Money, finances and credit

Impact of expectations on grain futures price formation

Economic Annals-XXI

Economic Annals-ХХI: Volume 178, Issue 7-8, Pages: 123-133

Citation information:
Shyian, D., Sakhno, I., & Kramarenko, K. (2019). Impact of expectations on grain futures price formation. Economic Annals-XXI, 178(7-8), 123-133. doi: https://doi.org/10.21003/ea.V178-11

View Full-TextDownload PDF

Dmytro Shyian
D.Sc. (Economics),
Professor,
Simon Kuznets Kharkiv National University of Economics
9-A Nauky Ave., Kharkiv, 61166, Ukraine
dmytro.shyian@hneu.net
ORCID ID: http://orcid.org/0000-0002-0815-267X

Iryna Sakhno
PhD (Economics),
Associate Professor,
National Academy of the National Guard of Ukraine
3 Zakhysnykiv Ukrainy Sq., Kharkiv, 61000, Ukraine
sakhno.ir@gmail.com
ORCID ID: http://orcid.org/0000-0001-6795-0535

Kateryna Kramarenko
PhD (Economics),
Associate Professor,
National Academy of the National Guard of Ukraine
3 Zakhysnykiv Ukrainy Sq., Kharkiv, 61001, Ukraine
km.kramarenko@gmail.com
ORCID ID: http://orcid.org/0000-0001-9601-2003

Impact of expectations on grain futures price formation

Abstract. Introduction. The problems of estimating and forecasting the price of grain futures in the US market are discussed in the paper. It is emphasized that the expectation factor in such markets plays one of the leading roles. It is noted that it is the grain market that is significantly influenced by expectations due to the forecast of future harvests in different parts of the world.

The purpose of the study is to analyze the process of shaping the dynamics of future prices for wheat and corn (maize) under the influence of the expectations factor in the United States in 2009-2019.

Methods. The authors’ own technique to analyze the dynamics of future price changes through the transformation of primary data, using the cumulative sliding expectations method, is proposed.

Results. Analysing the data on changes in the prices of futures for grain, the periods of their sharpest increase in wheat and the most significant fall in corn have been identified. Comparison of the absolute data of the dynamic series and the values of the total sliding expectations made it possible to state that the maximum and minimum values of the total sliding expectations are related to the maximum values of future prices. Analysing the fastest rise in prices of wheat futures and the values of total sliding expectations, the latent fluctuations in expectations change of economic agents have been revealed.

Conclusion. It is concluded that the proposed transformation method of the primary data on the dynamic series of changes in grain futures prices reveals hidden patterns, which in turn improves forecasting of future events in the market.

Keywords: Time Series; Total Sliding Expectations; Commodity Markets; Futures; Price of Goods; Grain Futures; Corn Futures; USA

JEL Classification: G13; G14; Q11

Acknowledgements and Funding: The authors received no direct funding for this research.

Contribution: The authors contributed equally to this work.

