[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/ags/joaaec/43790.html
   My bibliography  Save this article

Forecasting Basis Levels in the Soybean Complex: A Comparison of Time Series Methods

Author

Listed:
  • Sanders, Dwight R.
  • Manfredo, Mark R.
Abstract
A battery of time series methods are compared for forecasting basis levels in the soybean futures complex: soybeans, soybean meal, and soybean oil. Specifically, nearby basis forecasts are generated with exponential smoothing techniques, autoregression moving average (ARMA), and vector autoregression (VAR) models. The forecasts are compared to those of the 5-year average, year ago, and no change methods. Using the 5-year average as the benchmark method, the forecast evaluation results suggest that alternative naive techniques may produce better forecasts, and the improvement gained by time series modeling is relatively small. In this sample, there is little evidence that the basis has become systematically more difficult to forecast in recent years.

Suggested Citation

  • Sanders, Dwight R. & Manfredo, Mark R., 2006. "Forecasting Basis Levels in the Soybean Complex: A Comparison of Time Series Methods," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(3), pages 1-11, December.
    • Handle: RePEc:ags:joaaec:43790
    DOI: 10.22004/ag.econ.43790
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/43790/files/Sanders%20JAAE%20December%202006.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.43790?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kastens, Terry L. & Jones, Rodney D. & Schroeder, Ted C., 1998. "Futures-Based Price Forecasts For Agricultural Producers And Businesses," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(1), pages 1-14, July.
    2. Naik, Gopal & Leuthold, Raymond M., 1988. "Cash And Futures Price Relationships For Nonstorable Commodities: An Empirical Analysis Using A General Theory," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(2), pages 1-12, December.
    3. Spitze, R.G.F., 1983. "Series E, Agricultural Economics," Illinois Agricultural Economics Staff Paper 244634, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    4. Brorsen, B. Wade & Irwin, Scott H., 1996. "Improving The Relevance Of Research On Price Forecasting And Marketing Strategies," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 25(1), pages 1-8, April.
    5. 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.
    6. Kastens, Terry L. & Schroeder, Ted C. & Plain, Ronald L., 1998. "Evaluation Of Extension And Usda Price And Production Forecasts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(1), pages 1-18, July.
    7. Holt, Charles C., 2004. "Forecasting seasonals and trends by exponentially weighted moving averages," International Journal of Forecasting, Elsevier, vol. 20(1), pages 5-10.
    8. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    9. Jiang, Bingrong, 1997. "Corn and soybean basis behavior and forecasting: fundamental and alternative approaches," ISU General Staff Papers 1997010108000013213, Iowa State University, Department of Economics.
    10. Shi‐Miin Liu & B. Wade Brorsen & Charles M. Oellermann & Apul L. Farris, 1994. "Forecasting the nearby basis of live cattle," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 14(3), pages 259-273, May.
    11. Tomek, William G., 1993. "Dynamics of Price Changes: Implications for Agricultural Futures Markets," Staff Papers 121339, Cornell University, Department of Applied Economics and Management.
    12. Hayenga, Marvin L. & Jiang, Bingrong, 1997. "Corn and Soybean Basis Behavior and Forecasting: Fundamental and Alternative Approaches," Staff General Research Papers Archive 10400, Iowa State University, Department of Economics.
    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. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    2. Lee, Yoonsuk & Brorsen, B. Wade, 2012. "Impacts of Permanent and Transitory Shocks on Optimal Length of Moving Average to Predict Wheat Basis," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125001, Agricultural and Applied Economics Association.
    3. Welch, J. Mark & Mkrtchyan, Vardan & Power, Gabriel J., 2009. "Predicting the Corn Basis in the Texas Triangle Area," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 27(1-2), pages 1-15.
    4. Karen E. Lewis & Ira J. Altman & Mark R. Manfredo & Dwight R. Sanders, 2015. "Risk Premiums and Forward Basis: Evidence from the Soybean Oil Market," Agribusiness, John Wiley & Sons, Ltd., vol. 31(3), pages 388-398, June.
