Modelling volatility spillovers for bio-ethanol, sugarcane and corn

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Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
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The recent and rapidly growing interest in biofuel as a green energy source has raised concerns about its impact on the prices, returns and volatility of related agricultural commodities. Analyzing the spillover effects on agricultural commodities and biofuel helps commodity suppliers hedge their portfolios, and manage the risk and co-risk of their biofuel and agricultural commodities. There have been many papers concerned with analyzing crude oil and agricultural commodities separately. The purpose of this paper is to examine the volatility spillovers for spot and futures returns on bio-ethanol and related agricultural commodities, specifically corn and sugarcane, using the multivariate diagonal BEKK conditional volatility model. The daily data used are from 31 October 2005 to 14 January 2015. The empirical results show that in 2 of 6 cases for the spot market, there were significant negative co-volatility spillover effects, specifically corn on subsequent sugarcane co-volatility with corn, and sugarcane on subsequent corn co-volatility with sugarcane. In the other 4 cases, there are no significant co-volatility spillover effects. There are significant positive co-volatility spillover effects in all 6 cases, namely between corn and sugarcane, corn and ethanol, and sugarcane and ethanol, and vice-versa, for each of the three pairs of commodities. It is clear that the futures prices of bio-ethanol and the two agricultural commodities, corn and sugarcane, have stronger co-volatility spillovers than their spot price counterparts. These empirical results suggest that the bio-ethanol and agricultural commodities should be considered as viable futures products in financial portfolios for risk management.
For financial support, the first author wishes to thank the National Science Council, Taiwan, and the second author is grateful to the National Science Council, Taiwan and the Australian Research Council.
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Baba, Y., R. F.Engle, D. Kraft, and K.F. Kroner (1985), “Multivariate Simultaneous Generalized ARCH,” Unpublished manuscript, Department of Economics, University of California, San Diego, CA, USA. Black, F. (1976), “The Pricing of Commodity Contracts,” Journal of Financial Economics, 3, Issues 1–2, 167-179. Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroscedasticity,” Journal of Econometrics, 31(3), 307-327. Bollerslev, T. (1990), “Modelling the Coherence in Short-run Nominal Exchange Rate: A Multivariate Generalized ARCH Approach,” Review of Economics and Statistics, 72(3), 498-505. Bollerslev, T., R.F. Engle, and J.M. Wooldridge (1988), “A Capital Asset Pricing Model with Time Varying Covariance,” Journal of Political Economy, 96(1), 116-131. Cabrera, B.L. and F. Schulz (2013), “Volatility Linkages between Energy and Agricultural Commodity Prices,” SFB 649 Discusion paper 2013-042, Economic Risk. Berlin. Caporin, M. and M. McAleer (2008), “Scalar BEKK and Indirect DCC,” Journal of Forecasting, 27, Issue 6, 537-549. Caporin, M. and M. McAleer (2012), “Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models,” Journal of Economic Surveys, 26(4), 736-751. Cesar, R.G. and Z. Marco (2012), “Effectiveness of Hedging within the High Price Volatility Context,” Land Economy Working Paper Series, Number 69, SRUC. Chang, C.-L., B.-W. Huang, M.-G. Chen, and M. McAleer (2011), “Modelling the Asymmetric Volatility in Hog Prices in Taiwan: The Impact of Joining the WTO,” Mathematics and Computers in Simulation, 81(7), 1491-1506. Chang, C.-L., L.-H. Chen, S. Hammoudeh, and M. McAleer (2012), “Asymmetric Adjustments in the Ethanol and Grains Markets,” Energy Economics, 34(6), 1990-2002. Chang, C.-L., M. McAleer, and R. Tansuchat (2011), “Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH,” Energy Economics, 33(5), 912-923. Dickey, D.A. and W.A. Fuller (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root,” Journal of the American Statistical Association, 74(366), 427–431. Egelkraut, T.M., P. Garcia, and B.J. Sherrick (2007), “The Term Structure of Implied Forward Volatility: Recovery and Informational Content in the Corn Options Market,” American Journal of Agricultural Economics, 89(1), 1-11. Engle, R.F. (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance on United Kingdom Inflation,” Econometrica, 50(4), 987-1007. Engle, R.F. (2002), “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Hereoskedasticity Models,” Journal of Business and Economic Statistics, 20(3), 339-350. Engle, R.F. and K.F. Kroner (1995), “Multivariate Simultaneous Generalized ARCH,” Econometric Theory, 11(1), 122-150. Glosten, L.R., R. Jagannathan, and D.E. Runkle (1993), “On the Relation between the Expected Value and Volatility of Nominal Excess Return on Stocks,” Journal of Finance, 48(5), 1779-1801. Hafner, C.M. and H. Herwartz (2006), “A Lagrange Multiplier Test for Causality in Variance,” Economics