How market structure drives commodity prices

Li, Bin, Michael Wong, K. Y., Chan, Amos H.M., So, Tsz Yan, Heimonen, Hermanni, Wei, Junyi and Saad, David (2017). How market structure drives commodity prices. Journal of Statistical Mechanics: Theory and Experiment, 2017 (11),


We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the analysis, akin to mean-field parameters in statistical mechanics. When resources are scarce prices rise sharply below a turning point that marks the disappearance of excess producers. To compare the model with real empirical data, we study the relationship between commodity prices and stock-to-use ratios in a range of commodities such as agricultural products and metals. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities.

Publication DOI:
Divisions: Engineering & Applied Sciences > Systems analytics research institute (SARI)
Engineering & Applied Sciences > Mathematics
Additional Information: This is an author-created, un-copyedited version of an article accepted for publication/published in Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/1742-5468/aa933a. Funding: Research Grants Council of Hong Kong (grant numbers 604512, 605813 and 16322616) and the Leverhulme Trust RPG-2013-48.
Uncontrolled Keywords: agent-based models,graphical games,models of financial markets,socio-economic networks,Statistical and Nonlinear Physics,Statistics and Probability,Statistics, Probability and Uncertainty
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2017-11-29
Authors: Li, Bin
Michael Wong, K. Y.
Chan, Amos H.M.
So, Tsz Yan
Heimonen, Hermanni
Wei, Junyi
Saad, David ( 0000-0001-9821-2623)



Version: Accepted Version

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