Impact of expectations on grain futures price formation

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


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

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