TY - JOUR
T1 - Systemic risk and liquidity rescue in complex financial networks
T2 - Pit hole and black hole of liquidity
AU - He, Yi
AU - Wu, Shan
AU - Tong, Mu
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/12/15
Y1 - 2019/12/15
N2 - Using the payment settlement network as an example and constructing the liquidity circulation model in a complex network, the intrinsic mechanism of liquidity circulation is analyzed, and the function of different network nodes in liquidity circulation is studied by distinguishing between the spillover node and leaking node and the liquidity pit hole and liquidity black hole. After studying the different system risk scenarios under different network structures based on the simulation, this paper discovers that the smaller the differences between nodes and the closer the connections, the smaller the probability of systematic risk and the more serious the consequence when the risk is formed. This result is determined by the characteristics of network topology and the liquidity demand of the nodes affected by it. This study also finds that because the degree of systemic risk is positively correlated with the system's liquidity gap, the rescue strategy based on using the nodes’ liquidity gaps to allocate the rescue fund is better and can achieve complete relief when the gaps are eliminated. When taking care to avoid liquidity pits, the rescue effect can be improved on the small rescue scale. In different systemic risk scenarios, the order of rescue also matters. When the risk is high, priority should be given to the participants with a smaller liquidity gap, when the risk is moderate, priority should be given to a balanced bailout, and there is only a trivial difference between the different rescue orders when the risk is small.
AB - Using the payment settlement network as an example and constructing the liquidity circulation model in a complex network, the intrinsic mechanism of liquidity circulation is analyzed, and the function of different network nodes in liquidity circulation is studied by distinguishing between the spillover node and leaking node and the liquidity pit hole and liquidity black hole. After studying the different system risk scenarios under different network structures based on the simulation, this paper discovers that the smaller the differences between nodes and the closer the connections, the smaller the probability of systematic risk and the more serious the consequence when the risk is formed. This result is determined by the characteristics of network topology and the liquidity demand of the nodes affected by it. This study also finds that because the degree of systemic risk is positively correlated with the system's liquidity gap, the rescue strategy based on using the nodes’ liquidity gaps to allocate the rescue fund is better and can achieve complete relief when the gaps are eliminated. When taking care to avoid liquidity pits, the rescue effect can be improved on the small rescue scale. In different systemic risk scenarios, the order of rescue also matters. When the risk is high, priority should be given to the participants with a smaller liquidity gap, when the risk is moderate, priority should be given to a balanced bailout, and there is only a trivial difference between the different rescue orders when the risk is small.
KW - Liquidity rescue
KW - Network topology
KW - Payment system
KW - Systemic risk
UR - http://www.scopus.com/inward/record.url?scp=85066065989&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2019.04.241
DO - 10.1016/j.physa.2019.04.241
M3 - Article
AN - SCOPUS:85066065989
SN - 0378-4371
VL - 536
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
M1 - 121005
ER -