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Do cointegrated commodities bubble together? the case of hog, corn, and soybean

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  • Alexakis, Christos
  • Bagnarosa, Guillaume
  • Dowling, Michael

Abstract

Hog, corn, and soybean meal futures are shown to be cointegrated, reflecting the close intrinsic relationship of corn and soybean meal as the primary feed for hogs. Applying a recent technique to date-stamp pricing bubbles we further show that bubbles in feed do not appear to be associated with bubbles in the price of hogs. Instead there are temporary deviations in the spread between hog and feed, but the long-term cointegration relationship leads to a reversion towards the common trend. This finding sheds new insight into the price behaviour of commodities that depend for input costs on other commodities.

Suggested Citation

  • Alexakis, Christos & Bagnarosa, Guillaume & Dowling, Michael, 2017. "Do cointegrated commodities bubble together? the case of hog, corn, and soybean," Finance Research Letters, Elsevier, vol. 23(C), pages 96-102.
    • Handle: RePEc:eee:finlet:v:23:y:2017:i:c:p:96-102
    DOI: 10.1016/j.frl.2017.02.007
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    Cited by:

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    2. Caspi, Itamar & Graham, Meital, 2018. "Testing for bubbles in stock markets with irregular dividend distribution," Finance Research Letters, Elsevier, vol. 26(C), pages 89-94.
    3. Fatima, Hira & Ahmed, Mumtaz, 2019. "Testing for Exuberance Behavior in Agricultural Commodities of Pakistan," MPRA Paper 95304, University Library of Munich, Germany.
    4. Fang, Ming & Lin, Yizhou & Chang, Chiu-Lan, 2023. "Positive and negative price bubbles of Chinese agricultural commodity futures," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 456-471.
    5. Ma, Richie Ruchuan & Xiong, Tao, 2021. "Price explosiveness in nonferrous metal futures markets," Economic Modelling, Elsevier, vol. 94(C), pages 75-90.
    6. Dejan Živkov & Biljana Stankov & Nataša Papić-Blagojević & Jelena Damnjanović & Željko Račić, 2023. "How to reduce the extreme risk of losses in corn and soybean markets? Construction of a portfolio with European stock indices," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(3), pages 109-118.
    7. Liwen Ling & Dabin Zhang & Shanying Chen & Amin W. Mugera, 2020. "Can online search data improve the forecast accuracy of pork price in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 671-686, July.

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    More about this item

    Keywords

    Hog spread; Multiple bubbles; Commodities; Cointegration;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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