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Volatility linkages between energy and agricultural commodity prices

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  • Brenda López Cabrera,
  • Franziska Schulz,

Abstract

In this paper we investigate price and volatility risk originating in link- ages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for in- vestment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages (spillovers) are an- alyzed using a dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a exible and accurate fitting procedure for volatility and correlation risk.

Suggested Citation

  • Brenda López Cabrera, & Franziska Schulz,, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers SFB649DP2013-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2013-042
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    as
    1. Nakatani, Tomoaki & Teräsvirta, Timo, 2008. "Positivity constraints on the conditional variances in the family of conditional correlation GARCH models," Finance Research Letters, Elsevier, vol. 5(2), pages 88-95, June.
    2. Robles, Miguel & Torero, Maximo & von Braun, Joachim, 2009. "When speculation matters:," Issue briefs 57, International Food Policy Research Institute (IFPRI).
    3. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters,in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc.
    4. Teresa Serra & David Zilberman & José Gil, 2011. "Price volatility in ethanol markets," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 38(2), pages 259-280, June.
    5. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    6. Xiaodong Du and Lihong Lu McPhail, 2012. "Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    7. Buguk, Cumhur & Hudson, Darren & Hanson, Terrill R., 2003. "Price Volatility Spillover in Agricultural Markets: An Examination of U.S. Catfish Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 1), pages 1-14, April.
    8. 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.
    9. Yuan-Hung Hsu Ku & Ho-Chyuan Chen & Kuang-Hua Chen, 2007. "On the application of the dynamic conditional correlation model in estimating optimal time-varying hedge ratios," Applied Economics Letters, Taylor & Francis Journals, vol. 14(7), pages 503-509.
    10. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    11. Helmut Herwartz & Helmut Lütkepohl, 2011. "Generalized least squares estimation for cointegration parameters under conditional heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 281-291, May.
    12. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    13. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    14. Zhao, Jieyuan & Goodwin, Barry K., 2011. "Volatility Spillovers in Agricultural Commodity Markets: An Application Involving Implied Volatilities from Options Markets," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103636, Agricultural and Applied Economics Association.
    15. Jeantheau, Thierry, 1998. "Strong Consistency Of Estimators For Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 14(01), pages 70-86, February.
    16. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    17. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(04), pages 535-551, December.
    18. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    19. Nicholas Apergis & Anthony Rezitis, 2003. "Agricultural price volatility spillover effects: the case of Greece," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 30(3), pages 389-406, September.
    20. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    21. Derek Headey & Shenggen Fan, 2008. "Anatomy of a crisis: the causes and consequences of surging food prices," Agricultural Economics, International Association of Agricultural Economists, vol. 39(s1), pages 375-391, November.
    22. 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.
    23. Unknown, 2010. "SAEA 2010 Annual Meetings Selected Papers," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 0(Number 3), pages 1-22, August.
    24. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    25. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, October.
    26. Teresa Serra, 2015. "Price volatility in Niger millet markets," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 489-502, July.
    27. Tomoaki Nakatani & Timo Terasvirta, 2009. "Testing for volatility interactions in the Constant Conditional Correlation GARCH model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 147-163, March.
    28. Unknown, 2010. "SAEA 2010 Annual Meetings Selected Posters," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 0(Number 3), pages 1-3, August.
    29. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    30. Wolfgang Karl Härdle & Brenda López Cabrera & Ostap Okhrin & Weining Wang, 2016. "Localizing Temperature Risk," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1491-1508, October.
    31. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    32. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    33. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.
    34. Xiaoliang Liu & Guenther Filler & Martin Odening, 2013. "Testing for speculative bubbles in agricultural commodity prices: a regime switching approach," Agricultural Finance Review, Emerald Group Publishing, vol. 73(1), pages 179-200, May.
    35. Rathmann, Régis & Szklo, Alexandre & Schaeffer, Roberto, 2010. "Land use competition for production of food and liquid biofuels: An analysis of the arguments in the current debate," Renewable Energy, Elsevier, vol. 35(1), pages 14-22.
    36. Busse, Stefan & Brümmer, Bernhard & Ihle, Rico, 2010. "The Pattern of Integration between Fossil Fuel and Vegetable Oil Markets: The Case of Biodiesel in Germany," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61010, Agricultural and Applied Economics Association.
    37. Zibin Zhang & Luanne Lohr & Cesar Escalante & Michael Wetzstein, 2009. "Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-Fuels Market," Energies, MDPI, Open Access Journal, vol. 2(2), pages 1-20, June.
    38. Sorda, Giovanni & Banse, Martin & Kemfert, Claudia, 2010. "An overview of biofuel policies across the world," Energy Policy, Elsevier, vol. 38(11), pages 6977-6988, November.
    39. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    40. Bénédicte Vidaillet & V. D'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    41. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    42. Unknown, 2010. "Organized Symposia SAEA 2010 Annual Meetings," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 0(Number 3), pages 1-2, August.
    43. Myers, Robert J., 1994. "Time Series Econometrics and Commodity Price Analysis: A Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 02), pages 1-15, August.
    44. Hassouneh, Islam & Serra, Teresa & Goodwin, Barry K. & Gil, José M., 2012. "Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships," Energy Economics, Elsevier, vol. 34(5), pages 1507-1513.
    45. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    46. Seo, Byeongseon, 2007. "Asymptotic distribution of the cointegrating vector estimator in error correction models with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 137(1), pages 68-111, March.
    47. James Daniel, 2001. "Hedging Government Oil Price Risk," IMF Working Papers 01/185, International Monetary Fund.
    48. repec:hal:journl:peer-00732539 is not listed on IDEAS
    49. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, October.
    50. 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.
    51. Busse, Stefan & Brümmer, Bernhard & Ihle, Rico, 2010. "Investigating Rapeseed Price Volatilities In The Course Of The Food Crisis," 50th Annual Conference, Braunschweig, Germany, September 29-October 1, 2010 93957, German Association of Agricultural Economists (GEWISOLA).
    52. 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.
    53. Kelvin Balcombe & George Rapsomanikis, 2008. "Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(3), pages 658-668.
    54. 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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    Cited by:

