IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v38y2018i3p359-372.html
   My bibliography  Save this article

The weather premium in the U.S. corn market

Author

Listed:
  • Ziran Li
  • Dermot J. Hayes
  • Keri L. Jacobs

Abstract

We show that the weather premium, an anecdotal phenomenon in the U.S. corn futures market, can arise from a convex demand function. We further show that the magnitude of the weather premium depends on the carryout and expected yield at harvest. We use data from 1968 to 2015 to evaluate the accuracy of the December futures price as a forecast of the harvest price. A predictable component in the forecast error is consistent with the existence of a time‐varying weather premium. We demonstrate that a passive strategy of routinely shorting the corn December futures does not provide an attractive risk‐adjusted return.

Suggested Citation

  • Ziran Li & Dermot J. Hayes & Keri L. Jacobs, 2018. "The weather premium in the U.S. corn market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 359-372, March.
    • Handle: RePEc:wly:jfutmk:v:38:y:2018:i:3:p:359-372
    DOI: 10.1002/fut.21884
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.21884
    Download Restriction: no
    File URL: https://libkey.io/10.1002/fut.21884?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Angus Deaton & Guy Laroque, 1992. "On the Behaviour of Commodity Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(1), pages 1-23.
    2. 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..
    3. Bessembinder, Hendrik & Chan, Kalok, 1992. "Time-varying risk premia and forecastable returns in futures markets," Journal of Financial Economics, Elsevier, vol. 32(2), pages 169-193, October.
    4. Kilian, Lutz & Baumeister, Christiane, 2014. "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers 10162, C.E.P.R. Discussion Papers.
    5. J. Frank & P. Garcia, 2009. "Time-varying risk premium: further evidence in agricultural futures markets," Applied Economics, Taylor & Francis Journals, vol. 41(6), pages 715-725.
    6. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    7. 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.
    8. Nicole M. Aulerich & Scott H. Irwin & Philip Garcia, 2013. "Returns to individual traders in agricultural futures markets: skill or luck?," Applied Economics, Taylor & Francis Journals, vol. 45(25), pages 3650-3666, September.
    9. Jagannathan, Ravi, 1985. "An Investigation of Commodity Futures Prices Using the Consumption-based Intertemporal Capital Asset Pricing Model," Journal of Finance, American Finance Association, vol. 40(1), pages 175-191, March.
    10. Hartzmark, Michael L, 1991. "Luck versus Forecast Ability: Determinants of Trader Performance in Futures Markets," The Journal of Business, University of Chicago Press, vol. 64(1), pages 49-74, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Janzen, Joe, . "The Weather Risk Premium in New-Crop Corn Futures Prices," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 11(88).
    2. Bhattarai, Chandan & McKenzie, Andrew M. & Biram, Hunter D. & Durand-Morat, Alvaro, 2023. "Risk-Returns of forward contracting southern row crops with crop revenue insurance," 2023 Annual Meeting, July 23-25, Washington D.C. 335663, Agricultural and Applied Economics Association.
    3. Tianyang Zhang & Ziran Li, 2022. "Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 313-337, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Ziran, 2017. "Three essays on commodity markets," ISU General Staff Papers 201701010800006361, Iowa State University, Department of Economics.
    2. Acharya, Viral V. & Lochstoer, Lars A. & Ramadorai, Tarun, 2013. "Limits to arbitrage and hedging: Evidence from commodity markets," Journal of Financial Economics, Elsevier, vol. 109(2), pages 441-465.
    3. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    4. Sung Je Byun, 2017. "Speculation in Commodity Futures Markets, Inventories and the Price of Crude Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    5. Raushan Kumar, 2021. "Predicting Wheat Futures Prices in India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(1), pages 121-140, March.
    6. Kocagil, Ahmet E. & Topyan, Kudret, 1997. "An empirical note on demand for speculation and futures risk premium: A Kalman Filter application," Review of Financial Economics, Elsevier, vol. 6(1), pages 77-93.
    7. Baumeister, Christiane, 2021. "Measuring Market Expectations," CEPR Discussion Papers 16520, C.E.P.R. Discussion Papers.
    8. Nicole M. Moran & Scott H. Irwin & Philip Garcia, 2020. "Who Wins and Who Loses? Trader Returns and Risk Premiums in Agricultural Futures Markets," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(4), pages 611-652, December.
    9. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2013. "The Fundamentals of Commodity Futures Returns," Review of Finance, European Finance Association, vol. 17(1), pages 35-105.
    10. Cortazar, Gonzalo & Kovacevic, Ivo & Schwartz, Eduardo S., 2015. "Expected commodity returns and pricing models," Energy Economics, Elsevier, vol. 49(C), pages 60-71.
    11. Konstantinidi, Eirini & Skiadopoulos, George, 2011. "Are VIX futures prices predictable? An empirical investigation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 543-560, April.
    12. Valenti, Daniele & Manera, Matteo & Sbuelz, Alessandro, 2020. "Interpreting the oil risk premium: Do oil price shocks matter?," Energy Economics, Elsevier, vol. 91(C).
    13. Erkko Etula, 2013. "Broker-Dealer Risk Appetite and Commodity Returns," Journal of Financial Econometrics, Oxford University Press, vol. 11(3), pages 486-521, June.
    14. Hollstein, Fabian & Prokopczuk, Marcel & Tharann, Björn & Wese Simen, Chardin, 2021. "Predictability in commodity markets: Evidence from more than a century," Journal of Commodity Markets, Elsevier, vol. 24(C).
    15. 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.
    16. ap Gwilym, Rhys & Ebrahim, M. Shahid & El Alaoui, Abdelkader O. & Rahman, Hamid & Taamouti, Abderrahim, 2020. "Financial frictions and the futures pricing puzzle," Economic Modelling, Elsevier, vol. 87(C), pages 358-371.
    17. Symeonidis, Lazaros & Prokopczuk, Marcel & Brooks, Chris & Lazar, Emese, 2012. "Futures basis, inventory and commodity price volatility: An empirical analysis," Economic Modelling, Elsevier, vol. 29(6), pages 2651-2663.
    18. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    19. Kilian, Lutz & Baumeister, Christiane, 2014. "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers 10162, C.E.P.R. Discussion Papers.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jfutmk:v:38:y:2018:i:3:p:359-372. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.