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Volatility and a century of energy markets dynamics
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Volatility and a century of energy markets dynamics

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  • Serletis, Apostolos
  • Xu, Libo

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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  • Serletis, Apostolos & Xu, Libo, 2016. "Volatility and a century of energy markets dynamics," Energy Economics, Elsevier, vol. 55(C), pages 1-9.
    • Handle: RePEc:eee:eneeco:v:55:y:2016:i:c:p:1-9
    DOI: 10.1016/j.eneco.2016.01.007
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    Cited by:

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    7. 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.
    8. Wang, Tiantian & Wu, Fei & Dickinson, David & Zhao, Wanli, 2024. "Energy price bubbles and extreme price movements: Evidence from China's coal market," Energy Economics, Elsevier, vol. 129(C).
    9. 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.
    10. 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.
    11. 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..
    12. Haokai Xie & Pu Zhao & Xudong Ji & Qun Lin & Lianguang Liu, 2019. "Expansion Planning Method of the Industrial Park Integrated Energy System Considering Regret Aversion," Energies, MDPI, vol. 12(21), pages 1-20, October.
    13. 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.
    14. 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).
    15. Guo, Yanfeng & Zhao, Huanyu, 2024. "Volatility spillovers between oil and coal prices and its implications for energy portfolio management in China," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 446-457.
    16. 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.
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    18. Ding, Lili & Zhao, Zhongchao & Han, Meng, 2021. "Probability density forecasts for steam coal prices in China: The role of high-frequency factors," Energy, Elsevier, vol. 220(C).

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    More about this item

    Keywords

    Oil; Natural gas; Coal; Volatility; VARMA; GARCH-in-Mean model;
    All these keywords.

    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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