mycoreobjectrosdok_disshab_0000001780rosdok_disshab_0000001780rosdokdisshabrosdok_derivate_00000377432023-08-08T10:08:14.612Z2017-09-26T06:11:22.780ZadministratoreditorDpublished1rosdok_derivate_0000037743truetruederivate_types:fulltextVolltextfulltextwf_edit_epub wf_register_epubstate:publishedstate:publishedveröffentlichtpublishedrosdok/id00001958898495938MODS updated during RosDok migration in June 2021DissertationHochschulschrift1114925500LavriLabi1978-VerfasserInautModeling default probability in credit portfoliosevidence based on debt securities issuers in Germanyen140879455Prof. Dr.RafaelWeißbachUniversität Rostock, Lehrstuhl für Statistik und ÖkonometrieAkademischeR BetreuerIndgs121081648Prof. Dr.DorisNeubergerUniversität Rostock, Lehrstuhl für Geld und KreditAkademischeR BetreuerIndgs2140292-9Universität RostockWirtschafts- und Sozialwissenschaftliche FakultätGrad-verleihende Institutiondgg10.18453/rosdok_id00001958http://purl.uni-rostock.de/rosdok/id00001958urn:nbn:de:gbv:28-diss2017-0122-9330 WirtschaftWirtschafts- und Sozialwissenschaftliche Fakultätfrei zugänglich (Open Access)Lizenz Metadaten: CC0Nutzungsrechte erteiltalle Rechte vorbehaltenUniversität RostockRostock2017monographic20162017Universitätsbibliothek RostockRostock20172017Implementation of reliable rating systems for small credit portfolio is hindered by non-observed default events in databases and short time series of data available. In this study we propose an approach to handle those two challenges while developing rating systems. We further extend the approach by estimating systematic risk, that is, co-movements of creditworthiness of debt securities' issuers over time. Based on financial information from the PSVaG's debt securities portfolio, we could show that including a systematic risk component significantly increase the model accuracy.credit ratingcredit riskprobability of default (PD)systematic riskdefault correlationgeneralised linear mixed model (GLMM)double exponential smoothingUniversitätsbibliothek Rostockhttp://purl.uni-rostock.de/rosdok/id00001958doctype:epubdoctype:epubDokumenttypDocument typedoctype:epub.dissertationdoctype:epub.dissertationDissertationdoctoral thesisdiniPublType:doctoralThesis diniPublType2022:PhDThesis XMetaDissPlusThesisLevel:thesis.doctoralinfo:eu-repo/semantics/doctoralThesisdocumentnatureOfContent:ppn_105825778natureOfContent:ppn_105825778HochschulschriftdiniPublType2022:DoctoralThesisdiniPublType2022:DoctoralThesisDissertation oder HabilitationDoctoral thesisDRIVERdiniPublType2022:PhDThesisdiniPublType2022:PhDThesisDissertationPhD thesisKDSF (Pu34)XMetaDissPlusThesisLevel:thesis.doctoralXMetaDissPlusThesisLevel:thesis.doctoralDoktorarbeitdoctoral thesisrfc5646:enrfc5646:enEnglischEnglishengengSDNB:330SDNB:330330 Wirtschaft330 Economicsinstitution:unirostockinstitution:unirostockUniversität RostockUniversity of RostockUniversität RostockUniversität RostockUni.Rostockhttp://d-nb.info/gnd/38329-6institution:unirostock.wsfinstitution:unirostock.wsfWirtschafts- und Sozialwissenschaftliche FakultätFaculty of Economics and Social SciencesUniversität Rostock. 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In this study we propose an approach to handle those two challenges while developing rating systems. We further extend the approach by estimating systematic risk, that is, co-movements of creditworthiness of debt securities' issuers over time. 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In this study we propose an approach to handle those two challenges while developing rating systems. We further extend the approach by estimating systematic risk, that is, co-movements of creditworthiness of debt securities' issuers over time. 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In this study we propose an approach to handle those two challenges while developing rating systems. We further extend the approach by estimating systematic risk, that is, co-movements of creditworthiness of debt securities' issuers over time. Based on financial information from the PSVaG's debt securities portfolio, we could show that including a systematic risk component significantly increase the model accuracy.20172017[xslt]Saxonrosdok/id00001958https://purl.uni-rostock.de/rosdok/id0000195889849593810.18453/rosdok_id00001958urn:nbn:de:gbv:28-diss2017-0122-9Lavri LabiLabi LavriModeling default probability in credit portfolios : evidence based on debt securities issuers in GermanyDissertationdoctoral thesisUniversität Rostock, 2017Implementation of reliable rating systems for small credit portfolio is hindered by non-observed default events in databases and short time series of data available. In this study we propose an approach to handle those two challenges while developing rating systems. We further extend the approach by…Lavri LabiModeling default probability in credit portfoliosevidence based on debt securities issuers in GermanyUniversitätsbibliothek Rostockhttp://purl.uni-rostock.de/rosdok/id000019581114925500LavriLabi1978-VerfasserInaut140879455Prof. Dr.RafaelWeißbachUniversität Rostock, Lehrstuhl für Statistik und ÖkonometrieAkademischeR BetreuerIndgs121081648Prof. Dr.DorisNeubergerUniversität Rostock, Lehrstuhl für Geld und KreditAkademischeR BetreuerIndgs2140292-9Universität RostockWirtschafts- und Sozialwissenschaftliche FakultätGrad-verleihende Institutiondgg[doi]10.18453/rosdok_id00001958[purl]http://purl.uni-rostock.de/rosdok/id00001958[urn]urn:nbn:de:gbv:28-diss2017-0122-9open_access20172017epoch:21th_centuryrfc5646:endoctype:epub.dissertationaccesscondition:openaccessSDNB:330institution:unirostock.wsfstate:published