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Time-varying efficiency in food and energy markets: Evidence and implications

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  • Ikram Jebabli

    (CleRMa - Clermont Recherche Management - ESC Clermont-Ferrand - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA [2017-2020] - Université Clermont Auvergne [2017-2020])

  • David Roubaud

    (MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier)

Abstract

This paper analyses weak-form efficiency in daily spot and futures prices in the food and energy markets, given the simultaneous volatilities characterising prices in both markets. To determine the structural breaks and efficiency changes over time, we use the time-varying rolling Hurst exponent and threshold vector error correction models. Our main findings indicate that all of the studied commodities exhibit long-term efficiency and short-term inefficiencies that can be explained by global economic conditions: the 2008 global financial crisis, financialisation of commodities markets, and fluctuations in crude oil prices. Time-varying optimal weights minimising the portfolio risk show different patterns between food and crude oil. In terms of hedging effectiveness, food futures are better than crude oil futures. Therefore, optimal portfolios risk hedging requires an adequate rebalancing between spot and futures prices depending on markets conditions and the type of commodities considered. Investigation of the semi-strong efficiency form of these markets through the consideration of intra-day prices could constitute a future extension of the present work.
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Suggested Citation

  • Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    • Handle: RePEc:hal:journl:hal-02330557
    DOI: 10.1016/j.econmod.2017.10.013
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    1. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    2. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    3. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Energy Economics, Elsevier, vol. 40(C), pages 832-844.
    4. Rui Fan & Haiqi Li & Sung Y. Park, 2016. "Estimation and Hedging Effectiveness of Time‐Varying Hedge Ratio: Nonparametric Approaches," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(10), pages 968-991, October.
    5. Chang, Chun-Ping & Lee, Chien-Chiang, 2015. "Do oil spot and futures prices move together?," Energy Economics, Elsevier, vol. 50(C), pages 379-390.
    6. Algieri, Bernardina, 2014. "The influence of biofuels, economic and financial factors on daily returns of commodity futures prices," Energy Policy, Elsevier, vol. 69(C), pages 227-247.
    7. Jian Yang & Titus Awokuse, 2003. "Asset storability and hedging effectiveness in commodity futures markets," Applied Economics Letters, Taylor & Francis Journals, vol. 10(8), pages 487-491.
    8. Russ Wermers, 2000. "Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses," Journal of Finance, American Finance Association, vol. 55(4), pages 1655-1703, August.
    9. He, Ling-Yun & Qian, Wen-Bin, 2012. "A Monte Carlo simulation to the performance of the R/S and V/S methods—Statistical revisit and real world application," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(14), pages 3770-3782.
    10. Nicole M. Aulerich & Raymond P. H. Fishe & Jeffrey H. Harris, 2011. "Why do expiring futures and cash prices diverge for grain markets?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(6), pages 503-533, June.
    11. Hansen, Bruce E, 1999. "Testing for Linearity," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 551-576, December.
    12. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    13. repec:cii:cepiie:2014-q4-140-60 is not listed on IDEAS
    14. Walid Mensi & Makram Beljid & Shunsuke Managi, 2014. "Structural breaks and the time-varying levels of weak-form efficiency in crude oil markets: Evidence from the Hurst exponent and Shannon entropy methods," International Economics, CEPII research center, issue 140, pages 89-106.
    15. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    16. Barunik, Jozef & Kristoufek, Ladislav, 2010. "On Hurst exponent estimation under heavy-tailed distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3844-3855.
    17. Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
    18. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2011. "Crude oil hedging strategies using dynamic multivariate GARCH," Energy Economics, Elsevier, vol. 33(5), pages 912-923, September.
    19. Bampinas, Georgios & Panagiotidis, Theodore, 2016. "Hedging inflation with individual US stocks: A long-run portfolio analysis," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 374-392.
    20. Ruan, Qingsong & Huang, Ying & Jiang, Wei, 2016. "The exceedance and cross-correlations between the gold spot and futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 139-151.
