{"title":"Modeling Credit Losses for Multiple Loan Portfolios","authors":"Petr Gapko, M. Šmíd","doi":"10.2139/ssrn.3117107","DOIUrl":null,"url":null,"abstract":"We propose a dynamic structural model of credit risk of multiple loan portfolios. In line with Merton, Vasicek and Pykhtin, we assume that a loan defaults if the assets of the debtor fall below his liabilities, and the subsequent loss is determined by the collateral value. For each loan, the assets, liabilities and the collateral value each depends on a common and an individual factor. By applying our model to two nationwide United States loan portfolios with real estate collateral, we demonstrate its considerable predicting power and show that, similarly to calculations under prudential regulation, it can be used within financial institutions to measure credit risk under various macroeconomic situations and different probability levels. This makes the model usable for quantification of loan loss allowances under IFRS9 or for stress tests of credit risk.","PeriodicalId":11689,"journal":{"name":"ERN: Commercial Banks (Topic)","volume":"215 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Commercial Banks (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3117107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We propose a dynamic structural model of credit risk of multiple loan portfolios. In line with Merton, Vasicek and Pykhtin, we assume that a loan defaults if the assets of the debtor fall below his liabilities, and the subsequent loss is determined by the collateral value. For each loan, the assets, liabilities and the collateral value each depends on a common and an individual factor. By applying our model to two nationwide United States loan portfolios with real estate collateral, we demonstrate its considerable predicting power and show that, similarly to calculations under prudential regulation, it can be used within financial institutions to measure credit risk under various macroeconomic situations and different probability levels. This makes the model usable for quantification of loan loss allowances under IFRS9 or for stress tests of credit risk.