Journal of Credit Risk

This latest issue of The Journal of Credit Risk includes four papers.

The first paper in this issue by Leif Andersen, Michael Pykhtin and Alexander Sokol, entitled ‘Rethinking the Margin Period of Risk’, describes a new framework for modeling collateralized exposure under an International Swaps and Derivatives Association Master Agreement with a Credit Support Annex. The paper comprehensively covers the topic of MPR, one of the key modelling ingredients to quantify CCR exposure from pricing and risk perspectives. The analysis also includes an overview of the most common legal, operational and modelling challenges and misconceptions; providing useful thoughts on how to address them. 

In ‘Creditwatches and their impact on financial markets’, Florian Kiesel investigates financial market’s behaviour in the period between credit‐watch listing and the actual rating change. The paper finds no significant pattern in stock returns behaviour and a continuously increasing CDS spread following negative watch announcements. The paper provides some new and novel insights on the subject.

The reform of the Italian insolvency law in 2005 introduced the troubled debt restructuring procedure as a means to restore companies that are in financial distress and avoid potential liquidation. The success of this procedure depends strictly on the timeliness of intervention. Therefore, the availability of a prediction tool appears to be crucial. The third paper, ‘Financial distress pre-warning indicators: a case study on Italian listed companies’ by Francesco De Luca and Enrica Meschieri  focuses on the ability of accounting ratios to predict the financial distress status of a firm as defined by the law.

In the final paper in this issue, ‘Stochastic loss given default and exposure at default in a structural model of portfolio credit risk’, Florian Kaposty, Matthias Löderbusch and Jakob Maciag develop a factor-type latent variable model for portfolio credit risk that accounts for stochastically dependent probability of default (PD), loss given default (LGD) and exposure at default (EAD) at both the systematic and borrower specific levels. The paper makes a significant contribution to the field of credit risk modelling.