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A historical perspective of the informational content of commodity futures

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  • Fernandez, Viviana

Abstract

This article extends Chinn and Coibion (2014)'s work--Journal of Futures Markets 34-- on predictive content of commodity futures by considering a more comprehensive database and a longer time span, ranging from 25 to 65 years, and by presenting two extensions: multi-equation estimation of risk premiums and testing for the theory of storage.

Suggested Citation

  • Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
  • Handle: RePEc:eee:jrpoli:v:51:y:2017:i:c:p:135-150
    DOI: 10.1016/j.resourpol.2016.12.002
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    References listed on IDEAS

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    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. Chang, Chun-Ping & Lee, Chien-Chiang, 2015. "Do oil spot and futures prices move together?," Energy Economics, Elsevier, vol. 50(C), pages 379-390.
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    7. Chen, Yu-Lun & Chang, Ya-Kai, 2015. "Investor structure and the informational efficiency of commodity futures prices," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 358-367.
    8. 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..
    9. 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.
    10. Fernandez, Viviana, 2015. "Commodity price excess co-movement from a historical perspective: 1900–2010," Energy Economics, Elsevier, vol. 49(C), pages 698-710.
    11. 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.).
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    13. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.
    14. 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.
    15. 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.
    16. Han, Yufeng & Hu, Ting & Yang, Jian, 2016. "Are there exploitable trends in commodity futures prices?," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 214-234.
    17. 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.
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    19. Sergey V. Chernenko, 2004. "The information content of forward and futures prices: market expectations and the price of risk," International Finance Discussion Papers 808, Board of Governors of the Federal Reserve System (U.S.).
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    22. Ghoddusi, Hamed, 2016. "Integration of physical and futures prices in the US natural gas market," Energy Economics, Elsevier, vol. 56(C), pages 229-238.
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    Cited by:

    1. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2021. "Common factors and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 74(C).
    2. Fernandez, Viviana, 2020. "The predictive power of convenience yields," Resources Policy, Elsevier, vol. 65(C).
    3. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    4. Jebabli, Ikram & Roubaud, David, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Economic Modelling, Elsevier, vol. 70(C), pages 97-114.
    5. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    6. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
    7. Clark, Andrew, 2022. "Causality in the aluminum market," Journal of Commodity Markets, Elsevier, vol. 27(C).

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    More about this item

    Keywords

    Q02; L72; C13; Premium; Theory of storage; Seemingly unrelated equations;
    All these keywords.

    JEL classification:

    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • 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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