scholarly journals An Incentive Mechanism Model of Credit Behavior of SMEs Based on the Perspective of Credit Default Swaps

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Shenghong Wu ◽  
Pei Mu ◽  
Jiaxian Shen ◽  
Wenyi Wang
Keyword(s):  
Credit Risk ◽  
Rapid Development ◽  
Credit Default Swap ◽  
Bank Loan ◽  
Credit Risk Management ◽  
Mechanism Model ◽  
Influence Mechanism ◽  
Enterprise Credit ◽  
Credit Default ◽  
Credit Financing

The rapid development of credit default swap (CDS) market has changed the manner of credit risk management of banks to some extent and has had a new influence on the bank-enterprise credit model. In this study, the credit financing process of credit risk in small- and medium-sized enterprises (SMEs) gathers within a bank, which makes it difficult for SMEs to raise funds. On the basis of the perspective of CDS, we construct an incentive game model of bank-enterprise credit behavior and analyze the influence mechanism of the credit financing of SMEs on CDS contract coupon rate, CDS payout ratio, bank-enterprise credit effort, and loan recovery rate when considering CDS. The result shows that the CDS contract leads to insufficient supervision after a bank loan, the moral hazard of the SMEs rises, and the probability of credit default events increases. In addition, in view of CDS, the SMEs can access more credit funds.

What Drives Systemic State Credit Risk? Evidence from the State Credit Default Swap (CDS) Market

2019 ◽  
Vol 28 (4) ◽  
pp. 5-45
Author(s):  
Sheen Liu ◽  
Chunchi Wu ◽  
Chung-Ying Yeh ◽  
Woongsun Yoo
Keyword(s):  
Credit Risk ◽  
Credit Default Swap ◽  
The State ◽  
Credit Default ◽  
Default Swap

scholarly journals Enterprise Credit Risk Management Using Multicriteria Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenjuan Liu
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Credit Risk ◽  
Multicriteria Decision Making ◽  
Final Decision ◽  
Credit Risk Management ◽  
Multicriteria Decision ◽  
Risk Manager ◽  
Enterprise Credit ◽  
Weight Calculation

The purpose of this study is to reduce the rate of multicriteria decision-making (MCDA) errors in credit risk management and to weaken the influence of different attitudes of enterprise managers on the final decision when facing credit risk. First, several solutions that are suitable for present enterprise credit risk management are proposed according to the research of enterprise risk management in the world. Moreover, the criteria and matrix are established according to the general practice of the expert method. A decision-making method of enterprise credit risk management with trapezoidal fuzzy number as the criteria of credit risk management is proposed based on the prospect theory; then, the weight is calculated based on G1 weight calculation, G2 weight calculation method, and the method of maximizing deviation; finally, the prospect values of the alternatives calculated by each method are adopted to sort and compare the proposed solutions. Considering the difference of risk degree of managers in the face of credit risk management, the ranking results of enterprise credit risk management solutions based on three weight calculation methods are compared. The results show that as long as the quantitative value of the risk attitude of the enterprise credit risk manager meets a certain range, the final choice of credit risk management scheme ranking is consistent. This exploration provides a new research direction for enterprise credit risk management, which has reference significance.

The Rise of Credit Default Swaps and Its Implications on Financial Stability

2018 ◽  
pp. 336-350
Author(s):  
Fatma Sezer Dural
Keyword(s):  
Credit Risk ◽  
Exponential Growth ◽  
Financial Stability ◽  
Credit Default Swap ◽  
Credit Default Swaps ◽  
Financial Instruments ◽  
Credit Crisis ◽  
Credit Default ◽  
Default Swap ◽  
The Stability

The credit default swap market has experienced an exponential growth in recent decades. Though the fırst credit default swap contract was negotiated in the mid-1990s, the market has enjoyed a surge of popularity beginning in 2003. By the end of June 2013, the outstanding amount reached 24.3 trillion dollars. It is mostly used to transfer or to hedge credit risk. Concurrently with the global credit crisis, several shortcomings in CDS markets have appeared. One of the obvious questions is whether they affect the stability of financial markets. In this context after broader exhibition of credit default swaps market, speculative use of CDS, inception of central counterparty, and transparency of CDS market is handled. As a conclusion, it is true that the CDS market still has some weaknesses, but it is no more prone to be destabilizing than other financial instruments. This is shown in this chapter.

