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 focusses 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 the following, but not limited to, topics:
- 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
Estimating credit risk parameters using ensemble learning methods: an empirical study on loss given default
This study investigates two well-established ensemble learning methods: Stochastic Gradient Boosting and Random Forest, and proposed two new ensembles.
This paper analyzes the validity of using the loan-to-value (LTV) ratio to explain the behavior of mortgage borrowers at an empirical level.
The authors demonstrate how different credit risk models can be efficiently implemented for scenario analysis and stress testing execution with concrete application examples.
This paper presents a rigorously motivated pricing equation for derivatives.
This paper analyses whether the double default treatment under Basel II is appropriate to capture the asymmetric relationship between an obligor and its guarantor.
Fitting a distribution to value-at-risk and expected shortfall, with an application to covered bonds
This paper suggests simple and intuitive models for covered bonds that allow quantitative assessment of expected loss and the impact of asset encumbrance.
The authors develop a framework that consistently and fully integrates the market, credit and country transfer risks of a general portfolio of financial assets in a multi-period setup.
This paper analyzes whether the financial crisis of 2007–9 had an effect on the mispricing of CLNs.
This paper analyzes the pricing of contingent credit default swaps.
A credit portfolio framework under dependent risk parameters: probability of default, loss given default and exposure at default
This paper introduces a credit portfolio framework that allows for dependencies between default probabilities, secured and unsecured recovery rates and exposures at default (EADs).
This paper examines the predictive value of medical collections in assessing consumer creditworthiness with credit scoring models.
This paper proposes a semi-analytic approach to quantify the default risk associated with Money-Market Fund (MMF) portfolios.
This paper contributes to the literature for mixture models by leveraging an efficient algorithm for computing the density function of the loss distribution and extending the model in two key areas: constructing the systemic variable from a continuous-time...
An analytical value-at-risk approach for a credit portfolio with liquidity horizon and portfolio rebalancing
The authors provide a two-period analytical value-at-risk approach for credit portfolios with a liquidity horizon and a constant level of risk.
This paper puts forward an ensemble approach for asset correlations.
The article discusses the use of counting processes for retail (mortgage) default modeling.
This paper analyzes the theoretical properties and statistical behavior of credit default swap (CDS) premiums over time.
Hermite approximations in credit portfolio modeling with probability of default–loss given default correlation
The authors present an analytic framework for credit portfolio modeling using Hermite expansions.
This paper examines the performance of MM, ML and OLS estimators through Monte Carlo experiments for various sample sizes and correlation values when the true data is from non-Gaussian processes.
This paper presents the set-up of a behavioral credit-scoring model, and estimates such a model using an auto loan data set of one of the largest multinational financial institutions based in France.
This paper develops a method for estimating the full systematic risk of bonds and thereby enables a fuller understanding of the risk and return on fixed-income instruments.
The relationship between counterparty default and interest rate volatility and its impact on the credit risk of interest rate derivatives