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Qualitative and quantitative combined nonlinear dynamics model and its application in analysis of price, supply–demand ratio and selling rate

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  • Zhu, Dingju

Abstract

The qualitative and quantitative combined nonlinear dynamics model proposed in this paper fill the gap in nonlinear dynamics model in terms of qualitative and quantitative combined methods, allowing the qualitative model and quantitative model to perfectly combine and overcome their weaknesses by learning from each other. These two types of models use their strengths to make up for the other’s deficiencies. The qualitative and quantitative combined models can surmount the weakness that the qualitative model cannot be applied and verified in a quantitative manner, and the high costs and long time of multiple construction as well as verification of the quantitative model. The combined model is more practical and efficient, which is of great significance for nonlinear dynamics. The qualitative and quantitative combined modeling and model analytical method raised in this paper is not only applied to nonlinear dynamics, but can be adopted and drawn on in the modeling and model analysis of other fields. Additionally, the analytical method of qualitative and quantitative combined nonlinear dynamics model proposed in this paper can satisfactorily resolve the problems with the price system’s existing nonlinear dynamics model analytical method. The three-dimensional dynamics model of price, supply–demand ratio and selling rate established in this paper make estimates about the best commodity prices using the model results, thereby providing a theoretical basis for the government’s macro-control of price. Meanwhile, this model also offer theoretical guidance to how to enhance people’s purchasing power and consumption levels through price regulation and hence to improve people’s living standards.

Suggested Citation

  • Zhu, Dingju, 2016. "Qualitative and quantitative combined nonlinear dynamics model and its application in analysis of price, supply–demand ratio and selling rate," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 54-72.
    • Handle: RePEc:eee:chsofr:v:89:y:2016:i:c:p:54-72
    DOI: 10.1016/j.chaos.2015.09.026
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    References listed on IDEAS

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    1. Xuefeng Yan & Yong Zhou & Yan Wen & Xudong Chai, 2013. "Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-12, July.
    2. Caginalp, Gunduz & DeSantis, Mark & Sayrak, Akin, 2014. "The nonlinear price dynamics of U.S. equity ETFs," Journal of Econometrics, Elsevier, vol. 183(2), pages 193-201.
    3. G. Caginalp & M. Desantis, 2011. "Stock price dynamics: nonlinear trend, volume, volatility, resistance and money supply," Quantitative Finance, Taylor & Francis Journals, vol. 11(6), pages 849-861.
    4. Ramanathan, R. & Ganesh, L. S., 1995. "Energy resource allocation incorporating qualitative and quantitative criteria: An integrated model using goal programming and AHP," Socio-Economic Planning Sciences, Elsevier, vol. 29(3), pages 197-218, September.
    5. Berg, Ernst & Huffaker, Ray, 2015. "Explaining the German hog price cycle: A nonlinear dynamics approach," 2015 International European Forum (144th EAAE Seminar), February 9-13, 2015, Innsbruck-Igls, Austria 206210, International European Forum on System Dynamics and Innovation in Food Networks.
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