    21. Chiara Pederzoli & Costanza Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: New evidence across the financial crisis," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0040, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    22. Sensoy, Ahmet & Hacihasanoglu, Erk & Nguyen, Duc Khuong, 2015. "Dynamic convergence of commodity futures: Not all types of commodities are alike," Resources Policy, Elsevier, vol. 44(C), pages 150-160.
    23. Andriosopoulos, Kostas & Nomikos, Nikos, 2014. "Performance replication of the Spot Energy Index with optimal equity portfolio selection: Evidence from the UK, US and Brazilian markets," European Journal of Operational Research, Elsevier, vol. 234(2), pages 571-582.
    24. Kristoufek, Ladislav & Vosvrda, Miloslav, 2013. "Measuring capital market efficiency: Global and local correlations structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 184-193.
    25. Bruce Hansen, 1999. "Testing for Linearity," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 551-576, December.
    26. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    27. Elie Bouri & Imad Kachacha & Donald Lien & David Roubaud, 2017. "Short- and long-run causality across the implied volatility of crude oil and agricultural commodities," Economics Bulletin, AccessEcon, vol. 37(2).
    28. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    29. Mellios, Constantin & Six, Pierre & Lai, Anh Ngoc, 2016. "Dynamic speculation and hedging in commodity futures markets with a stochastic convenience yield," European Journal of Operational Research, Elsevier, vol. 250(2), pages 493-504.
    30. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    31. Rodriguez, E. & Aguilar-Cornejo, M. & Femat, R. & Alvarez-Ramirez, J., 2014. "US stock market efficiency over weekly, monthly, quarterly and yearly time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 554-564.
    32. Lardic, Sandrine & Mignon, Valerie, 2006. "The impact of oil prices on GDP in European countries: An empirical investigation based on asymmetric cointegration," Energy Policy, Elsevier, vol. 34(18), pages 3910-3915, December.
    33. Menzie D. Chinn & Olivier Coibion, 2014. "The Predictive Content of Commodity Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(7), pages 607-636, July.
    34. Weron, Rafał, 2002. "Estimating long-range dependence: finite sample properties and confidence intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 285-299.
    35. Lo, Ming Chien & Zivot, Eric, 2001. "Threshold Cointegration And Nonlinear Adjustment To The Law Of One Price," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 533-576, September.
    36. Martin Martens & Paul Kofman & Ton C. F. Vorst, 1998. "A threshold error-correction model for intraday futures and index returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 245-263.
    37. Zhang, Bing & Li, Xiao-Ming & He, Fei, 2014. "Testing the evolution of crude oil market efficiency: Data have the conn," Energy Policy, Elsevier, vol. 68(C), pages 39-52.
    38. Chen, Pei-Fen & Lee, Chien-Chiang & Zeng, Jhih-Hong, 2014. "The relationship between spot and futures oil prices: Do structural breaks matter?," Energy Economics, Elsevier, vol. 43(C), pages 206-217.
    39. 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.
    40. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis And The Global Financial Crisis: Scaling, Investment Horizons And Liquidity," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-13.
    41. Liyan Han & Ziying Li & Libo Yin, 2017. "The effects of investor attention on commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(10), pages 1031-1049, October.
    42. Seo, Byeongseon, 2003. "Nonlinear mean reversion in the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2243-2265, September.
    43. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    44. Jinghong Shu & Jin E. Zhang, 2012. "Causality in the VIX futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(1), pages 24-46, January.
    45. Yu-Lun Chen & Yin-Feng Gau & Wen-Ju Liao, 2016. "Trading activities and price discovery in foreign currency futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 793-818, May.
    46. Tokic, Damir, 2015. "The 2014 oil bust: Causes and consequences," Energy Policy, Elsevier, vol. 85(C), pages 162-169.
    47. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    48. Nicholas Kaldor, 1939. "Speculation and Economic Stability," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 7(1), pages 1-27.
    49. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    50. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    51. 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.
    52. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    53. Tokic, Damir, 2010. "The 2008 oil bubble: Causes and consequences," Energy Policy, Elsevier, vol. 38(10), pages 6009-6015, October.
    54. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    55. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross‐Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    56. Robert J. Myers, 1991. "Estimating time‐varying optimal hedge ratios on futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(1), pages 39-53, February.
