This paper focuses on the corporate stress testing models for credit risk.
A model combination approach to developing robust models for credit risk stress testing: an application to a stressed economy
This paper uses a model combination approach to develop robust macrofinancial models for credit risk stress testing.
Proposal to harmonise rules on debt stays and holdout creditors touches on sensitive issues
Risk Awards 2017: Guarantees and insurance help French bank cut RWAs by €3bn – and limit use of CDSs
This paper focuses on the ability of accounting ratios to predict the financial distress status of a firm as defined by the law.
Jonas Hirz, Uwe Schmock and Pavel Shevchenko present a summary of actuarial applications of the extended CreditRisk+ model
Barker, Dickinson, Lipton and Virmani propose a credit and liquidity risk model for CCPs
Combinations of models produce better NPL estimates in study of Greek crisis
Sponsored webinar: Moody's Analytics and Qlik
This paper explores the aggregation of different single ratings to a ‘consensus rating’ to get a higher precision of a debtor’s default probability. It builds upon the methodology published by Grün et al, 2013 and Lehmann and Tillich, 2016.
The authors analyze the impact of a decline in property prices that leads to stressed recovery rates for collateral on the loss given default (LGD) parameter in portfolios of mortgage loan.
Huge losses from the 2008 crisis can be seen as a short option position
This paper assesses the predictive ability of financial and nonfinancial variables for a long horizon in a large cross-sectional sample of Finnish firms
Sponsored by Oracle, Moody's Analytics and AxiomSL
Self-taught technology could push humans aside from some – or all – of the underwriting process
PeerIQ CEO Ram Ahluwalia shines a light on the world of peer-to-peer securitisation
Sponsored webinar: Oracle
Impact studies showing significant capital increase prompted committee rethink
Modeling corporate customers’ credit risk considering the ensemble approaches in multiclass classification: evidence from Iranian corporate credits
This paper introduces a model which enables lenders to develop specific policies for credit granting by predicting the solvency and insolvency rates of their corporate clients.
Sponsored content: SAS
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.
Political and prudential risks in huge bond-holdings force experts to consider new ideas
This paper analyzes the validity of using the loan-to-value (LTV) ratio to explain the behavior of mortgage borrowers at an empirical level.