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Market interdependence and volatility transmission among major crops:

Author

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  • Gardebroek, Cornelis
  • Hernandez, Manuel A.
  • Robles, Miguel

Abstract

This paper provides a comprehensive analysis of the dynamics of volatility between the corn, wheat, and soybean markets in the United States. Volatility interactions across markets, if they exist, may lower the effectiveness of diversification strategies to mitigate price risks and should be taken into account when analyzing the pricing behavior of different agricultural commodities. We follow a Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) approach to evaluate the level of interdependence and volatility transmission across these major crops on a daily, weekly, and monthly basis.

Suggested Citation

  • Gardebroek, Cornelis & Hernandez, Manuel A. & Robles, Miguel, 2014. "Market interdependence and volatility transmission among major crops:," IFPRI discussion papers 1344, International Food Policy Research Institute (IFPRI).
  • Handle: RePEc:fpr:ifprid:1344
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Saghaian, Sayed & Nemati, Mehdi & Walters, Cory & Chen, Bo, 2018. "Asymmetric Price Volatility Transmission between U.S. Biofuel, Corn, and Oil Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(1), January.
    2. de Nicola, Francesca & De Pace, Pierangelo & Hernandez, Manuel A., 2014. "Co-movement of major commodity price returns: A time-series assessment:," IFPRI discussion papers 1354, International Food Policy Research Institute (IFPRI).
    3. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    4. Hamadi, Hassan & Bassil, Charbel & Nehme, Tamara, 2017. "News surprises and volatility spillover among agricultural commodities: The case of corn, wheat, soybean and soybean oil," Research in International Business and Finance, Elsevier, vol. 41(C), pages 148-157.
    5. Santiago Guerrero & Gerardo Hernández†del†Valle & Miriam Juárez†Torres, 2017. "Using a functional approach to test trending volatility in the price of Mexican and international agricultural products," Agricultural Economics, International Association of Agricultural Economists, vol. 48(1), pages 3-13, January.
    6. Dohnal, Mirko & Doubravsky, Karel, 2016. "Equationless and equation-based trend models of prohibitively complex technological and related forecasts," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 297-304.
    7. Ceballos, Francisco & Hernandez, Manuel A. & Minot, Nicholas & Robles, Miguel, 2017. "Grain Price and Volatility Transmission from International to Domestic Markets in Developing Countries," World Development, Elsevier, vol. 94(C), pages 305-320.
    8. Śmiech, Sławomir & Papież, Monika & Fijorek, Kamil & Dąbrowski, Marek A., 2019. "What drives food price volatility? Evidence based on a generalized VAR approach applied to the food, financial and energy markets," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 13, pages 1-32.
    9. Matthias Kalkuhl & Lukas Kornher & Marta Kozicka & Pierre Boulanger & Maximo Torero, 2013. "Conceptual framework on price volatility and its impact on food and nutrition security in the short term," FOODSECURE Working papers 15, LEI Wageningen UR.
    10. Refk Selmi & Jamal Bouoiyour, 2020. "Global Market's Diagnosis on Coronavirus : A Tug of War between Hope and Fear," Working Papers hal-02514428, HAL.
    11. Ayesha Sayed & Christo Auret, 2020. "Volatility transmission in the South African white maize futures market," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(1), pages 71-88, March.
    12. Czudaj, Robert L., 2019. "Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach," Econometrics and Statistics, Elsevier, vol. 12(C), pages 78-145.
    13. Christian Gross, 2017. "Examining the Common Dynamics of Commodity Futures Prices," CQE Working Papers 6317, Center for Quantitative Economics (CQE), University of Muenster.

    More about this item

    Keywords

    Prices; volatility; agricultural products; Commodities; Markets; volatility transmission; agricultural commodities; Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH);

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • 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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