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Smooth volatility shifts and spillovers in U.S. crude oil and corn futures markets

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  • Teterin, Pavel
  • Brooks, Robert
  • Enders, Walter

Abstract

Recent developments in biofuel technologies have resulted in heightened linkages between the petroleum and agricultural sectors. As such, a large price and/or volatility shift experienced in one sector is now more likely to spill-over into the other. In trying to capture the interrelations present in the two markets, we take seriously the importance of properly modeling smooth structural shifts. We incorporate trigonometric functions into a multivariate GARCH model of crude and corn futures prices in order to obtain the empirical volatility response functions and the time-varying correlation coefficient. Although both short-term and long-term futures exhibit shifts in the mean and volatility, volatility shifts do not manifest themselves in the same manner for different maturities. This indicates that the term structure of futures volatility changes over time.

Suggested Citation

  • Teterin, Pavel & Brooks, Robert & Enders, Walter, 2016. "Smooth volatility shifts and spillovers in U.S. crude oil and corn futures markets," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 22-36.
    • Handle: RePEc:eee:empfin:v:38:y:2016:i:pa:p:22-36
    DOI: 10.1016/j.jempfin.2016.05.005
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    Cited by:

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    5. Heckelei, T. & Amrouk, E.M. & Grosche, S., 2018. "International interdependence between cash crop and staple food futures price indices: A wavelet-BEKK-GARCH assessment," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277376, International Association of Agricultural Economists.
    6. Zhang, Yue-Jun & Yao, Ting & He, Ling-Yun & Ripple, Ronald, 2019. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 302-317.
    7. Nicholas Apergis & Umit Bulut & Gulbahar Ucler & Serife Ozsahin, 2021. "The causal linkage between inflation and inflation uncertainty under structural breaks: Evidence from Turkey," Manchester School, University of Manchester, vol. 89(3), pages 259-275, June.
    8. Guo, Ranran & Ye, Wuyi, 2021. "A model of dynamic tail dependence between crude oil prices and exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    9. Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
    10. Tiwari, Aviral Kumar & Boachie, Micheal Kofi & Suleman, Muhammed Tahir & Gupta, Rangan, 2021. "Structure dependence between oil and agricultural commodities returns: The role of geopolitical risks," Energy, Elsevier, vol. 219(C).
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    12. Nazlioglu, Saban & Gupta, Rangan & Gormus, Alper & Soytas, Ugur, 2020. "Price and volatility linkages between international REITs and oil markets," Energy Economics, Elsevier, vol. 88(C).
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    14. Brooks, Robert & Brooks, Joshua A., 2022. "Samuelson hypothesis and carry arbitrage: U.S. and China," Journal of International Money and Finance, Elsevier, vol. 128(C).
    15. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
    16. Cheng, Natalie Fang Ling & Hasanov, Akram Shavkatovich & Poon, Wai Ching & Bouri, Elie, 2023. "The US-China trade war and the volatility linkages between energy and agricultural commodities," Energy Economics, Elsevier, vol. 120(C).
    17. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    18. Debasish Maitra & Varun Dawar, 2019. "Return and Volatility Spillover among Commodity Futures, Stock Market and Exchange Rate: Evidence from India," Global Business Review, International Management Institute, vol. 20(1), pages 214-237, February.
    19. Hau, Liya & Zhu, Huiming & Huang, Rui & Ma, Xiang, 2020. "Heterogeneous dependence between crude oil price volatility and China’s agriculture commodity futures: Evidence from quantile-on-quantile regression," Energy, Elsevier, vol. 213(C).
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    More about this item

    Keywords

    Corn futures; Crude oil futures; Multivariate GARCH; Volatility breaks; Fourier flexible form; Variance impulse response function;
    All these keywords.

    JEL classification:

    • 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
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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