Journal of Credit Risk
ISSN:
1744-6619 (print)
1755-9723 (online)
Editor-in-chief: Ashish Dev and Michael Gordy
About this journal
With the re-writing of the Basel accords in international banking and their ensuing application, interest in credit risk has never been greater. The Journal of Credit Risk focuses on the measurement and management of credit risk, the valuation and hedging of credit products, and aims to promote a greater understanding in the area of credit risk theory and practice.
The Journal of Credit Risk considers submissions in the form of research papers and technical papers, on topics including, but not limited to:
- Modelling and management of portfolio credit risk
- Recent advances in parameterizing credit risk models: default probability estimation, copulas and credit risk correlation, recoveries and loss given default, collateral valuation, loss distributions and extreme events
- Pricing and hedging of credit derivatives
- Structured credit products and securitizations e.g. collateralized debt obligations, synthetic securitizations, credit baskets, etc.
- Measuring managing and hedging counterparty credit risk
- Credit risk transfer techniques
- Liquidity risk and extreme credit events
- Regulatory issues, such as Basel II, internal ratings systems, credit-scoring techniques and credit risk capital adequacy
Abstracting and Indexing: Scopus; Web of Science - Social Science Index; EconLit; Excellence Research Australia; Econbiz; and Cabell’s Directory
Journal Metrics:
Impact Factor: 0.226
5-Year Impact Factor: 0.354
CiteScore: 0.17
Latest papers
An efficient portfolio loss model
This paper develops a parsimonious model for evaluating portfolio credit derivatives dependent on aggregate loss.
A consumer credit risk structural model based on affordability: balance at risk
A statistical technique to enhance application scorecard monitoring
Application scoring plays a critical role in determining the future quality of a lender’s book. It is therefore important to monitor the performance of an application scorecard to ensure it performs as expected.
Wrong-way risk of interest rate instruments
This paper investigates wrong-way risk effects on the pricing of counterparty credit risk for interest rate instruments.
The influence of firm efficiency on agency credit ratings
Calibration and mapping of credit scores by riding the cumulative accuracy profile
Are lenders using risk-based pricing in the Italian consumer loan market? The effect of the 2008 crisis
This paper analyzes whether in Italy the price of consumer loans is based on borrower-specific credit risk.
Systemic risk in the financial system: capital shortfalls under Brexit, the US elections and the Italian referendum
This paper uses SRISK to quantify the estimated capital shortfalls of financial institutions under three relevant stress events that occurred in 2016: Brexit, the Trump election and the Italian referendum.
A fifty-year retrospective on credit risk models, the Altman Z-score family of models and their applications to financial markets and managerial strategies
This paper reflects upon the evolution of the Altman family of bankruptcy prediction models, as well as their extensions and multiple applications in financial markets and managerial decision making.
Bank risk, bank bailouts and sovereign capacity during a financial crisis: a cross-country analysis
This paper analyzes the competitive effects of government bailout expectations on bank risk using a sample of banks in OECD countries from 2005 to 2015.
Calculating capital charges for sector concentration risk
This paper proposes a methodology to quantify capital charges for concentration risk when economic capital calculations are conducted within a multifactor Merton framework.
An empirical study on credit risk management: the case of nonbanking financial companies
The aim of this paper is to predict future default behaviors of nonbank financial company customers using credit scores.
A new model for bank loan loss given default by leveraging time to recovery
In this paper, the author estimates a two-equation system: one for LGD that incorporates time to recovery as one of the model explanatory variables, and the other for time to recovery using survival models that address data censoring.
Default contagion among credit modalities: evidence from Brazilian data
The aim of this paper is to assess the impact of defaulting on one personal credit modality on future defaults on other modalities. Using Brazilian microdata, the authors run a logistic regression to estimate the probability of default on a given credit…
Modeling dependent risk factors with CreditRisk+
In this paper, an extension of the CreditRisk+ model, called the mixed vector model, is proposed.
Consumer risk appetite, the credit cycle and the housing bubble
In this paper, we explore the role of consumer risk appetite in the initiation of credit cycles and as an early trigger of the US mortgage crisis.
Credit default prediction using a support vector machine and a probabilistic neural network
In this study, the authors address the fact that the ranking of classifiers varies for different criteria with measures under different circumstances, by proposing the simultaneous application of support vector machine and probabilistic neural network …
Moment estimators for autocorrelated time series and their application to default correlations
In this paper, the authors analyze how autocorrelation affects MoM estimators commonly used in the industry to determine the latent asset return correlation, and propose a new estimator that includes correction terms to account for the autocorrelation…
A copula approach to credit valuation adjustment for swaps under wrong-way risk
This paper deals with the credit valuation adjustment (CVA) of interest rate swap (IRS) contracts in the presence of an adverse dependence between the default time and interest rates: so-called wrong-way risk (WWR).
Nonlinear relationships in a logistic model of default for a high-default installment portfolio
This paper uses data on consumer credit along with generalized additive models to analyze nonlinear relationships and their effect on predicting the probability of default in the context of consumer credit scoring.