    1. Rangga Handika & Rangga Handika & Sigit Triandaru, 2016. "Is the Best Generalized Autoregressive Conditional Heteroskedasticity(p,q) Value-at-risk Estimate also the Best in Reality? An Evidence from Australian Interconnected Power Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 6(4), pages 814-821.
    2. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. repec:eee:rensus:v:81:y:2018:i:p1:p:1002-1018 is not listed on IDEAS
    4. Xian, Hui & Colson, Gregory & Karali, Berna & Wetzstein, Michael, 2017. "Do nonrenewable-energy prices affect renewable-energy volatility? The case of wood pellets," Journal of Forest Economics, Elsevier, vol. 28(C), pages 42-48.
    5. Chang, Chia-Lin & McAleer, Michael & Wang, Yu-Ann, 2018. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn spot and futures prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1002-1018.
    6. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn," Econometric Institute Research Papers EI2016-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. repec:eee:ecmode:v:70:y:2018:i:c:p:97-114 is not listed on IDEAS
    8. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    9. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A. & Fijorek, Kamil, 2018. "What drives food price volatility? Evidence based on a generalized VAR approach applied to the food, financial and energy markets," Economics Discussion Papers 2018-55, Kiel Institute for the World Economy (IfW).
    10. Saghaian, Sayed H. & Nemati, Mehdi & Walters, Cory G. & Chen, Bo, 2017. "Asymmetric Price Volatility Interaction between U.S. Food and Energy Markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258240, Agricultural and Applied Economics Association.
    11. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    12. Siami-Namini, Sima & Hudson, Darren, 2017. "Volatility Spillover Between Oil Prices, Us Dollar Exchange Rates And International Agricultural Commodities Prices," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252845, Southern Agricultural Economics Association.
    13. repec:eee:phsmap:v:506:y:2018:i:c:p:671-678 is not listed on IDEAS

    More about this item

    Keywords

    Energy; Agriculture; Biodiesel; Commodities; Interdependencies; Volatility Spillovers;

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other
    • Q59 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Other

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