A belief-function perspective to credit risk assessments

2010 ◽  
pp. 269-294 ◽  
Author(s):  
Rajendra P. Srivastava ◽  
Stewart Jones
Keyword(s):  
Credit Risk ◽  
Belief Function ◽  
Risk Assessments

scholarly journals Credit Risk Assessments and Firm Value of Listed Commercial Banks in Kenya

2021 ◽  
pp. 68-82
Author(s):  
Mohamed Maalim Issackow ◽  
Felix Mwambia ◽  
Wilson Muema
Keyword(s):  
Credit Risk ◽  
Commercial Bank ◽  
Commercial Banks ◽  
Firm Value ◽  
Equity Capital ◽  
Capital Adequacy ◽  
Risk Assessments ◽  
Asset Quality ◽  
The Impact ◽  
Positive Effect

Despite the various control measures put in place especially the CBK’s prudential laws to ensure that the performance of commercial banks in Kenya is ensured, most commercial banks have been collapsing in the recent past. It is in this light that the current study sought to ascertain the impact of bank liquidity, capital adequacy, asset quality and earnings on the firm value of listed Commercial banks in Kenya. Descriptive research design was employed on a population sample of eleven publicly listed retail banks. Secondary data was collected from CBK and other public financial reports over the 12-year period from 2009 to 2020. The collected data was analysed using1a multivariate panel regression1model to generate the relevant regression tests. The1study established that the capital adequacy has a marginal positive impact on the firm value while earning ability was found to have a statically insignificant positive effect on firm value among Kenyan commercial bank. The study findings indicated that liquidity was insignificantly and negatively correlated with firm value as asset quality had insignificant positive effect on firm value among Kenyan commercial bank. The study recommends that, managers of listed banks should embrace utilization of internally generated equity capital to ultimately promotes credit risk assessments as they maintain optimal levels of liquidity to maximize firm value and maintain high quality of assets as they sustained levels of earnings that boost output. This paper explained a credit risk rating concept that had not been examined in Kenya before.

Credit risk signals in CDS market vs agency ratings

2016 ◽  
Vol 17 (2) ◽  
pp. 194-217 ◽  
Author(s):  
Michael Jacobs Jr ◽  
Ahmet K. Karagozoglu ◽  
Dina Naples Layish
Keyword(s):  
Credit Risk ◽  
Credit Rating ◽  
Credit Ratings ◽  
Credit Default Swap ◽  
Risk Assessments ◽  
Content Type ◽  
Rating Agencies ◽  
Market Participants ◽  
Credit Default ◽  
The Relationship

Purpose This research aims to model the relationship between the credit risk signals in the credit default swap (CDS) market and agency credit ratings, and determines the factors that help explain the variation in such signals. Design/methodology/approach A comprehensive analysis of the differences in the relative credit risk assessments of CDS-based risk signals and agency ratings is provided. It is shown that the divergence between credit risk signals in the CDS market and agency ratings is explained by factors which the rating agencies may consider differently than credit market participants. Findings The results suggest that agency credit ratings of relative riskiness of a reference entity do not always correspond with assessments by CDS spreads, as the price of risk is a function of additional macro and micro factors that can be explained using statistical analysis. Originality/value This research is unique in modeling the relationship between the credit risk assessments of the CDS market and the agency ratings, which to the best of the authors' knowledge has not been analyzed before in terms of their agreement and the level of discrepancy between them. This model can be used by investors in debt instruments that are not explicitly CDSs or which have illiquid CDS contracts, to replicate market-based, point-in-time credit risk signals. Based on both market-based and firm-specific factors in this model, the results can be used to augment through-the-cycle credit risk assessments, analyze issues surrounding the pricing of CDSs and examine the policies of credit rating agencies.

Soft Information in Loan Agreements

2017 ◽  
Vol 33 (1) ◽  
pp. 40-71 ◽  
Author(s):  
Zahn Bozanic ◽  
Lin Cheng ◽  
Tzachi Zach
Keyword(s):  
Credit Risk ◽  
Soft Information ◽  
Risk Assessments ◽  
Uncertainty Measure ◽  
Performance Pricing ◽  
And Performance ◽  
Loan Spreads ◽  
Bid Ask Spreads ◽  
Private Loan ◽  
Secondary Loan Market

In this study, we seek to understand whether soft information conveyed by contracting language found in private loan agreements is informative regarding borrower risk. We proxy for credit-risk-relevant soft information using Loughran and McDonald’s uncertainty measure. We first examine initial contract terms and find that, incremental to traditional summary measures of credit risk, increased contractual uncertainty is associated with higher initial loan spreads and a greater likelihood of using dynamic and performance-pricing covenants. We then turn to examine realized credit risk over the life of the loan and find that increased uncertainty is associated with a higher likelihood of future loan downgrades and loan amendments. We corroborate our results on the risk relevance of soft information by showing that the bid-ask spreads of loans trading on the secondary loan market are increasing in uncertainty. Overall, the evidence we provide is consistent with embedded linguistic cues in loan agreements publicly revealing the credit risk assessments of privately informed lenders.

To Construct an Individual Credit Risk Assessment Method

2010 ◽  
Vol 143-144 ◽  
pp. 116-119
Author(s):  
Jia Jun Li ◽  
Li Ping Qin ◽  
Jia Zhao
Keyword(s):  
Risk Assessment ◽  
Cluster Analysis ◽  
Credit Risk ◽  
Practical Method ◽  
Assessment Method ◽  
Risk Assessments ◽  
Individual Risk ◽  
Multiple Classifiers ◽  
Risk Assessment Method ◽  
Low Costs

To achieve low costs and better accuracy of individual risk assessments, we constructed a practical method based on multiple classifiers. The method includes many singal classifiers, such as decision trees and the cluster analysis. And we tested it empirically. The result shows that the application of the method can achieve better accuracy than any single classifier of it.

Column: Risk Assessments

Polymer News ◽  
2004 ◽  
Vol 29 (7) ◽  
pp. 220-223
Author(s):  
Charles Carraher, Jr.
Keyword(s):  
Risk Assessments

Column: Risk Assessments

Polymer News ◽  
2004 ◽  
Vol 29 (2) ◽  
pp. 58-60
Author(s):  
Charles Carraher, Jr.
Keyword(s):  
Risk Assessments
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