Open AccessAnalysis on the topological properties of the linkage complex network between crude oil future price and spot price
Author(s) -
Xiangyun Gao,
Haizhong An,
Honghong Liu,
Yinghui Ding
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.068902
Subject(s) - betweenness centrality , linkage (software) , clustering coefficient , topology (electrical circuits) , node (physics) , average path length , cluster analysis , complex network , computer science , cluster (spacecraft) , mathematics , centrality , shortest path problem , combinatorics , physics , artificial intelligence , biology , graph , biochemistry , quantum mechanics , gene , programming language
This paper analyzes the linkage between crude oil future price and spot price based on complex network theory. The linkage between oil future price and Daqing (China) crude oil spot price from November 25, 2002 to September 24, 2010 is transformed into symbolic sequences consisted of three characters {Y, O, N} through the process of coarse graining. The nodes of the complex network are 5-symbol strings in the number of 177 in the form of data window linked in the networks topology by sliding sequence. The complexity of the linkage is verified through analyzing the topological properties of point of strength, strength distribution, weighted clustering coefficient, average shortest paths, betweenness centrality and subgroup in the complex network. The results indicate that the point of strength value of the former 32 nodes is larger, cumulative strength distribution is 73.27%, and most fluctuation models linkages have the character with the same direction. However, it does not show a good correlation between weighted clustering coefficient and point of strength. There are some small cluster groups appearing in the network. These small cluster groups constitute two camps whose cores are node and node. The results also show that average shortest paths length is 6.969 and 11.3% of nodes occupying 1/4 of centrality function, and there are not many subgroups with close linkage, which verifies the complex characteristics of the linkage fluctuation in the network topology. This paper finds the power law, clustering and periodicity between two kinds of prices in the long run, which is of great significance in grasping the crude oil market, predicting oil price volatility reasonable, formulating price and avoiding risk.