Predicting loss severities for residential mortgage loans: a three-step selection approach

DOI10.1016/J.EJOR.2018.02.057zbMath1403.91360OpenAlexW2794349255WikidataQ130139599 ScholiaQ130139599MaRDI QIDQ1754749

Daniel Rösch, Harald Scheule, Hung Xuan Do

Publication date: 31 May 2018

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2018.02.057

zbMATH Keywords

defaultanalyticsselection modelloss given defaultresidential mortgage

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Credit risk (91G40)

Related Items (2)

The profitability of online loans: a competing risks analysis on default and prepayment ⋮ Loss given default decomposition using mixture distributions of in-default events

Cites Work

• Cure events in default prediction
• Accuracy of mortgage portfolio risk forecasts during financial crises
• Mixture cure models in credit scoring: if and when borrowers default
• Cost-based feature selection for support vector machines: an application in credit scoring
• Credit risk evaluation using multi-criteria optimization classifier with kernel, fuzzification and penalty factors
• Recent developments in consumer credit risk assessment
• Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation
• Credit scoring with macroeconomic variables using survival analysis
• How Do Foreclosures Exacerbate Housing Downturns?

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