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Volatility and a Century of Energy Markets Dynamics

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  • Apostolos Serletis

    (University of Calgary)

  • Libo Xu

    (University of Calgary)

Abstract

How similar is the price behavior of oil, natural gas, and coal? Are there any interactions among these three fuel prices and their volatilities? Using the Yatchew and Dimitropoulos (2016) annual data for the United States, over the period from 1870 to 2014, and state-of-the-art econometric methodology, we explore for spillovers and interactions among the three energy markets. In doing so, we use a range of univariate and multivariate volatility models. The key contribution to the literature is the estimation of a trivariate BEKK model that allows for the interdependence of oil, natural gas, and coal returns and volatilities, using the longest span prices that have ever been studied before.
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Suggested Citation

  • Apostolos Serletis & Libo Xu, "undated". "Volatility and a Century of Energy Markets Dynamics," Working Papers 2016-29, Department of Economics, University of Calgary, revised 28 Jan 2016.
    • Handle: RePEc:clg:wpaper:2016-29
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    4. Lv, Xin & Lien, Donald & Yu, Chang, 2020. "Who affects who? Oil price against the stock return of oil-related companies: Evidence from the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 85-100.
    5. Pettinau, Alberto & Ferrara, Francesca & Tola, Vittorio & Cau, Giorgio, 2017. "Techno-economic comparison between different technologies for CO2-free power generation from coal," Applied Energy, Elsevier, vol. 193(C), pages 426-439.
    6. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: Evidences from China’s coal market," Energy Economics, Elsevier, vol. 84(C).
    7. Xiufeng Xing & Yingjia Cong & Yu Wang & Xueqing Wang, 2023. "The Impact of COVID-19 and War in Ukraine on Energy Prices of Oil and Natural Gas," Sustainability, MDPI, vol. 15(19), pages 1-16, September.
    8. Gondo, Rocío & Vega, Marco, 2019. "The dynamics of investment projects: Evidence from Peru," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 324-340.
    9. Afees A. Salisu & Raymond Swaray, 2020. "Forecasting the Return Volatility of Energy Prices: A GARCH-MIDAS Approach," World Scientific Book Chapters, in: Stéphane Goutte & Duc Khuong Nguyen (ed.), HANDBOOK OF ENERGY FINANCE Theories, Practices and Simulations, chapter 3, pages 47-71, World Scientific Publishing Co. Pte. Ltd..
    10. Asadi, Mehrad & Roudari, Soheil & Tiwari, Aviral Kumar & Roubaud, David, 2023. "Scrutinizing commodity markets by quantile spillovers: A case study of the Australian economy," Energy Economics, Elsevier, vol. 118(C).
    11. Shrestha, Keshab & Subramaniam, Ravichandran & Peranginangin, Yessy & Philip, Sheena Sara Suresh, 2018. "Quantile hedge ratio for energy markets," Energy Economics, Elsevier, vol. 71(C), pages 253-272.
    12. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: evidences from China’s coal market," LSE Research Online Documents on Economics 102540, London School of Economics and Political Science, LSE Library.
    13. Pablo Cansado-Bravo & Carlos Rodríguez-Monroy, 2018. "Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices," Energies, MDPI, vol. 11(12), pages 1-17, December.
    14. Wang, Xiaoyu & Wang, Jiaojiao & Wang, Wenhuan & Zhang, Shuquan, 2023. "International and Chinese energy markets: Dynamic spillover effects," Energy, Elsevier, vol. 282(C).
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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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