scholarly journals The Stability of Banking System with Shadow Banking on Different Interbank Network Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hongjie Pan ◽  
Hong Fan
Keyword(s):  
Systemic Risk ◽  
Random Network ◽  
Rapid Development ◽  
Banking System ◽  
Small World ◽  
Shadow Banking ◽  
Network Structures ◽  
Scale Free ◽  
Interbank Lending ◽  
The Stability

With the rapid development of the financial market, the outbreak of systemic risk is affected by many factors, among which shadow banking is considered to be the essential reason to cause financial crisis and destroy the stability of the banking system. In view of the stability of the banking system, considering shadow banking, interbank lending, and complex relationships between banks, a dynamic complex interbank network model with shadow banking under different network structures is proposed. Based on the model, the effects of ROI, investment periods, average deposit, deposit interest rate, the density of shadow banks, and asset loss are studied quantitatively, and the sensitivity and difference of the banking system with shadow banking under different interbank networks are compared and analyzed. The findings indicate that the spread of systemic risks between banks is closely related to the interbank network structures. With the relatively concentrated interbank network structure, it is easier to increase the probability and degree of risk contagion. Under the random, small-world, and scale-free networks, the random network has the strongest ability to resist and absorb risks, while the small-world network is the weakest. However, once the banking network suffers a big shock, excessive risk will directly break through the protection of the banking network, detonate the systematic risk, and destroy the stability of the banking system with shadow banking. This study contributes to a future empirical research agenda on the topic. Moreover, it gives a reference for policymakers and regulatory authorities to prevent systemic risk introduced by shadow banking.

scholarly journals Network Entropy and Systemic Risk in Dynamic Banking Systems

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Liang He ◽  
Shouwei Li
Keyword(s):  
Systemic Risk ◽  
Random Network ◽  
Small World ◽  
Random Networks ◽  
Scale Free Network ◽  
Small World Networks ◽  
Scale Free ◽  
Banking Systems ◽  
Free Network ◽  
Network Entropy

We investigate network entropy of dynamic banking systems, where interbank networks analyzed include random networks, small-world networks, and scale-free networks. We find that network entropy is positively correlated with the effect of systemic risk in the three kinds of interbank networks and that network entropy in the small-world network is the largest, followed by those in the random network and the scale-free network.

STABILITY OF TWO TYPICAL COMPLEX DYNAMICAL NETWORKS

2008 ◽  
Vol 22 (05) ◽  
pp. 553-560 ◽  
Author(s):  
WU-JIE YUAN ◽  
XIAO-SHU LUO ◽  
PIN-QUN JIANG ◽  
BING-HONG WANG ◽  
JIN-QING FANG
Keyword(s):  
Numerical Simulation ◽  
Dissipative System ◽  
Small World ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Scale Free ◽  
Scale Free Networks ◽  
General Complex ◽  
The Stability ◽  
Theoretical Results

When being constructed, complex dynamical networks can lose stability in the sense of Lyapunov (i. s. L.) due to positive feedback. Thus, there is much important worthiness in the theory and applications of complex dynamical networks to study the stability. In this paper, according to dissipative system criteria, we give the stability condition in general complex dynamical networks, especially, in NW small-world and BA scale-free networks. The results of theoretical analysis and numerical simulation show that the stability i. s. L. depends on the maximal connectivity of the network. Finally, we show a numerical example to verify our theoretical results.

scholarly journals Analysis on Invulnerability of Wireless Sensor Network towards Cascading Failures Based on Coupled Map Lattice

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiuwen Fu ◽  
Yongsheng Yang ◽  
Haiqing Yao
Keyword(s):  
Random Network ◽  
Small World ◽  
Coupled Map Lattice ◽  
Wireless Sensor ◽  
Cascading Failures ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
Entire Network