    57. 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.
    58. Jawadi, Fredj & Ftiti, Zied & Hdia, Mouna, 2017. "Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach," Economic Modelling, Elsevier, vol. 64(C), pages 567-588.
    59. Lardic, Sandrine & Mignon, Valérie, 2008. "Oil prices and economic activity: An asymmetric cointegration approach," Energy Economics, Elsevier, vol. 30(3), pages 847-855, May.
    60. 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.
    61. Russ Wermers, 2000. "Mutual Fund Performance: An Empirical Decomposition into Stock‐Picking Talent, Style, Transactions Costs, and Expenses," Journal of Finance, American Finance Association, vol. 55(4), pages 1655-1695, August.
    62. Chiu, Fan-Ping & Hsu, Chia-Sheng & Ho, Alan & Chen, Chi-Chung, 2016. "Modeling the price relationships between crude oil, energy crops and biofuels," Energy, Elsevier, vol. 109(C), pages 845-857.
    63. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    64. Jeffrey A. Busse & Amit Goyal & Sunil Wahal, 2010. "Performance and Persistence in Institutional Investment Management," Journal of Finance, American Finance Association, vol. 65(2), pages 765-790, April.
    65. repec:cii:cepiei:2014-q4-140-6 is not listed on IDEAS
    66. Andrew McKenzie & Matthew Holt, 2002. "Market efficiency in agricultural futures markets," Applied Economics, Taylor & Francis Journals, vol. 34(12), pages 1519-1532.
    67. Cajueiro, Daniel O & Tabak, Benjamin M, 2004. "The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 521-537.
    68. François Lescaroux & Valérie Mignon, 2008. "On the Influence of Oil Prices on Economic Activity and Other Macroeconomic and Financial Variables," Working Papers 2008-05, CEPII research center.
    69. C. Pederzoli & C. Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: new evidence across the financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(24), pages 1853-1863, December.
    70. 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(4), pages 535-551, December.
    71. Seo, Byeongseon, 2003. "Nonlinear mean reversion in the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11), pages 2243-2265.
    72. Olson, Eric & J. Vivian, Andrew & Wohar, Mark E., 2014. "The relationship between energy and equity markets: Evidence from volatility impulse response functions," Energy Economics, Elsevier, vol. 43(C), pages 297-305.
    73. Manolis G. Kavussanos & Nikos K. Nomikos, 2000. "Futures hedging when the structure of the underlying asset changes: The case of the BIFFEX contract," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(8), pages 775-801, September.
    74. Zhang, Bing, 2013. "Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test," Energy Economics, Elsevier, vol. 40(C), pages 875-881.
    75. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    76. Wang, Yudong & Wu, Chongfeng, 2012. "Long memory in energy futures markets: Further evidence," Resources Policy, Elsevier, vol. 37(3), pages 261-272.
    77. Zhong, Maosen & Darrat, Ali F. & Otero, Rafael, 2004. "Price discovery and volatility spillovers in index futures markets: Some evidence from Mexico," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 3037-3054, December.
    78. Ching-Chun Wei & Shu-Min Chen, 2016. "Examining the Relationship of Crude Oil Future Price Return and Agricultural Future Price Return in US," International Journal of Energy Economics and Policy, Econjournals, vol. 6(1), pages 58-64.
    79. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    80. 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.
    81. 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.
    82. François Lescaroux & Valérie Mignon, 2008. "On the influence of oil prices on economic activity and other macroeconomic and financial variables ," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 32(4), pages 343-380, December.
    83. Cajueiro, Daniel O. & Tabak, Benjamin M., 2004. "Evidence of long range dependence in Asian equity markets: the role of liquidity and market restrictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 656-664.
    84. Go, You-How & Lau, Wee-Yeap, 2017. "Investor demand, market efficiency and spot-futures relation: Further evidence from crude palm oil," Resources Policy, Elsevier, vol. 53(C), pages 135-146.
    85. Khediri, Karim Ben & Charfeddine, Lanouar, 2015. "Evolving efficiency of spot and futures energy markets: A rolling sample approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 6(C), pages 67-79.
    86. Beckmann, Joscha & Belke, Ansgar & Czudaj, Robert, 2014. "Regime-dependent adjustment in energy spot and futures markets," Economic Modelling, Elsevier, vol. 40(C), pages 400-409.
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    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

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