Research on BDI index fluctuation power law distribution features based on the jump time and jump range

YU Fangping, KUANG Haibo

Systems Engineering - Theory & Practice ›› 2017, Vol. 37 ›› Issue (3) : 607-619.

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Systems Engineering - Theory & Practice ›› 2017, Vol. 37 ›› Issue (3) : 607-619. DOI: 10.12011/1000-6788(2017)03-0607-13

Research on BDI index fluctuation power law distribution features based on the jump time and jump range

  • YU Fangping, KUANG Haibo
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Abstract

The baltic dry index (BDI) index is the international shipping market barometer. BDI index fluctuation power law distribution features are important for further mastering shipping freight characteristics, BDI trends forecasting, shipping decision-making and so on. This paper has a detailed research on 30 years BDI index fluctuation power law distribution features. The main characteristics includes:Firstly, the BDI index power law distribution features are discussed with Pareto, Exponential and Fokker-Planck function for the first time. Secondly, on the basis of jump identify, the jump time and jump range scales BDI index fluctuation power law distribution models are set up, which are transformed into a least square method of linear regression models. Thirdly, empirical analysis on BDI index daily, weekly and monthly growth rates jump time and jump range power law distribution features, results showed that BDI index growth rate distribution has pointed peak, thin tail and fluctuation gathered. Fokker-Planck function fitting BDI index growth rate jump time is more appropriate, Exponential function fitting BDI index growth rate jump range is more appropriate. BDI index growth rate jump time and jump range are has thin tail power law feature, and jump upon and jump down power law features are symmetry.

Key words

BDI index / power law distribution features / jump time / jump range / Fokker-Planck function

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YU Fangping , KUANG Haibo. Research on BDI index fluctuation power law distribution features based on the jump time and jump range. Systems Engineering - Theory & Practice, 2017, 37(3): 607-619 https://doi.org/10.12011/1000-6788(2017)03-0607-13

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Funding

National Natural Science Foundation of China (71273037); Transportation Soft Science Project of Ministry of Transport (2013-322-225-240); Program for Innovative Research Team in University of Liaoning (LT2013011); Program for Changjiang Scholars and Innovative Research Team (IRT13048)
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