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Do spot food commodity and oil prices predict futures prices?

Author

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  • Phillip A. Cartwright

    (PSB Paris School of Business)

  • Natalija Riabko

    (France AgriMer)

Abstract

Futures prices reflect the price that both the buyer and the seller agree will be the price of a commodity upon delivery. Therefore, these prices provide direct information about investor’s expectations about the future price of the commodity of interest. This purpose of this research is twofold. First, following earlier investigations, an effort is made to understand the extent to which the spot energy price contains information content in the current period useful for predicting the forward-looking variable. The working hypothesis is that both own-commodity spot prices and spot energy prices are significant predictors of future commodity prices at alternative leads (lags). Second, the research investigates the predictive accuracy and biasedness of futures prices predictions from reverse regressions using in-sample criteria as well as from the performance of the models based upon ex post forecasts generated by alternative time series models. The results indicate that in some cases spot own-commodity prices and spot oil prices are useful for predicting prices of futures contracts although the lead–lag relationships vary considerably as between commodities and markets considered as well as with respect to temporal aggregation. Further, the evidence suggests that unless there is specific interest in the EGARCH parameter estimates, GARCH models tend to perform at least as well as without the added complexity of EGARCH.

Suggested Citation

  • Phillip A. Cartwright & Natalija Riabko, 2019. "Do spot food commodity and oil prices predict futures prices?," Review of Quantitative Finance and Accounting, Springer, vol. 53(1), pages 153-194, July.
  • Handle: RePEc:kap:rqfnac:v:53:y:2019:i:1:d:10.1007_s11156-018-0746-1
    DOI: 10.1007/s11156-018-0746-1
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    1. Saghaian, Sayed H., 2010. "The Impact of the Oil Sector on Commodity Prices: Correlation or Causation?," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 42(3), pages 477-485, August.
    2. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-927, July.
    3. Kilian, Lutz & Vigfusson, Robert J., 2011. "Nonlinearities In The Oil Price–Output Relationship," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 337-363, November.
    4. Charles Engel & Kenneth D. West, 2005. "Exchange Rates and Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 113(3), pages 485-517, June.
    5. Liu, Shi-Miin & Brorsen, B Wade, 1995. "Maximum Likelihood Estimation of a Garch-Stable Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(3), pages 273-285, July-Sept.
    6. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.
    7. Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
    8. 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.
    9. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    10. Fung, Hung-Gay & Leung, Wai K & Xu, Xiaoqing Eleanor, 2003. "Information Flows between the U.S. and China Commodity Futures Trading," Review of Quantitative Finance and Accounting, Springer, vol. 21(3), pages 267-285, November.
    11. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    12. Robert F. Engle & Ta-Chung Liu, 1972. "Effects of Aggregation Over Time on Dynamic Characteristics of an Econometric Model," NBER Chapters, in: Econometric Models of Cyclical Behavior, Volumes 1 and 2, pages 673-737, National Bureau of Economic Research, Inc.
    13. Yu, Tun-Hsiang (Edward) & Bessler, David A. & Fuller, Stephen W., 2006. "Cointegration and Causality Analysis of World Vegetable Oil and Crude Oil Prices," 2006 Annual meeting, July 23-26, Long Beach, CA 21439, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Phillip A. Cartwright & Natalija Riabko, 2016. "Further evidence on the explanatory power of spot food and energy commodities market prices for futures prices," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 579-605, October.
    15. Jungho Baek & Ji-Yong Seo, 2015. "A Study on Unobserved Structural Innovations of Oil Price: Evidence from Global Stock, Bond, Foreign Exchange, and Energy Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 1-17.
    16. Alghalith, Moawia, 2010. "The interaction between food prices and oil prices," Energy Economics, Elsevier, vol. 32(6), pages 1520-1522, November.
    17. Fengping Tian & Ke Yang & Langnan Chen, 2017. "Realized Volatility Forecasting of Agricultural Commodity Futures Using Long Memory and Regime Switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(4), pages 421-430, July.
    18. Smith, Kenneth L & Bracker, Kevin, 2003. "Forecasting Changes in Copper Futures Volatility with GARCH Models Using an Iterated Algorithm," Review of Quantitative Finance and Accounting, Springer, vol. 20(3), pages 245-265, May.
    19. Gohin, A. & Chantret, F., 2010. "The long-run impact of energy prices on world agricultural markets: The role of macro-economic linkages," Energy Policy, Elsevier, vol. 38(1), pages 333-339, January.
    20. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    21. Cartwright, Phillip A & Lee, Cheng F, 1987. "Time Aggregation and the Estimation of the Market Model: Empirical Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 131-143, January.
    22. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    23. Mutuc, Maria & Pan, Suwen & Hudson, Darren, 2011. "Response of Cotton to Oil Price Shocks," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 12(2).
    24. Christopher F Baum, 2006. "An Introduction to Modern Econometrics using Stata," Stata Press books, StataCorp LP, number imeus, March.
    25. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    27. Cooke, Bryce & Robles, Miguel, 2009. "Recent food prices movements: A time series analysis," IFPRI discussion papers 942, International Food Policy Research Institute (IFPRI).
    28. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    29. 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.
    30. Campiche, Jody L. & Bryant, Henry L. & Richardson, James W. & Outlaw, Joe L., 2007. "Examining the Evolving Correspondence Between Petroleum Prices and Agricultural Commodity Prices," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon 9881, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    31. Mr. David A Reichsfeld & Mr. Shaun K. Roache, 2011. "Do Commodity Futures Help Forecast Spot Prices?," IMF Working Papers 2011/254, International Monetary Fund.
    32. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
    33. Bopp, Anthony E. & Lady, George M., 1991. "A comparison of petroleum futures versus spot prices as predictors of prices in the future," Energy Economics, Elsevier, vol. 13(4), pages 274-282, October.
    34. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    35. James Wilkinson & Atanu Ghoshray, 2013. "A Cointegration Analysis of Oil and Agricultural Prices," Review of Market Integration, India Development Foundation, vol. 5(3), pages 249-270, December.
    36. Ying Jiang & Shamim Ahmed & Xiaoquan Liu, 2017. "Volatility forecasting in the Chinese commodity futures market with intraday data," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 1123-1173, May.
    37. Esmaeili, Abdoulkarim & Shokoohi, Zainab, 2011. "Assessing the effect of oil price on world food prices: Application of principal component analysis," Energy Policy, Elsevier, vol. 39(2), pages 1022-1025, February.
    38. Zhang, Qiang & Reed, Michael R., 2008. "Examining the Impact of the World Crude Oil Price on China's Agricultural Commodity Prices: The Case of Corn, Soybean, and Pork," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6797, Southern Agricultural Economics Association.
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    More about this item

    Keywords

    Commodities prices; Oil; Causality; Temporal aggregation; Predictive validity;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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