DOI: https://doi.org/10.21003/ea.V178-11

References

  1. Smith, A. (1776, 2007). An Inquiry into the Nature and Causes of the Wealth of Nations. S. M. Soares (Ed.). Lausanne: MetaLibri Digital Library.
    Retrieved from https://www.ibiblio.org/ml/libri/s/SmithA_WealthNations_p.pdf
  2. Marshall, A. (2013). Principles of Economics (8th edition). London: Palgrave Macmillan.
    Retrieved from http://www.library.fa.ru/files/Marshall-Principles.pdf
  3. Keynes, J. M. (1936). The General Theory of Employment, Interest and Money. Macmillan.
    Retrieved from http://cas2.umkc.edu/economics/people/facultypages/kregel/courses/econ645/winter2011/generaltheory.pdf
  4. Peltzman, S. (2000). Prices Rise Faster than They Fall. Journal of Political Economy, 108(3), 466-502.
    doi: https://doi.org/10.1086/262126
  5. Lobell, D. B., Cassman, K. G., & Field, Ch. B. (2009). Crop Yield Gaps: Their Importance, Magnitudes, and Causes. Annual Review of Environment and Resources, 34, 179-204.
    doi: https://doi.org/10.1146/annurev.environ.041008.093740
  6. Lobell, D. B., & Field, Ch. B. (2007). Global scale climate-crop yield relationships and the impacts of recent warming. Environmental Research Letters, 2(1), 1-7.
    doi: https://doi.org/10.1088/1748-9326/2/1/014002
  7. Headey, D., & Fan, Sh. (2008). Anatomy of a crisis: The causes and consequences of surging food prices. Agricultural Economics, 39(1), 375-391.
    doi: https://doi.org/10.1111/j.1574-0862.2008.00345.x
  8. Anderson, K., & Nelgen, S. (2010) Trade Barrier Volatility and Agricultural Price Stabilization. World Development, 40(1), 36-48.
    doi: https://doi.org/10.1016/j.worlddev.2011.05.018
  9. McPhail, L. L., Du, X., & Muhammad, A. (2012). Disentangling Corn Price Volatility: The Role of Global Demand, Speculation, and Energy. Journal of Agricultural and Applied Economics, 44(3), 401-410.
    doi: https://doi.org/10.1017/S107407080000050X
  10. Xu, Y., Pan, F., Wang, Ch., & Li, J. (2019). Dynamic Price Discovery Process of Chinese Agricultural Futures Markets: An Empirical Study Based on the Rolling Window Approach. Journal of Agricultural and Applied Economics, 51(4), 664-681.
    doi: https://doi.org/10.1017/aae.2019.23
  11. Boyer, Ch. N., Larson, J. A., Roberts, R. K., McClure, M. A., Tyler, D. D., & Smith, S. A. (2015). Effects of recent corn and energy prices on irrigation investment in the humid climate of tennessee. Journal of Agricultural and Applied Economics, 47(1), 105-122.
    doi: https://doi.org/10.1017/aae.2014.4
  12. Luckstead, J., & Devadoss, S. (2019). Implications of Commodity Programs and Crop Insurance Policies for Wheat Producers. Journal of Agricultural and Applied Economics, 51(2), 267-285.
    doi: https://doi.org/10.1017/aae.2018.32
  13. Amrouk, El M., Heckelei, Th., & Grosche, S.-C. (2019). International Interdependence between Cash Crop and Staple Food Futures Price Indices: A Dynamic Assessment. Journal of Agricultural and Applied Economics, 51(3), 450-471.
    doi: https://doi.org/10.1017/aae.2019.12
  14. Grosche, S.-C., & Heckelei, Th. (2016). Directional Volatility Spillovers between Agricultural, Crude Oil, Real Estate, and Other Financial Markets. In M. Kalkuhl, J. von Braun, & M. Torero (Eds.), Food Price Volatility and Its Implications for Food Security and Policy (pp. 183-205). Springer Open.
    doi: https://doi.org/10.1007/978-3-319-28201-5_9
  15. Koyck, L. M. (1954). Distributed Lags and Investment Analysis. Contributions to Economic Analysis. Amsterdam: North-Holland Publishing Company.
    doi: https://doi.org/10.1017/S1373971900069778
  16. Gál, T., Nagy, L., Dávid, L., Vasa, L., & Balogh, P. (2013). Technology planning system as a decision support tool for dairy farms in Hungary. Acta Polytechnica Hungarica, 10(8), 231-244.
    Retrieved from https://www.uni-obuda.hu/journal/Gal_Nagy_David_Vasa_Balogh_46.pdf
  17. Muth, J. F. (1961). Rational Expectations and the Theory of Price Movements. Econometrica, 29(3), 315-335.
    doi: https://doi.org/10.2307/1909635
  18. Simon, H. A. (1958). The Role of Expectations in an Adaptive or Behavioristic Model. In M. J. Bowman (Eds.), Expectations, Uncertainty and Business Behavior (pp. 49-58). New York: Social Sciences Research Council.
  19. Phillips, A. W. (1958). The Relation between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861-1957. Economica, 25(100), 283-299.
    doi: https://doi.org/10.2307/2550759
  20. Lucas, E. R. Jr. (1976). Econometric Policy Evaluation: A Critique. Carnegie-Rochester Conference Series on Public Policy, 1, 19-46.
    doi: https://doi.org/10.1016/S0167-2231(76)80003-6
  21. Kendall, M. G., & Hill, A. B. (1953). The Analysis of Economic Time Series: Part 1. Prices. Journal of Royal Statistical Society. Series A (General), 116(1), 11-34.
    doi: https://doi.org/10.2307/2980947
  22. Ferrell, A. (2003). If We Understand the Mechanisms, Why Don’t We Understand Their Output? Harvard Law and Economics, Discussion Paper No. 414. Harvard Law School. Cambridge, MA.
    doi: https://doi.org/10.2139/ssrn.393683
  23. Shyian, D. V. (2011). Impact of expectations on the mechanism of action of the economic cycle. Ekonomika i prohnozuvannia (Economics and Forecasting), 2, 40-52 (in Ukr.).
  24. Investing.com (2019). Real-time futures quotes.
    Retrieved from https://ru.investing.com/commodities/real-time-futures

Received 29.07.2019
Received in revised form 27.08.2019
Accepted 29.08.2019
Available online 30.09.2019

View Full-TextDownload PDF
In, , , , , , ,

More Papers