Intelligent System for Credit Risk Management in Financial Institutions

2019 ◽  
Vol 9 (2) ◽  
pp. 57-67
Author(s):  
Philip Sarfo-Manu ◽  
Gifty Siaw ◽  
Peter Appiahene
Keyword(s):  
Credit Risk ◽  
Financial Institutions ◽  
Intelligent System ◽  
Subjective Assessment ◽  
Bank Loan ◽  
Credit Risk Management ◽  
Tree Model ◽  
Assessment And Evaluation ◽  
Employment Sector ◽  
The Government

Credit crunch is an alarming challenge facing financial institutions in Ghana due to their inability to manage credit risk. Failure to manage credit risk may lead to customers defaulting and institutions becoming bankrupt, making it a major concern for financial institutions and the government. The assessment and evaluation of loan applications based on a loan officer's subjective assessment and human judgment is inefficient, inconsistent, non-uniform, and time consuming. Therefore, a knowledge discovery tool is required to help in decision making regarding the approval of loan application. The aim of this project is to develop an intelligent system based on a decision tree model to manage credit risk. Data was obtained from the bank loan histories. The data is comprised of four hundred observations with seven variables: client age, amount requested, dependents, collateral value, employment sector, employment type, and results. The results of study suggest that the proposed system can be used to predict client eligibility for loans with an accuracy rate of 70%.

Counterparty credit risk and the credit default swap market

2012 ◽  
Vol 103 (2) ◽  
pp. 280-293 ◽  
Author(s):  
Navneet Arora ◽  
Priyank Gandhi ◽  
Francis A. Longstaff
Keyword(s):  
Credit Risk ◽  
Credit Default Swap ◽  
Credit Default ◽  
Counterparty Credit Risk ◽  
Default Swap

scholarly journals Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components

2019 ◽  
Vol 12 (3) ◽  
pp. 129
Author(s):  
Alfonso Novales ◽  
Alvaro Chamizo
Keyword(s):  
Risk Factor ◽  
Credit Risk ◽  
Interest Rates ◽  
Explanatory Power ◽  
Credit Default Swap ◽  
Global Risk ◽  
Additional Information ◽  
The North ◽  
Credit Default ◽  
Highly Correlated

We provide a methodology to estimate a global credit risk factor from credit default swap (CDS) spreads that can be very useful for risk management. The global risk factor (GRF) reproduces quite well the different episodes that have affected the credit market over the sample period. It is highly correlated with standard credit indices, but it contains much higher explanatory power for fluctuations in CDS spreads across sectors than the credit indices themselves. The additional information content over iTraxx seems to be related to some financial interest rates. We first use the estimated GRF to analyze the extent to which the eleven sectors we consider are systemic. After that, we use it to split the credit risk of individual firms into systemic, sectorial, and idiosyncratic components, and we perform some analyses to test that the estimated idiosyncratic components are actually firm-specific. The systemic and sectorial components explain around 65% of credit risk in the European industrial and financial sectors and 50% in the North American sectors, while 35% and 50% of risk, respectively, is of an idiosyncratic nature. Thus, there is a significant margin for portfolio diversification. We also show that our decomposition allows us to identify those firms whose credit would be harder to hedge. We end up analyzing the relationship between the estimated components of risk and some synthetic risk factors, in order to learn about the different nature of the credit risk components.

scholarly journals THE INTERACTIONS AND TRADE-OFFS OF SOVEREIGN CREDIT DEFAULT SWAP (CDS) AND BOND SPREADS IN A DYNAMIC CONTEXT

2019 ◽  
Vol 20 (3) ◽  
pp. 466-488
Author(s):  
Ioannis A. Tampakoudis ◽  
Andrius Tamošiūnas ◽  
Demetres N. Subeniotis ◽  
Ioannis G. Kroustalis
Keyword(s):  
Credit Risk ◽  
Price Discovery ◽  
Credit Default Swap ◽  
Bond Market ◽  
Discovery Process ◽  
Sovereign Credit ◽  
Credit Default ◽  
Default Swap ◽  
Bond Spreads ◽  
Price Discovery Process

This study provides a dynamic analysis of the lead-lag relationship between sovereign Credit Default Swap (CDS) and bond spreads of the highly indebted southern European countries, considering an extensive time sample from the period before the global financial crisis to the latest developments of the sovereign indebtedness in the euro area. We employ an integrated price discovery methodology on a rolling sample, with the intention to shed light on whether the CDS spreads can trigger rises in bond spreads, and the relative efficiency of credit risk pricing in the CDS and bond markets. In addition, we attempt to depict the evolution of the price discovery process regarding the direction of influence from one market to the other. The rolling window analysis verifies that the price discovery process evolves over time, presenting frequent alternations concerning the leading market. We find that during periods of economic turbulence the CDS market leads the bond market in price discovery, incorporating the new information about sovereign credit risk faster and more efficiently than the bond market does. This regularity should be seriously considered by private and public participants as they make investment and funding decisions. Therefore, the motivation of our paper is to identify the dominant market in terms of price discovery during a period of economic turmoil and, thus, to provide insights for decision making to investment bodies and central governments.

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