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The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes

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  • Mensi, Walid
  • Tiwari, Aviral
  • Bouri, Elie
  • Roubaud, David
  • Al-Yahyaee, Khamis H.

Abstract

This paper examines the dependence structure between three commodities implied volatility indexes (oil, wheat and corn) during bear, normal and bull markets and at different scales. For this purpose, we combine wavelet and copula methods to analyse the changes of the tail dependence at different scales or investment horizons. The results support evidence of time-varying asymmetric tail dependence between the pair of cereals as well as between oil and the two cereals at different time horizons – short-term horizon, medium term horizon and long term horizon, suggesting that the dependence structure is sensitive to time horizons. These results have important implications for the analysis of portfolio risk management.

Suggested Citation

  • Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
  • Handle: RePEc:eee:eneeco:v:66:y:2017:i:c:p:122-139
    DOI: 10.1016/j.eneco.2017.06.007
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    as
    1. Aboura, Sofiane & Chevallier, Julien, 2015. "Volatility returns with vengeance: Financial markets vs. commodities," Research in International Business and Finance, Elsevier, vol. 33(C), pages 334-354.
    2. Jiang, Jingze & Marsh, Thomas L. & Tozer, Peter R., 2015. "Policy induced price volatility transmission: Linking the U.S. crude oil, corn and plastics markets," Energy Economics, Elsevier, vol. 52(PA), pages 217-227.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Cartwright, Phillip A. & Riabko, Natalija, 2015. "Measuring the effect of oil prices on wheat futures prices," Research in International Business and Finance, Elsevier, vol. 33(C), pages 355-369.
    5. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2016. "Dynamics and evolution of the role of biofuels in global commodity and financial markets," Nature Energy, Nature, vol. 1(12), pages 1-9, December.
    6. Trujillo-Barrera, Andres & Mallory, Mindy L. & Garcia, Philip, 2012. "Volatility Spillovers in U.S. Crude Oil, Ethanol, and Corn Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-16, August.
    7. Sari, Ramazan & Hammoudeh, Shawkat & Chang, Chia-Lin & McAleer, Michael, 2012. "Causality between market liquidity and depth for energy and grains," Energy Economics, Elsevier, vol. 34(5), pages 1683-1692.
    8. 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.
    9. Gardebroek, Cornelis & Hernandez, Manuel A., 2013. "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," Energy Economics, Elsevier, vol. 40(C), pages 119-129.
    10. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    11. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    12. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    13. Jeffrey A. Frankel, 2008. "The Effect of Monetary Policy on Real Commodity Prices," NBER Chapters, in: Asset Prices and Monetary Policy, pages 291-333, National Bureau of Economic Research, Inc.
    14. Vacha, Lukas & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2013. "Time–frequency dynamics of biofuel–fuel–food system," Energy Economics, Elsevier, vol. 40(C), pages 233-241.
    15. Abdelradi, Fadi & Serra, Teresa, 2015. "Food–energy nexus in Europe: Price volatility approach," Energy Economics, Elsevier, vol. 48(C), pages 157-167.
    16. Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    17. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    18. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    19. Chen, Sheng-Tung & Kuo, Hsiao-I & Chen, Chi-Chung, 2010. "Modeling the relationship between the oil price and global food prices," Applied Energy, Elsevier, vol. 87(8), pages 2517-2525, August.
    20. Nicole M. Aulerich & Scott H. Irwin & Philip Garcia, 2014. "Bubbles, Food Prices, and Speculation: Evidence from the CFTC's Daily Large Trader Data Files," NBER Chapters, in: The Economics of Food Price Volatility, pages 211-253, National Bureau of Economic Research, Inc.
    21. Wallace E. Tyner, 2010. "The integration of energy and agricultural markets," Agricultural Economics, International Association of Agricultural Economists, vol. 41(s1), pages 193-201, November.
    22. Koirala, Krishna H. & Mishra, Ashok K. & D'Antoni, Jeremy M. & Mehlhorn, Joey E., 2015. "Energy prices and agricultural commodity prices: Testing correlation using copulas method," Energy, Elsevier, vol. 81(C), pages 430-436.
    23. repec:dau:papers:123456789/13359 is not listed on IDEAS
    24. 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.
    25. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    26. Nazlioglu, Saban & Soytas, Ugur, 2011. "World oil prices and agricultural commodity prices: Evidence from an emerging market," Energy Economics, Elsevier, vol. 33(3), pages 488-496, May.
    27. Fowowe, Babajide, 2016. "Do oil prices drive agricultural commodity prices? Evidence from South Africa," Energy, Elsevier, vol. 104(C), pages 149-157.
    28. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    29. 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.
    30. 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.
    31. Bouri, Elie & Jain, Anshul & Biswal, P.C. & Roubaud, David, 2017. "Cointegration and nonlinear causality amongst gold, oil, and the Indian stock market: Evidence from implied volatility indices," Resources Policy, Elsevier, vol. 52(C), pages 201-206.
    32. Brunetti, Celso & Reiffen, David, 2014. "Commodity index trading and hedging costs," Journal of Financial Markets, Elsevier, vol. 21(C), pages 153-180.
    33. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    34. Zibin Zhang & Luanne Lohr & Cesar Escalante & Michael Wetzstein, 2009. "Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-Fuels Market," Energies, MDPI, vol. 2(2), pages 1-20, June.
    35. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
    36. Dietrich Domanski & Alexandra Heath, 2007. "Financial investors and commodity markets," BIS Quarterly Review, Bank for International Settlements, March.
    37. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2016. "Contemporaneous interactions among fuel, biofuel and agricultural commodities," Energy Economics, Elsevier, vol. 58(C), pages 1-10.
    38. Uddin, Gazi Salah & Tiwari, Aviral Kumar & Arouri, Mohamed & Teulon, Frédéric, 2013. "On the relationship between oil price and exchange rates: A wavelet analysis," Economic Modelling, Elsevier, vol. 35(C), pages 502-507.
    39. 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.
    40. Liu, Ming-Lei & Ji, Qiang & Fan, Ying, 2013. "How does oil market uncertainty interact with other markets? An empirical analysis of implied volatility index," Energy, Elsevier, vol. 55(C), pages 860-868.
    41. Campbell, John Y. (ed.), 2008. "Asset Prices and Monetary Policy," National Bureau of Economic Research Books, University of Chicago Press, number 9780226092119, December.
    42. Adams, Zeno & Glueck, Thorsten, 2014. "Financialization in Commodity Markets: A Passing Trend or the New Normal?," Working Papers on Finance 1413, University of St. Gallen, School of Finance, revised Aug 2015.
    43. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    44. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    45. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
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    More about this item

    Keywords

    Commodity implied volatility; Dependence; Scale; Copula; Wavelet;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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