title: Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network.
abstract: We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01-2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results.
authors.affiliation: Nonlinear Science Research Center, Jiangsu University, Zhenjiang, Jiangsu, China.
authors.forename: Ruijin
authors.initials: R
authors.lastname: Du
authors.affiliation: Nonlinear Science Research Center, Jiangsu University, Zhenjiang, Jiangsu, China.
authors.forename: Gaogao
authors.initials: G
authors.lastname: Dong
authors.affiliation: Nonlinear Science Research Center, Jiangsu University, Zhenjiang, Jiangsu, China.|School of Mathematics Sciences, Nanjing Normal University, Nanjing, Jiangsu, China.
authors.forename: Lixin
authors.initials: L
authors.lastname: Tian
authors.affiliation: School of Mathematics Sciences, Nanjing Normal University, Nanjing, Jiangsu, China.
authors.forename: Minggang
authors.initials: M
authors.lastname: Wang
authors.affiliation: School of Economics, Nanjing University of Finance and Economics, Nanjing, Jiangsu 210023, China.
authors.forename: Guochang
authors.initials: G
authors.lastname: Fang
authors.affiliation: Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts, United States of America.
authors.forename: Shuai
authors.initials: S
authors.lastname: Shao
mesh_terms: D016000:Cluster Analysis; D008962:Models, Theoretical; D010578:Petroleum / Q000191:economics*
chemical_list: D010578:Petroleum