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Cyclical adjustment of point-in-time PD / S. Ingolfsson in Journal of the operational research society (JORS), Vol. 61 N° 3 (Mars 2010) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 61 N° 3 (Mars 2010) . - pp. 374–380 Titre : Cyclical adjustment of point-in-time PD Type de document : texte imprimé Auteurs : S. Ingolfsson, Auteur ; B. T. Elvarsson, Auteur Année de publication : 2011 Article en page(s) : pp. 374–380 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Banking  Risk  Capital  budgeting  Time  series  Forecasting Index. décimale : 001.424 Résumé : Banking regulation stipulates that to calculate minimum capital requirements a long-term average of annual default probability (PD) should be used. Typically, logistic regression is applied with a 12-month sample period to obtain retail PD estimates. Thus the output will reflect the default rate in the sample, and not the long-term average. The ensuing calibration problem is addressed in the paper by a ‘variable scalar methodology’, based on an actual application in a commercial bank. Using quarterly intra-bank loss data over 15 years, a state-space model of the credit cycle is estimated by a Kalman filter, resulting in a structural decomposition of the credit cycle. This yields an adjustment factor for each point in the cycle for each of two client segments. The regulatory compliance aspects of such a framework, as well as some practical issues are presented and discussed. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n3/abs/jors2009136a.html [article] Cyclical adjustment of point-in-time PD [texte imprimé] / S. Ingolfsson, Auteur ; B. T. Elvarsson, Auteur . - 2011 . - pp. 374–380. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 3 (Mars 2010) . - pp. 374–380 Mots-clés : Banking  Risk  Capital  budgeting  Time  series  Forecasting Index. décimale : 001.424 Résumé : Banking regulation stipulates that to calculate minimum capital requirements a long-term average of annual default probability (PD) should be used. Typically, logistic regression is applied with a 12-month sample period to obtain retail PD estimates. Thus the output will reflect the default rate in the sample, and not the long-term average. The ensuing calibration problem is addressed in the paper by a ‘variable scalar methodology’, based on an actual application in a commercial bank. Using quarterly intra-bank loss data over 15 years, a state-space model of the credit cycle is estimated by a Kalman filter, resulting in a structural decomposition of the credit cycle. This yields an adjustment factor for each point in the cycle for each of two client segments. The regulatory compliance aspects of such a framework, as well as some practical issues are presented and discussed. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n3/abs/jors2009136a.html