scholarly journals Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Tingqiang Chen ◽  
Binqing Xiao ◽  
Haifei Liu
Keyword(s):  
Credit Risk ◽  
Network Model ◽  
Network Structure ◽  
Behavioral Interventions ◽  
Spillover Effects ◽  
Credit Risk Management ◽  
Risk Transfer ◽  
Credit Risk Transfer ◽  
Market Noise ◽  
Credit Risk Contagion

We introduce an evolving network model of credit risk contagion in the credit risk transfer (CRT) market. The model considers the spillover effects of infected investors, behaviors of investors and regulators, emotional disturbance of investors, market noise, and CRT network structure on credit risk contagion. We use theoretical analysis and numerical simulation to describe the influence and active mechanism of the same spillover effects in the CRT market. We also assess the reciprocal effects of market noises, risk preference of investors, and supervisor strength of financial market regulators on credit risk contagion. This model contributes to the explicit investigation of the connection between the factors of market behavior and network structure. It also provides a theoretical framework for considering credit risk contagion in an evolving network context, which is greatly relevant for credit risk management.

scholarly journals A Network Model of Credit Risk Contagion

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Ting-Qiang Chen ◽  
Jian-Min He
Keyword(s):  
Credit Risk ◽  
Numerical Simulations ◽  
Network Model ◽  
Financial Market ◽  
Network Structure ◽  
Stochastic Dominance ◽  
Individual Attitude ◽  
Individual Ability ◽  
The Individual ◽  
Credit Risk Contagion

A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

scholarly journals An Entropy Model of Credit Risk Contagion in the CRT Market

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Tingqiang Chen ◽  
Ying Chen ◽  
Xindan Li ◽  
Jining Wang
Keyword(s):  
Credit Risk ◽  
Spatial Model ◽  
Spatial Distance ◽  
Entropy Model ◽  
Risk Transfer ◽  
Contagion Effects ◽  
Default Rates ◽  
Credit Default ◽  
Credit Risk Transfer ◽  
Credit Risk Contagion

This paper reports the effect of the change in the credit status of debtors on investors as a result of the banks’ transferring of credit risk to investors in the credit risk transfer (CRT) market. Thus, an entropy spatial model is introduced, in which the spatial distance and nonlinear coupling between the banks and the investors, the transfer ability of credit risk of banks, and investor appetite for risk in the CRT network are considered. The contagion effects of the credit default of debtor on the default rates of investors in the CRT market are investigated using numerical simulation and sensitivity analysis.

Credit Risk Transfer and the Forecasting of Bank Defaults

2009 ◽  
Author(s):  
Giovanni Calice ◽  
Christos Ioannidis ◽  
Julian M. Williams
Keyword(s):  
Credit Risk ◽  
Risk Transfer ◽  
Credit Risk Transfer

What explains the recourse of US commercial banks to securitization?

2016 ◽  
Vol 15 (3) ◽  
pp. 317-328 ◽  
Author(s):  
Nesrine Bensalah ◽  
Hassouna Fedhila
Keyword(s):  
Credit Risk ◽  
Selection Procedure ◽  
Regulatory Capital ◽  
Heckman Selection Model ◽  
Mortgage Loans ◽  
Content Type ◽  
Risk Transfer ◽  
Credit Risk Transfer ◽  
The Usa ◽  
Heckman Selection

Purpose The purpose of this paper is to investigate the reasons that urge US banks to securitize. Design/methodology/approach The authors apply a logistic regression model to a sample of 5,394 observations. The dependent variable takes 1 if the bank securitizes and 0 if not. The authors use also, a Heckman selection model to account for the potential dependence between the decision to securitize and the decision of which assets to securitize. Findings The results indicate that liquidity, credit risk transfer, regulatory capital arbitrage and profitability are the most important factors that drive securitization in the USA. Moreover, the nature of the asset securitized appears to be dependent on the objective that the bank pursues. For funding and capital arbitrage objectives, the bank needs to securitize its mortgage loans. However, for credit risk transfer purposes, it has to opt for a non mortgage securitization. The nature of the asset securitized can thus, be used as a signal for bank’s intentions to securitize. Originality/value This study contributes to a better understanding of the reasons that urge banks to securitize. It also presents, using a Heckman selection procedure, a detailed analysis that discriminates between different types of securitization.

scholarly journals Credit risk transfer and bank competition

2010 ◽  
Vol 19 (3) ◽  
pp. 308-332 ◽  
Author(s):  
Hendrik Hakenes ◽  
Isabel Schnabel
Keyword(s):  
Credit Risk ◽  
Bank Competition ◽  
Risk Transfer ◽  
Credit Risk Transfer
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