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Dynamic Volatility Spillovers Between Agricultural And Energy Commodities

Author

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  • XIARCHOS, IRENE M.
  • BURNETT, J. WESLEY

Abstract

This study contributes to the literature by using a spillover index method to examine the changing interrelations in volatility among corn and energy future prices. This methodology allows us to account for endogenously determined economic fundamentals and market speculation. After controlling for market trends and seasonality, we find relative large increases in volatility spillovers between corn, crude oil, and ethanol futures prices. Our results suggest that the cross-commodity spillovers provide useful incremental information in determining future price volatility; however, a commodity's own dynamics explain the largest portion of volatility spillovers.

Suggested Citation

  • Xiarchos, Irene M. & Burnett, J. Wesley, 2018. "Dynamic Volatility Spillovers Between Agricultural And Energy Commodities," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 50(3), pages 291-318, August.
    • Handle: RePEc:cup:jagaec:v:50:y:2018:i:03:p:291-318_00
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    Citations

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    Cited by:

    1. Corbet, Shaen & Goodell, John W. & Günay, Samet, 2020. "Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19," Energy Economics, Elsevier, vol. 92(C).
    2. Vo, Long Hai & Le, Thai-Ha, 2021. "Eatery, energy, environment and economic system, 1970–2017: Understanding volatility spillover patterns in a global sample," Energy Economics, Elsevier, vol. 100(C).
    3. Sun, Yanpeng & Mirza, Nawazish & Qadeer, Abdul & Hsueh, Hsin-Pei, 2021. "Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?," Resources Policy, Elsevier, vol. 72(C).
    4. Hanif, Waqas & Areola Hernandez, Jose & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2021. "Tail dependence risk and spillovers between oil and food prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 195-209.
    5. Chen, Hao & Xu, Chao & Peng, Yun, 2022. "Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China," Resources Policy, Elsevier, vol. 78(C).
    6. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    7. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    8. de Souza Ramser, Claudia Aline & Souza, Adriano Mendonça & Souza, Francisca Mendonça & da Veiga, Claudimar Pereira & da Silva, Wesley Vieira, 2019. "The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy," Resources Policy, Elsevier, vol. 62(C), pages 9-21.
    9. Khalfaoui, Rabeh & Shahzad, Umer & Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2023. "Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 63-80.
    10. Ida Farida & Faurani Santi Singagerda, 2021. "Volatilitiy of World Food Commodity Prices and Renewable Fuel Standard Policy," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 516-527.

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