doi: 10.3934/jdg.2020022

The sensitivity of commodity markets to exchange operations such as swing

1. 

Plekhanov Russian University of Economics, Moscow, Russian Federation

2. 

Institute of Problems of Transport of N. S. Solomenko of the Russian Academy of Sciences, Moscow, Russian Federation, Plekhanov Russian University of Economics, Moscow, Russian Federation

Received  November 2019 Revised  March 2020 Published  July 2020

A pricing model for the simplest commodity markets is considered. The model describes the behavior of the Order Book, consisting of orders from producers, consumers and speculators. The paper explores the external impact on this model in the form of large operations by new market participants, who at high speeds begin to push forward their orders, for example, first bids and then asks. Such strategies are called swings. This paper investigates a single cycle of one simple trading strategy of the swing type. Found a particular model case of pricing potentiality price relative to swing operation. An example is given, that shows that the simplest commodity markets with producers and consumers have the internal property that they are potentially vulnerable to external influences. The swinging of prices through large purchases and sales leads to systematic profits of the entrants at the expense of the traditional market participants.

Citation: Galina Bobrik, Petr Bobrik, Irina Sukhorukova. The sensitivity of commodity markets to exchange operations such as swing. Journal of Dynamics & Games, doi: 10.3934/jdg.2020022
References:
[1]

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P. P. Bobrik, G. I. Bobrik and I. V. Sukhorukova, The impact of transport costs on network price variation,in Proceedings of the 1st International Scientific Practical Conference "The Individual and Society in the Modern Geopolitical Environment" (ISMGE 2019), Atlantis Press, 2019, 97–100. doi: 10.2991/ismge-19.2019.20.  Google Scholar

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J. J. Murphy, Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications, New York Institute of Finance, NY, 1999. Google Scholar

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[12]

I. V. SukhorukovaG. I. Bobrik and V. A. Mushrub, Achieving academic leadership through teaching mathematical methods in economics and finance, Advances in Social Science, Education and Humanities Research, 217 (2018), 247-255.   Google Scholar

[13]

I. V. Sukhorukova and N. A. Chistiakova, Economic regulation and mathematical modeling of insurance product cost, Regional Science Inquiry, 2 (2018), 195-203.   Google Scholar

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show all references

References:
[1]

G. I. Bobrik and P. P. Bobrik, Determination of exchange trends by corner operations, Vestnic of The Plekhanov Russian University of Economics, 4 (2017), 67-73.   Google Scholar

[2]

G. I. Bobrik and P. P. Bobrik, Sensitivity of grid pricing, in IX Moscow International Conference on Operations Research (ORM-2018) Proceedings, vol. 2, Max Press, 2018, 243–246. Google Scholar

[3]

G. I. BobrikP. P. Bobrik and A. I. Iskorostinskii, Potentiality of local exchange pricing, Educational Resources and Technologies, 4 (2014), 18-21.   Google Scholar

[4]

G. I. Bobrik, P. P. Bobrik and I. V. Sukhorukova, Operation such as swing in exchange pricing model, in Information Technology and Mathematical Methods in Economics and Management (ITiMM-2019), Collection of Articles, Plekhanov Russian University of Economics, 2019, 18–21. Google Scholar

[5]

K. Bobrik and N. Popova, Analysis of processes communication structure for better mapping of parallel applications, RuSCDays 2016 Supercomputing, in Part of Communications in Computer and Information Science book series (CCIS), 687 (2016), 264-278.  doi: 10.1007/978-3-319-55669-7_21.  Google Scholar

[6]

P. P. Bobrik, Wave properties of the transport equilibrium search algorithm, in Proceedings of ORM2016, Moscow, October 17-22, 2016, Ed. FIZ IU RAS, 2016, 231–232. Google Scholar

[7]

P. P. Bobrik, G. I. Bobrik and I. V. Sukhorukova, The impact of transport costs on network price variation,in Proceedings of the 1st International Scientific Practical Conference "The Individual and Society in the Modern Geopolitical Environment" (ISMGE 2019), Atlantis Press, 2019, 97–100. doi: 10.2991/ismge-19.2019.20.  Google Scholar

[8]

W. Grandmill, Investing in Wheat, Soybean, Corn, Windsor Book, NY, 1990. Google Scholar

[9]

B. Knuteson, Celebrating Three Decades of Worldwide Stock Market Manipulation, preprint, arXiv: 1912.01708. doi: 10.2139/ssrn.3490879.  Google Scholar

[10]

J. J. Murphy, Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications, New York Institute of Finance, NY, 1999. Google Scholar

[11]

J. D. Schwager, A Complete Guide to the Futures Market: Technical Analysis, Trading Systems, Fundamental Analysis, Options, Spreads, and Trading Principles (Wiley Trading), 2nd edition, Kindle Edition, John Wiley & Sons Inc; Underlining edition, NY, 1984. doi: 10.1002/9781119209713.  Google Scholar

[12]

I. V. SukhorukovaG. I. Bobrik and V. A. Mushrub, Achieving academic leadership through teaching mathematical methods in economics and finance, Advances in Social Science, Education and Humanities Research, 217 (2018), 247-255.   Google Scholar

[13]

I. V. Sukhorukova and N. A. Chistiakova, Economic regulation and mathematical modeling of insurance product cost, Regional Science Inquiry, 2 (2018), 195-203.   Google Scholar

[14] A. A. VasinO. M. Grigorieva and I. A. Lesik, The problem of optimal development of the energy market of the transport system,in IX Moscow International Conference on Operations Research (ORM-2018) Proceedings, vol. 2, Max Press, 2018.   Google Scholar
Figure 1.  Impact of third player in the case of stable supply and demand intensities
Figure 2.  Impact of the exchange operations such as swings
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