A bank liquidity multilayer network based on media emotion

Lei Wang, Shouwei Li (), Wenyi Wang, Wenke Yang and Hu Wang
Additional contact information
Lei Wang: Southeast University
Shouwei Li: Southeast University
Wenyi Wang: University of Toronto
Wenke Yang: Southeast University
Hu Wang: Southeast University

The European Physical Journal B: Condensed Matter and Complex Systems, 2021, vol. 94, issue 2, 1-23

Abstract: Abstract From the cross perspective of media emotion and multilayer network correlation, this paper uses big data technology to mine the data of news reports about bank liquidity, constructs a bank liquidity multilayer network including different media emotional layers, and then analyzes the correlation characteristics of interbank liquidity risk. The main conclusions are as follows: there are banks with higher strength and activity in the bank liquidity multilayer network. These systemically important banks are large state-owned banks and joint-stock commercial banks with large assets. However, among systemically important banks based on strength, large state-owned banks are dominant, and when based on activity, joint-stock commercial banks have more significant influence. The interlayer correlation of the bank liquidity multilayer network is high, and the importance of banks is relatively consistent in different layers. A bank liquidity multilayer network has the characteristics of a small world network with smaller average path length and larger clustering coefficient. The interlayer similarity of the bank liquidity multilayer network is low, and the substitution is poor between positive media emotional network layer and negative media emotional network layer. Graphic abstract

Date: 2021
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DOI: 10.1140/epjb/s10051-020-00017-3

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