Letters, 93 (1), 137–141. Hafner, C. and M. McAleer (2014), “A One Line Derivation of DCC: Application of a Vector Random Coefficient Moving Average Process,” Tinbergen Institute Discussion Paper, 14-087, The Netherlands. Haynes, J. (1895), “Risk as an Economic Factor,” The Quarterly Journal of Economics, 9(4), 409-449. Jeantheau, T. (1998), “Strong Consistency of Estimators for Multivariate ARCH Models,” Econometric Theory, 14(1), 70-86. Jin, H.J. and D.L. Frechette (2004), “Fractional Integration in Agricultural Futures Price Volatilities,” American Journal of Agricultural Economics, 86(2), 432-443. Langley, S.V., M. Giugale, W.H. Meyers, and C. Hallahan (2000), “International Financial Volatility and Agricultural Commodity Trade: A Primer,” American Journal of Agricultural Economics, 82(3), 695-700. Lence, S.H. and D.J. Hayes (2002), “U.S. Farm Policy and the Volatility of Commodity Prices and Farm Revenues,” American Journal of Agricultural Economics, 84(2), 335-351. Ling, S. and M. McAleer (2003), “Asymptotic Theory for a Vector ARMA-GARCH Model,” Econometric Theory, 19(2), 280-310. Martinet, G.G. and M. McAleer (2016), “On the Invertibility of EGARCH(p,q),” to appear in Econometric Reviews. McAleer, M. (2014), “Asymmetry and Leverage in Conditional Volatility Models,” Econometrics, 2(3), 145-150. McAleer, M. and C. Hafner (2014), “A One Line Derivation of EGARCH,” Econometrics, 2(2), 92-97. McAleer, M., F. Chan, S. Hoti, and O. Lieberman (2008), “Generalized Autoregressive Conditional Correlation,” Econometric Theory, 24(6), 1554-1583. McAleer, M., S. Hoti, and F. Chan (2009), “Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility,” Econometric Reviews, 28, Issue5, 422-440. Nazlioglu, S., C. Erdem, and U. Soytas (2013), “Volatility Spillover between Oil and Agricultural Commodity Markets,” Energy Economics, 36, 658-665. Nelson, D. B. (1990), “ARCH Models as Diffusion Approximations,” Journal of Econometrics, 45(1-2), 7-38. Nelson, D.B. (1991), “Conditional Heteroskedasticity in Asset Returns: A New Approach,” Econometrica, 59(2), 347-370. Phillips, P.C.B. and P. Perron (1988), “Testing for a Unit Root in Time Series Regression,” Biometrika, 75(2), 335-346. Revoredo-Giha, C. and M. Zuppiroli (2012), “Effectiveness of Hedging within the High Price Volatility Context,” Land Economy Working Paper Series, Number: 69, SRUC. Renewable Fuels Association (2014), “Ethanol Facts: Agriculture,” Washington, DC: Renewable Fuels Association. Said, S.E. and D.A. Dickey (1984), “Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order,” Biometrika, 71 (3), 599-607. Schwartz, E.S. (1997), “The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging,” Journal of Finance, 52, 923-73. Sendhil, R., A. Kar, V.C. Mathur, and G.K. Jha (2013), “Price Discovery, Transmission and Volatility: Evidence from Agricultural Commodity Futures,” Agricultural Economics Research Review, 26(1), 41-54. Serra, T. (2011), “Volatility Spillovers between Food and Energy Markets: A Semiparametric Approach,” Energy Economics, 33, Issue6, 1155-1164. Serra T. (2012), “Biofuel-related Price Volatility Literature: A Review and New Approaches,” Paper Presented at the Conference on International Association of Agricultural Economists (IAAE) Triennial. Foz do Iguaçu, Brazil. Serra, T., D. Zilberman, and J. Gil (2011), “Price Volatility in Ethanol Markets,” European Review of Agricultural Economics, 38(2), 259-280. Serra, T. and Gil, J.M. (2013), “Price volatility in food markets: can stock building mitigate price fluctuations,” European Review of Agricultural Economics, 40(3), 507-528. Texas Comptroller of Public Accounts (2008), “The Energy Report – Ethanol”. Texas: Texas Comptroller of Public Accounts. Trujillo-Barrera, A., M. Mallory, and P. Garcia (2012), “Volatility Spillovers in U.S. Crude Oil, Ethanol, and Corn Futures Markets,” Journal of Agricultural and Resource Economics, 37(2), 247–262. Tsay, R. S. (1987), “Conditional Heteroscedastic Time Series Models,” Journal of the American Statistical Association, 82(398), 590-604. Tse, Y.K. and A.K.C. Tsui (2002), “A Multivariate GARCH Model with Time-Varying Correlations,” Journal of Business and Economic Statistics, 20(3), 351-362. U.S. Energy Information Administration (2014), “Biofuels Production Drives Growth in Overall Biomass Energy Use over Past Decade,” Washington, DC: U.S. Energy Information Administration. Wisner, R. (2008), “Impact of Ethanol on the Livestock and Poultry Industry,” Renewable Fuels Association, October.(, accessed 1 January 2016). Zhang, D., F. Asche, and A. Oglend (2014), “Ethanol and Trade: An Analysis of Price Transmission in the US Market,” Energy Economics, 42, Issue C, 1-8. Zhang, Z., L. Lohr, C. Escalante, and M. Wetzstein (2009), “Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-fuels Market,” Energies, 2(2), 230-339. Zhao, J. and B.K. Goodwin (2011), “Volatility Spillovers in Agricultural Commodity Markets: An Application Involving Implied Volatilities from Options Markets,” Paper to the Agricultural & Applied Economics Association’s 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania.