Journal of Credit Risk
ISSN:
1744-6619 (print)
1755-9723 (online)
Editor-in-chief: Nikunj Kapadia and Linda Allen
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
Dynamic initial margin estimation based on quantiles of Johnson distributions
The authors compare JLSMC DIM estimates with those produced by two other methods, finding that the JLSMC algorithm is accurate and efficient, producing results comparable with nested Monte Carlo with an order of magnitude less computational effort.
Estimating correlation parameters in credit portfolio models under time-varying and nonhomogeneous default probabilities
This paper proposes new maximum likelihood estimation methods that offer greater flexibility than current methods and can account for finite portfolio sizes, scarce default data and time varying, nonhomogeneous default probabilities.
Sovereign probabilities of default in the euro area
This paper decomposes credit default swap spreads of euro area members into their risk premium and default risk elements and forecast one year probabilities of default.
Risks of long-term auto loans
The authors investigate the borrower risk factors, delinquency rates, yield curves, and interest rates of long-term auto loans.
An effective credit rating method for corporate entities using machine learning
The authors propose a new method to design credit risk rating models for corporate entities using a meta-algorithm which exploits information embedded in expert-assigned credit ratings to rank customers.
Stressing of migration matrixes for International Financial Reporting Standard 9 and Internal Capital Adequacy Assessment Process calculations
This paper demonstrates that correlation estimates are sensitive to model assumptions and estimation methodology by comparing three methods used to stress rating transition matrixes.
Generalized additive modeling of the credit risk of Korean personal bank loans
The authors demonstrate a nonlinear impact of loan and borrower characteristics when applying a GAM framework to personal loans taken from a Korean bank.
Stressed distance to default and default risk
The authors propose a stressed version of distance to default to measure time-varying corporate default risk in the event of a systematic stress scenario.
A three-factor hazard rate model for single-name credit default swap pricing
The authors propose a reduced-form model in which the evolution of the risk-neutral hazard rate is driven by three risk factors.
Repo haircuts and economic capital: a theory of repo pricing
The author proposes a repo haircut model that will identify capital for repo default risk as the main driver of repo spreads and allow investors to settle at an optimal combination of the haircut and repo rate.
Merton’s model with recovery risk
By adding a correlated risk driver to Merton's model for corporate bond pricing, the authors model the empirically observed recovery risk premium.
How a credit run affects asset correlation
This paper analyzes how soaring demand in the lending market shortly before a financial crisis can affect one of the main parameters in the internal ratings-based approach: the asset correlation.
The loss optimization of loan recovery decision times using forecast cashflows
In this paper, a theoretical method is empirically illustrated in finding the best time to forsake a loan such that the overall credit loss is minimized.
On comprehensive balance sheet stress testing and net interest income risk attribution
In this paper the authors propose a framework for granular-level stressed net interest income calculation and profit-and-loss risk attribution.
A structural credit risk model based on purchase order information
This paper proposes a credit risk model based on purchase order information to address the deficiencies of monitoring methods that use only financial statements.
Bank-sourced transition matrixes: are banks’ internal credit risk estimates Markovian?
This study explores banks’ internal credit risk estimates and the associated banksourced transition matrixes.
Covid-19 and the credit cycle: 2020 revisited and 2021 outlook
This study continues the author’s examination and forecasts as to the impact of Covid-19 on the US credit cycle after one and a half years since the pandemic first began.
Customer churn prediction for commercial banks using customer-value-weighted machine learning models
In this paper the authors propose a framework to address the issue of customer churn prediction, and they quantify customer values with the use of an improved customer value model.
Does economic policy uncertainty exacerbate corporate financial distress risk?
This paper adds to the literature on factors driving distress risk and the economic consequences of economic policy uncertainty, and it provides a basis for enterprises to respond to changes in policies.
Incorporating small-sample defaults history in loss given default models
This paper proposes a methodology for estimating loss given default (LGD) that accounts for small default sample sizes.