Previous research of wireless sensor networks (WSNs) invulnerability mainly focuses on the static topology, while ignoring the cascading process of the network caused by the dynamic changes of load. Therefore, given the realistic features of WSNs, in this paper we research the invulnerability of WSNs with respect to cascading failures based on the coupled map lattice (CML). The invulnerability and the cascading process of four types of network topologies (i.e., random network, small-world network, homogenous scale-free network, and heterogeneous scale-free network) under various attack schemes (i.e., random attack, max-degree attack, and max-status attack) are investigated, respectively. The simulation results demonstrate that the rise of interference R and coupling coefficient ε will increase the risks of cascading failures. Cascading threshold values Rc and εc exist, where cascading failures will spread to the entire network when R>Rc or ε>εc. When facing a random attack or max-status attack, the network with higher heterogeneity tends to have a stronger invulnerability towards cascading failures. Conversely, when facing a max-degree attack, the network with higher uniformity tends to have a better performance. Besides that, we have also proved that the spreading speed of cascading failures is inversely proportional to the average path length of the network and the increase of average degree k can improve the network invulnerability.

scholarly journals Competitive Advantages of Shadow Banking Industry: An Analysis Using Porter Diamond Model

2015 ◽  
Vol 6 (2) ◽  
pp. 15 ◽  
Author(s):  
Arash Riasi
Keyword(s):  
Systemic Risk ◽  
Banking Industry ◽  
Banking System ◽  
Firm Strategy ◽  
The Other ◽  
Shadow Banking ◽  
Competitive Advantages ◽  
Diamond Model ◽  
Shadow Banking System ◽  
Global Financial System

<p>This paper tries to find out why shadow banking system has become so competitive in the global financial system and how it can be controlled. For this reason we use Porter’s diamond model to find the competitive advantages of shadow banking. Based on the results of this study it can be concluded that factor conditions, chance and government do not contribute to the competitiveness of shadow banking industry. On the other hand the results suggested that related and supporting industries, firm strategy, structure and rivalry, and demand conditions contribute to the competitiveness of shadow banking industry. It is important to regulate the activities of shadow banking industry in order to prevent this industry from creating systemic risk.</p>

scholarly journals An Empirical Study about Influence of China’s Shadow Banking on the Stability of the Financial System

2016 ◽  
Vol 8 (4) ◽  
pp. 104 ◽  
Author(s):  
Bo Liu ◽  
Shuai Shao ◽  
Yan-yang Gao
Keyword(s):  
Evaluation System ◽  
Rapid Development ◽  
Risk Index ◽  
Financial System ◽  
Fuzzy Comprehensive Evaluation ◽  
Entropy Method ◽  
Response Analysis ◽  
Shadow Banking ◽  
Shadow Banks ◽  
The Stability

<p class="1"><span lang="EN-US">With the rapid development of the financial system in recent years, all kinds of financial derivatives teem and the size of the shadow banking is becoming more and bigger. It has become an important factor affecting the stability of China’s financial system. The influence of shadow banks on the financial system has two sides, on the one hand it is advantageous to the development and expansion of small and medium-sized enterprises as lubricant of corporate financing, on the other hand, features of shadow banking that highly leveraged and term mismatch also bring uncertainty to China’s financial system. Firstly, this paper calculates the size of the shadow banking in China, and then builds a fuzzy comprehensive evaluation system to evaluate the risk of China’s financial system. When determining the evaluation index, this paper apply KMV model to calculate the credit risk of China’s securities market, and the maximum entropy method to determine the index weight. After getting China’s financial system risk index and the size of shadow banking, this paper constructs the VAR model and makes the parameter estimation and impulse response analysis. Analysis results show that in a certain degree, the increase of the scale of shadow banks can reduce the risk of the financial system, but if it is over some certain threshold, it will increase the overall risk of the financial system.</span></p>

scholarly journals Network rewiring dynamics with convergence towards a star network

2016 ◽  
Vol 472 (2194) ◽  
pp. 20160236 ◽  
Author(s):  
P. A. Whigham ◽  
G. Dick ◽  
M. Parry
Keyword(s):  
Infectious Disease ◽  
Random Network ◽  
Small World ◽  
Fixation Time ◽  
Fixed Size ◽  
Star Network ◽  
Scale Free ◽  
Link Type ◽  
Scale Free Networks ◽  
Network Rewiring

Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz ( Nature 393 , 440–442. ( doi:10.1038/30918 )). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach.

