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To analyze the dynamic of crude oil price data using homogenous partition of coarse graining process,OK WTI Spot Price FOB from January 1986 to November 2009 was transformed into symbolic sequences consisting of three characters (R,e,D). The vertices of the oil price fluctuation network were 5-symbol strings in the number of 102(i.e.102 fluctuation patterns in durations of 5 days) linked in the network's topology by time sequence. It contained integrated information about interconnections and interactions between fluctuation patterns of oil price in network topology. The dynamical statistics of the degree, degree distribution, clustering coefficient and the shortest path length were calculated. The results indicated that the degree of the oil price sequence fluctuation network and the accumulated degree distribution show a power-law distribution, so did the node degree and the rank. The degree of the former 32 nodes was larger, and most oil price fluctuation models had the character with the escalating trend. Some nodes of the oil price fluctuation network had stronger ability in between centrality, and 24.5 percent of the nodes took part in the 80.97 percent of Between Centrality function. The average path length was 2.285, and the paths with length 2—3 were 86.8 percent, which verified the complex characteristics of the oil price fluctuation in network topology. This paper had guiding significance in identifying the topological importance of the node model and understanding the inherent law and information of the oil price fluctuation.
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Keywords:
- oil price /
- symbolic strings /
- complex network /
- topological structure
[1] Robert K K, Ben U 2009 Energy Economics 31 550
[2] Barabási A L, Albert R 1999 Science 286 509
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[12] Fang J Q, Wang X F, Liu Z R 2004 Sci.Techn.Rev.2 9 (in Chinese) [方锦清、汪小帆、刘曾荣 2004 科技导报 2 9 ]
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[14] Qin S, Dai G Z 2009 Chin.Phys.B 18 383
[15] Hao B L 1999 Science 51 3[郝柏林 1999 科学 51 3]
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[18] Zhou L, Gong Z Q, Zhi R, Feng G L 2008 Acta Phys.Sin.57 7380 (in Chinese) [周 磊、龚志强、支 蓉、封国林 2008 57 7380]
[19] Zhou L, Gong Z Q, Zhi R, Feng G L 2009 Acta Phys.Sin.58 7351 (in Chinese) [周 磊、龚志强、支 蓉、封国林 2009 58 7351]
[20] Li J, Wang B H, Jiang P Q, Zhou T, Wang W X 2006 Acta Phys.Sin.55 4051 (in Chinese) [李 季、汪秉宏、蒋品群、周 涛、王文旭 2006 55 4051]
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[1] Robert K K, Ben U 2009 Energy Economics 31 550
[2] Barabási A L, Albert R 1999 Science 286 509
[3] Watts D J, Strogatz S H 1998 Nature 393 6684
[4] Newman M E J 1999 Phys.Lett.A 263 341
[5] Erds P, Rényi A 1960 Publ.Math.Inst.Hung.Acad.Sci.5 17
[6] Meng Q K, Zhu J Y 2009 Chin.Phys.B 18 3632
[7] Zhang L, Liu Y 2008 Acta Phys.Sin.57 5419 (in Chinese) [张 立、 刘 云 〖8] Chen H L, Liu Z X, Chen Z Q, Yuan Z Z 2009 Acta Phys.Sin.58 6068 (in Chinese) [陈华良、刘忠信、陈增强、袁著祉 2009 58 6068]
[8] He Y, Zhang P P, Xu T, Jiang Y M, He D R 2004 Acta Phys.Sin.53 1710 (in Chinese) [何 阅、张培培、许 田、姜玉梅、何大韧 2004 53 1710]
[9] Cao Z W, Li Y X, Luo J H, Tao L, Yu H, Zhao J 2007 Chin.Phys.16 3571
[10] Guo J L 2007 Chin.Phys.16 1239
[11] Zhang H F, Fu X C, Wang B H 2009 Chin.Phys.B 18 3639
[12] Fang J Q, Wang X F, Liu Z R 2004 Sci.Techn.Rev.2 9 (in Chinese) [方锦清、汪小帆、刘曾荣 2004 科技导报 2 9 ]
[13] Xu D, Li X, Wang X F 2007 Acta Phys.Sin.56 1313 (in Chinese) [许 丹、李 翔、汪小帆 2007 56 1313]
[14] Qin S, Dai G Z 2009 Chin.Phys.B 18 383
[15] Hao B L 1999 Science 51 3[郝柏林 1999 科学 51 3]
[16] Ke D G, Zhang H, Tong Q Y 2005 Acta Phys.Sin.54 534 (in Chinese) [柯大观、张 宏、童勤业 2005 54 534]
[17] Huang W Q, Zhuang X T, Yao S 2009 Physica A 388 2956
[18] Zhou L, Gong Z Q, Zhi R, Feng G L 2008 Acta Phys.Sin.57 7380 (in Chinese) [周 磊、龚志强、支 蓉、封国林 2008 57 7380]
[19] Zhou L, Gong Z Q, Zhi R, Feng G L 2009 Acta Phys.Sin.58 7351 (in Chinese) [周 磊、龚志强、支 蓉、封国林 2009 58 7351]
[20] Li J, Wang B H, Jiang P Q, Zhou T, Wang W X 2006 Acta Phys.Sin.55 4051 (in Chinese) [李 季、汪秉宏、蒋品群、周 涛、王文旭 2006 55 4051]
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