Futures trading is the core of futures business, and  is considered as a typical complex system . To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from  Shanghai Futures Exchange to construct futures trading networks, in which vertices are trading participants, and two vertices have a common edge if the two corresponding investors simultaneously appear in at least one trading record as a purchaser and a seller respectively. Then, we conduct a comprehensive statistical analysis on the constructed futures trading networks , and empirical results show that the futures trading networks exhibit such features as scale-free structure with interesting odd-even-degree divergence in low degree region , small-world effect, URLanization, power-law betweenness distribution,  and shrinkage of both  average path length and  diameter as network size increases. To the best of our knowledge, this is the first work that uses real data to study futures trading networks, and we argue that the research results can shed light on the nature of real futures business.
Futures trading is the core of futures business, and it is considered as one of the typical complex systems . To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from the Shanghai Futures Exchange to construct futures trading networks, in which nodes are trading participants, and two nodes have a common edge if the two corresponding investors appear simultaneously in at least one trading record as a purchaser and a seller respectively. Then, we conduct a comprehensive statistical analysis on the constructed futures trading networks . Empirical results show that the futures trading networks exhibit features such as scale-free behavior with interesting odd-even-degree divergence in low-degree regions , small-world effect, URLanization, power-law betweenness distribution, disassortative mixing, and shrinkage of both the average path length and the diameter as network size increases. To the best of our knowledge, this is the first work that uses real data to study futures trading networks, and we argue that the research results can shed light on the nature of real futures business.
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it
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a typical complex system
one of the typical complex systems
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the
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vertices
nodes
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vertices
nodes
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simultaneously appear
appear simultaneously
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, and empirical
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such features
features such
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structure
behavior
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low degree region
low-degree regions
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disassortative mixing,
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the
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the