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Modeling Price Volatility Linkages between Corn and Wheat: A Multivariate GARCH Estimation

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  • Naveen Musunuru

Abstract

The present paper attempts an empirical investigation on price volatility linkages between two important agricultural commodities: corn and wheat, by using a multivariate GARCH-BEKK model. Evidence of bidirectional linkages were found between corn and wheat in terms of returns and volatility. Multivariate conditional Student’s-t distribution results show a unidirectional volatility transmission from corn to wheat. Diagnostic tests reveal that the Student’s-t distribution will better model the volatility of returns when compared to the Gaussian distribution. Overall, the results show that the conditional variances and covariances between agricultural commodity market returns exhibit significant changes over time. Copyright International Atlantic Economic Society 2014

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  • Naveen Musunuru, 2014. "Modeling Price Volatility Linkages between Corn and Wheat: A Multivariate GARCH Estimation," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(3), pages 269-280, August.
    • Handle: RePEc:kap:iaecre:v:20:y:2014:i:3:p:269-280:10.1007/s11294-014-9477-9
    DOI: 10.1007/s11294-014-9477-9
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    Cited by:

    1. Dejan Živkov & Jovan Njegić & Marko Pećanac, 2019. "Multiscale interdependence between the major agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(2), pages 82-92.
    2. Marwa Ben Abdallah & Maria Fekete Farkas & Zoltan Lakner, 2020. "Analysis of meat price volatility and volatility spillovers in Finland," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(2), pages 84-91.
    3. 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.
    4. Kshitij Kakade & Aswini Kumar Mishra & Kshitish Ghate & Shivang Gupta, 2022. "Forecasting Commodity Market Returns Volatility: A Hybrid Ensemble Learning GARCH‐LSTM based Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(2), pages 103-117, April.
    5. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    6. Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.

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    More about this item

    Keywords

    Multivariate GARCH BEKK; Corn; Wheat; Volatility; Conditional covariance; C58; Q13;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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