury.
    21. Hinich, Melvin J & Patterson, Douglas M, 1985. "Evidence of Nonlinearity in Daily Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(1), pages 69-77, January.
    22. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    23. Glasserman, Paul & Young, H. Peyton, 2015. "How likely is contagion in financial networks?," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 383-399.
    24. Martin Summer, 2013. "Financial Contagion and Network Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 277-297, November.
    25. Levy-Carciente, Sary & Kenett, Dror Y. & Avakian, Adam & Stanley, H. Eugene & Havlin, Shlomo, 2015. "Dynamical macroprudential stress testing using network theory," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 164-181.
    26. Racicot, François-Éric & Théoret, Raymond, 2018. "Multi-moment risk, hedging strategies, & the business cycle," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 637-675.
    27. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    28. Dong-Ming Song & Michele Tumminello & Wei-Xing Zhou & Rosario N. Mantegna, 2011. "Evolution of worldwide stock markets, correlation structure and correlation based graphs," Papers 1103.5555, arXiv.org.
    29. Asche, Frank & Gjolberg, Ole & Volker, Teresa, 2003. "Price relationships in the petroleum market: an analysis of crude oil and refined product prices," Energy Economics, Elsevier, vol. 25(3), pages 289-301, May.
    30. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    31. Niccolò Casnici & Pierpaolo Dondio & Roberto Casarin & Flaminio Squazzoni, 2015. "Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-15, August.
    32. Vasant Dhar & Tomer Geva & Gal Oestreicher-Singer & Arun Sundararajan, 2014. "Prediction in Economic Networks," Information Systems Research, INFORMS, vol. 25(2), pages 264-284, June.
    33. Chintrakarn, Pandej & Millimet, Daniel L., 2006. "The environmental consequences of trade: Evidence from subnational trade flows," Journal of Environmental Economics and Management, Elsevier, vol. 52(1), pages 430-453, July.
    34. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    35. Bai, Zhidong & Wong, Wing-Keung & Zhang, Bingzhi, 2010. "Multivariate linear and nonlinear causality tests," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 5-17.
    36. Amil Dasgupta, 2004. "Financial Contagion Through Capital Connections: A Model of the Origin and Spread of Bank Panics," Journal of the European Economic Association, MIT Press, vol. 2(6), pages 1049-1084, December.
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