Network and equation-based models in epidemiology

2018 ◽  
Vol 11 (03) ◽  
pp. 1850046 ◽  
Author(s):  
Kossi Edoh ◽  
Elijah MacCarthy
Keyword(s):  
Network Models ◽  
Small World ◽  
Control Measures ◽  
Network Structures ◽  
Scale Free ◽  
Measles Outbreak ◽  
Spanish Flu ◽  
Spread Of Infection ◽  
Aggregate Population ◽  
The Impact

Network and equation-based (EB) models are two prominent methods used in the study of epidemics. While EB models use a global approach to model aggregate population, network models focus on the behavior of individuals in the population. The two approaches have been used in several areas of research, including finance, computer science, social science and epidemiology. In this study, epidemiology is used to contrast EB models with network models. The methods are based on the assumptions and properties of compartmental models. In EB models we solve a system of ordinary differential equations and in network models we simulate the spread of epidemics on contact networks using bond percolation. We examine the impact of network structures on the spread of infection by considering various networks, including Poisson, Erdős Rényi, Scale-free, and Watts–Strogatz small-world networks, and discuss how control measures can make use of the network structures. In addition, we simulate EB assumptions on Watts–Strogatz networks to determine when the results are similar to that of EB models. As a case study, we use data from the 1918 Spanish flu pandemic and that from measles outbreak to validate our results.

EXPLORING THE VULNERABILITY OF FRACTAL COMPLEX NETWORKS THROUGH CONNECTION PATTERN AND FRACTAL DIMENSION

Fractals ◽  
2019 ◽  
Vol 27 (06) ◽  
pp. 1950102
Author(s):  
DONG-YAN LI ◽  
XING-YUAN WANG ◽  
PENG-HE HUANG
Keyword(s):  
Fractal Dimension ◽  
Quantitative Research ◽  
Fractal Dimensions ◽  
Network Models ◽  
Small World ◽  
Brain Network ◽  
Complex Model ◽  
Scale Free ◽  
Connection Pattern ◽  
The Stability

The structure of network has a significant impact on the stability of the network. It is useful to reveal the effect of fractal structure on the vulnerability of complex network since it is a ubiquitous feature in many real-world networks. There have been many studies on the stability of the small world and scale-free models, but little has been down on the quantitative research on fractal models. In this paper, the vulnerability was studied from two perspectives: the connection pattern between hubs and the fractal dimensions of the networks. First, statistics expression of inter-connections between any two hubs was defined and used to represent the connection pattern of the whole network. Our experimental results show that statistic values of inter-connections were obvious differences for each kind of complex model, and the more inter-connections, the more stable the network was. Secondly, the fractal dimension was considered to be a key factor related to vulnerability. Here we found the quantitative power function relationship between vulnerability and fractal dimension and gave the explicit mathematical formula. The results are helpful to build stable artificial network models through the analysis and comparison of the real brain network.

scholarly journals Systemic Risk in the Interbank Market with Overlapping Portfolios

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Shanshan Jiang ◽  
Hong Fan
Keyword(s):  
Interest Rate ◽  
Systemic Risk ◽  
Banking System ◽  
Bipartite Network ◽  
Investment Risk ◽  
Interbank Market ◽  
Operating Rules ◽  
Proposed Model ◽  
The Stability ◽  
The Impact

The increasing frequency and scope of the financial crisis have attracted more attention in the research of the systemic risk of banking system. A new model for the interbank market with overlapping portfolios is proposed to simulate a banking system in this work. The proposed model uses a bipartite network of banks and their assets to analyze the impact of bank investment on the stability of the banking system. In addition, this model introduces investment risk and allows banks to make up for liquidity by selling devaluated assets, which reflects the operating rules of the banking system more realistically. The results show that allowing banks to sell devaluated assets to make up for liquidity can improve the stability of the banking system and the interbank market can also improve the stability of the banking system. For the investment of banks, the investment risk is an uncertain factor that affects the stability of the banking system. The proposed model further analyzes the impact of average investment interest rate, savings interest rate, deposit reserve ratio, and investment asset diversity on the stability of the banking system. The model provides a tool for policy-makers and supervision agencies to prevent the systemic risk of banking system.

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