    5. Onel, Gulcan & Karali, Berna, 2014. "Relative Performance of Semi-Parametric Nonlinear Models in Forecasting Basis," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169795, Agricultural and Applied Economics Association.
    6. Mingming Liu & Dongmei Li, 2010. "An Analysis on Total Factor Productivity and Influencing Factors of Soybean in China," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 2(2), pages 158-158, May.
    7. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    8. Hatchett, Robert B. & Brorsen, B. Wade & Anderson, Kim B., 2010. "Optimal Length of Moving Average to Forecast Futures Basis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 35(1), pages 1-16.
    9. Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent shocks and forecasting with moving averages," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1213-1225, 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. Kastens, Terry L. & Dhuyvetter, Kevin C., 1999. "Post-Harvest Grain Storing And Hedging With Efficient Futures," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(2), pages 1-24, December.
    2. Sanders, Dwight R. & Manfredo, Mark R., 2003. "USDA Livestock Price Forecasts: A Comprehensive Evaluation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(2), pages 1-19, August.
    3. Tonsor, Glynn T. & Dhuyvetter, Kevin C. & Mintert, James R., 2004. "Improving Cattle Basis Forecasting," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(2), pages 1-14, August.
    4. Sanders, Dwight R. & Manfredo, Mark R., 2004. "Predicting Pork Supplies: An Application of Multiple Forecast Encompassing," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(3), pages 1-11, December.
    5. Evelyn V. Colino & Scott H. Irwin, 2010. "Outlook vs. Futures: Three Decades of Evidence in Hog and Cattle Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 1-15.
    6. Parcell, Joe L. & Schroeder, Ted C. & Dhuyvetter, Kevin C., 2000. "Factors Affecting Live Cattle Basis," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 32(3), pages 531-541, December.
    7. Renyuan Shao & Brian Roe, 2003. "The design and pricing of fixed‐ and moving‐window contracts: An application of Asian‐Basket option pricing methods to the hog‐finishing sector," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(11), pages 1047-1073, November.
    8. Onel, Gulcan & Karali, Berna, 2014. "Relative Performance of Semi-Parametric Nonlinear Models in Forecasting Basis," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169795, Agricultural and Applied Economics Association.
    9. Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
    10. Pär Österholm, 2005. "The Taylor Rule: A Spurious Regression?," Bulletin of Economic Research, Wiley Blackwell, vol. 57(3), pages 217-247, July.
    11. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    12. Korbinian Dress & Stefan Lessmann & Hans-Jorg von Mettenheim, 2017. "Residual Value Forecasting Using Asymmetric Cost Functions," Papers 1707.02736, arXiv.org.
    13. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    14. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    15. Paroissien, Emmanuel, 2020. "Forecasting bulk prices of Bordeaux wines using leading indicators," International Journal of Forecasting, Elsevier, vol. 36(2), pages 292-309.
    16. Rolando F. Peláez, 2015. "A recession‐and‐state forecasting model," Southern Economic Journal, John Wiley & Sons, vol. 81(4), pages 1025-1039, April.
    17. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    18. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
    19. repec:kap:iaecre:v:15:y:2009:i:4:p:470-482 is not listed on IDEAS
    20. Sanders, Dwight R. & Garcia, Philip & Manfredo, Mark R., 2008. "Information Content in Deferred Futures Prices: Live Cattle and Hogs," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(1), pages 1-12, April.
    21. Hyunseok Kim & GianCarlo Moschini, 2018. "The Dynamics of Supply: U.S. Corn and Soybeans in the Biofuel Era," Land Economics, University of Wisconsin Press, vol. 94(4), pages 593-613.

    More about this item

    Keywords

    Risk and Uncertainty;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

    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:ags:joaaec:43790. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/saeaaea.html .

    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.