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Conditional correlation and volatility between spot and futures markets for soybean and corn

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  • Julyerme M. Tonin
  • Carlos M. R. Vieira
  • Rui M. de Sousa Fragoso
  • João G. Martines Filho

Abstract

This paper investigates the dynamics of volatility and conditional correlations between corn and soybean prices in the spot and futures markets. Faced with price and production risks, farmers must use all information available in their risk management process, both in their product's spot and futures markets, and in related products' markets, either domestic or foreign. Dynamic conditional correlation specifications with a bivariate GARCH model are employed, with data for Brazilian and U.S. markets in the period 2004–2017, during which several structural changes and extreme climate phenomena have occurred. We find the highest correlations between the corn and soybean spot markets, and evidence of spillovers in both products in the spot and futures markets. We also find that the financial crisis have significantly affected the relationship between the corn and soybean markets. We also find that in periods of increased conditional correlation between the soybean and corn markets, there is an increase in the optimal hedge ratio for risk management strategies involving corn futures contracts at B3 and Chicago Mercantile Exchange. [EconLit Citations: C32, G13, Q14].

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  • Julyerme M. Tonin & Carlos M. R. Vieira & Rui M. de Sousa Fragoso & João G. Martines Filho, 2020. "Conditional correlation and volatility between spot and futures markets for soybean and corn," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 707-724, October.
  • Handle: RePEc:wly:agribz:v:36:y:2020:i:4:p:707-724
    DOI: 10.1002/agr.21664
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    as
    1. Irwin, Scott H. & Sanders, Dwight R., 2012. "Financialization and Structural Change in Commodity Futures Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 371-396, August.
    2. William G. Tomek, 1980. "Price Behavior on a Declining Terminal Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(3), pages 434-444.
    3. Cornelis Gardebroek & Manuel A. Hernandez & Miguel Robles, 2016. "Market interdependence and volatility transmission among major crops," Agricultural Economics, International Association of Agricultural Economists, vol. 47(2), pages 141-155, March.
    4. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility," Energy Economics, Elsevier, vol. 45(C), pages 66-98.
    5. Robert J. Myers & Stanley R. Thompson, 1989. "Generalized Optimal Hedge Ratio Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 858-868.
    6. Newbery, David M, 1987. "When Do Futures Destabilize Spot Prices?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(2), pages 291-297, June.
    7. Aaron Smith, 2005. "Partially overlapping time series: a new model for volatility dynamics in commodity futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 405-422.
    8. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    9. Da‐Hsiang Donald Lien, 1996. "The effect of the cointegration relationship on futures hedging: A note," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(7), pages 773-780, October.
    10. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    11. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    12. Han, Liyan & Zhou, Yimin & Yin, Libo, 2015. "Exogenous impacts on the links between energy and agricultural commodity markets," Energy Economics, Elsevier, vol. 49(C), pages 350-358.
    13. David J. Pannell & Getu Hailu & Alfons Weersink & Amanda Burt, 2008. "More reasons why farmers have so little interest in futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 39(1), pages 41-50, July.
    14. Benoit Mandelbrot, 1963. "New Methods in Statistical Economics," Journal of Political Economy, University of Chicago Press, vol. 71, pages 421-421.
    15. Boudoukh, Jacob & Richardson, Matthew & Shen, YuQing (Jeff) & Whitelaw, Robert F., 2007. "Do asset prices reflect fundamentals? Freshly squeezed evidence from the OJ market," Journal of Financial Economics, Elsevier, vol. 83(2), pages 397-412, February.
    16. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    17. Etienne, Xiaoli L. & Trujillo-Barrera, Andrés & Hoffman, Linwood A., 2017. "Volatility Spillover and Time-Varying Conditional Correlation Between DDGS, Corn, and Soybean Meal Markets," Agricultural and Resource Economics Review, Cambridge University Press, vol. 46(3), pages 529-554, December.
    18. Lars Helge Haß & Christian Koziol & Denis Schweizer, 2014. "What Drives Contagion in Financial Markets? Liquidity Effects versus Information Spill†Over," European Financial Management, European Financial Management Association, vol. 20(3), pages 548-573, June.
    19. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    20. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    21. Fry, Renée & Martin, Vance L. & Tang, Chrismin, 2010. "A New Class of Tests of Contagion With Applications," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 423-437.
    22. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    23. Ronald W. Anderson & Jean-Pierre Danthine, 1983. "The Time Pattern of Hedging and the Volatility of Futures Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(2), pages 249-266.
    24. Tse, Y. K., 2000. "A test for constant correlations in a multivariate GARCH model," Journal of Econometrics, Elsevier, vol. 98(1), pages 107-127, September.
    25. Donald Lien & Y. K. Tse, 2002. "Some Recent Developments in Futures Hedging," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 357-396, July.
    26. Liu, Hsiang-Hsi & Chen, Yi-Chun, 2013. "A study on the volatility spillovers, long memory effects and interactions between carbon and energy markets: The impacts of extreme weather," Economic Modelling, Elsevier, vol. 35(C), pages 840-855.
    27. Baldi, Lucia & Peri, Massimo & Vandone, Daniela, 2016. "Stock markets’ bubbles burst and volatility spillovers in agricultural commodity markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 277-285.
    28. Lien, Donald & Tse, Y K, 2002. "Some Recent Developments in Futures Hedging," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 357-396, July.
    29. Cruz Júnior, José César & Irwin, Scott H. & Marques, Pedro Valentim & Martines-Filho, Joao Gomes & Bacchi, Mirian Rumenos Piedade, 2011. "O Excesso de Confiança dos Produtores de Milho no Brasil e o Uso de Contratos Futuros," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 49(2), pages 1-22, June.
    30. Haase, Marco & Seiler Zimmermann, Yvonne & Zimmermann, Heinz, 2016. "The impact of speculation on commodity futures markets – A review of the findings of 100 empirical studies," Journal of Commodity Markets, Elsevier, vol. 3(1), pages 1-15.
    31. Feng Wu & Zhengfei Guan & Robert J. Myers, 2011. "Volatility spillover effects and cross hedging in corn and crude oil futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(11), pages 1052-1075, November.
    32. Fabio L. Mattos & Rodrigo Lanna Franco da Silveira, 2018. "The Expansion of the Brazilian Winter Corn Crop and Its Impact on Price Transmission," IJFS, MDPI, vol. 6(2), pages 1-17, April.
    33. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    34. Gozgor, Giray & Lau, Chi Keung Marco & Bilgin, Mehmet Huseyin, 2016. "Commodity markets volatility transmission: Roles of risk perceptions and uncertainty in financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 35-45.
    35. Dornbusch, Rudiger & Park, Yung Chul & Claessens, Stijn, 2000. "Contagion: Understanding How It Spreads," The World Bank Research Observer, World Bank, vol. 15(2), pages 177-197, August.
    36. Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2017. "Modeling and forecasting the volatility of carbon dioxide emission allowance prices: A review and comparison of modern volatility models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 692-704.
    37. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
    38. Yuan-Hung Hsu Ku, 2008. "Student-t distribution based VAR-MGARCH: an application of the DCC model on international portfolio risk management," Applied Economics, Taylor & Francis Journals, vol. 40(13), pages 1685-1697.
    39. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    1. Dejan Živkov & Suzana Balaban & Marijana Joksimović, 2022. "Making a Markowitz portfolio with agricultural commodity futures," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(6), pages 219-229.

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