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The predictive power of convenience yields

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  • Fernandez, Viviana

Abstract

A convenience yield or benefit associated with holding a physical commodity reflects the market's expectations about its future availability. This article explores the in- and out-of-sample predictive power of convenience yields with respect to future spot prices of five mineral commodities— aluminum, copper, lead, nickel, and zinc— for the period of 1983–2017. To that end, alternative measures of convenience yields are considered. The in-sample results show that convenience yields may explain the evolution of future spot prices at short-time horizons of 1, 3, and 6 months, while interest rates and nominal exchange rates may be more relevant at a 12-month horizon. By contrast out-of-sample forecasts show that convenience yields and the de-trended real oil price may have more predictive power with respect to future spot prices than interest and exchange rates within 1–12 months. In addition, this article offers new evidence on the informational content of convenience yields of mineral commodities and oil with respect to the business cycles of Australia, Canada, China, Japan, and the United States, among others.

Suggested Citation

  • Fernandez, Viviana, 2020. "The predictive power of convenience yields," Resources Policy, Elsevier, vol. 65(C).
  • Handle: RePEc:eee:jrpoli:v:65:y:2020:i:c:s0301420719305252
    DOI: 10.1016/j.resourpol.2019.101532
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    as
    1. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    2. Nahid Movassagh & Bagher Modjtahedi, 2005. "Bias and backwardation in natural gas futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(3), pages 281-308, March.
    3. Oya Celasun & Mr. Lev Ratnovski & Miss Roxana Mihet, 2012. "Commodity Prices and Inflation Expectations in the United States," IMF Working Papers 2012/089, International Monetary Fund.
    4. Jason West, 2012. "Convenience Yields in Bulk Commodities: The Case of Thermal Coal," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 6(4), pages 33-44.
    5. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    6. Longstaff, Francis A, 1995. "How Much Can Marketability Affect Security Values?," Journal of Finance, American Finance Association, vol. 50(5), pages 1767-1774, December.
    7. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    8. 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.
    9. Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
    10. Clinton Watkins & Michael McAleer, 2003. "Pricing of Non-ferrous Metals Futures on the London Metal Exchange," CIRJE F-Series CIRJE-F-213, CIRJE, Faculty of Economics, University of Tokyo.
    11. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    12. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    13. 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.
    14. James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
    15. Nikolaos T. Milonas & Stavros B. Thomadakis, 1997. "Convenience yields as call options: An empirical analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(1), pages 1-15, February.
    16. Richard Heaney, 2002. "Approximation for convenience yield in commodity futures pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(10), pages 1005-1017, October.
    17. Fischer, Stanley, 1978. "Call Option Pricing when the Exercise Price Is Uncertain, and the Valuation of Index Bonds," Journal of Finance, American Finance Association, vol. 33(1), pages 169-176, March.
    18. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    19. Trevor A. Reeve & Robert J. Vigfusson, 2011. "Evaluating the forecasting performance of commodity futures prices," International Finance Discussion Papers 1025, Board of Governors of the Federal Reserve System (U.S.).
    20. Stepanek, Christian & Walter, Matthias & Rathgeber, Andreas, 2013. "Is the convenience yield a good indicator of a commodity's supply risk?," Resources Policy, Elsevier, vol. 38(3), pages 395-405.
    21. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    22. Geman, Hélyette & Smith, William O., 2013. "Theory of storage, inventory and volatility in the LME base metals," Resources Policy, Elsevier, vol. 38(1), pages 18-28.
    23. Modjtahedi, Bagher & Movassagh, Nahid, 2005. "Natural-gas futures: Bias, predictive performance, and the theory of storage," Energy Economics, Elsevier, vol. 27(4), pages 617-637, July.
    24. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    25. Yuewen Xiao & David B. Colwell & Ramaprasad Bhar, 2015. "Risk Premium in Electricity Prices: Evidence from the PJM Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(8), pages 776-793, August.
    26. Engelbert J. Dockner & Zehra Eksi & Margarethe Rammerstorfer, 2015. "A Convenience Yield Approximation Model for Mean‐Reverting Commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(7), pages 625-654, July.
    27. Frederick T. Furlong & Robert Ingenito, 1996. "Commodity prices and inflation," Economic Review, Federal Reserve Bank of San Francisco, pages 27-47.
    28. Chow, Ying-Foon & McAleer, Michael & Sequeira, John M, 2000. "Pricing of Forward and Futures Contracts," Journal of Economic Surveys, Wiley Blackwell, vol. 14(2), pages 215-253, April.
    29. Ying‐Foon Chow & Michael McAleer & John Sequeira, 2000. "Pricing of Forward and Futures Contracts," Journal of Economic Surveys, Wiley Blackwell, vol. 14(2), pages 215-253, April.
    30. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2015. "Convenience yield and inventory accessibility: Impact of regional market conditions," Resources Policy, Elsevier, vol. 44(C), pages 1-11.
    31. Robert Heinkel & Maureen E. Howe & John S. Hughes, 1990. "Commodity convenience yields as an option profit," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 10(5), pages 519-533, October.
    32. Nikolay Gospodinov & Serena Ng, 2013. "Commodity Prices, Convenience Yields, and Inflation," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 206-219, March.
    33. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.
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    More about this item

    Keywords

    Theory of storage; Interest-adjusted basis; Convenience yield; Oil price;
    All these keywords.

    JEL classification:

    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • L72 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Other Nonrenewable Resources
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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