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Multiple commodities in statistical microeconomics: Model and market

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  • Baaquie, Belal E.
  • Yu, Miao
  • Du, Xin

Abstract

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

Suggested Citation

  • Baaquie, Belal E. & Yu, Miao & Du, Xin, 2016. "Multiple commodities in statistical microeconomics: Model and market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 912-929.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:912-929
    DOI: 10.1016/j.physa.2016.06.102
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    References listed on IDEAS

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    1. Khrennikov, Andrei, 2008. "Quantum-like microeconomics: Statistical model of distribution of investments and production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5826-5843.
    2. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, September.
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    Cited by:

    1. Baaquie, Belal Ehsan, 2018. "Bonds with index-linked stochastic coupons in quantum finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 148-169.
    2. Baaquie, Belal Ehsan, 2019. "A statistical model of the firm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 392-411.
    3. Feng, Ling & Wang, Jieyu, 2023. "Random sources correlations and carbon futures pricing," International Review of Financial Analysis, Elsevier, vol. 86(C).

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