Modeling default probability in credit portfolios : evidence based on debt securities issuers in Germany

Lavri Labi

doi:10.18453/rosdok_id00001958

Lavri Labi

Modeling default probability in credit portfolios : evidence based on debt securities issuers in Germany

Universität Rostock, 2017

https://doi.org/10.18453/rosdok_id00001958

Abstract: Implementation 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.

Dissertation Freier Zugang

Titel:

Modeling default probability in credit portfolios: evidence based on debt securities issuers in Germany

Beteiligte Personen:

Lavri Labi[VerfasserIn]
	1114925500
Rafael Weißbach , Prof. Dr.[AkademischeR BetreuerIn]
	140879455
	Universität Rostock, Lehrstuhl für Statistik und Ökonometrie
Doris Neuberger , Prof. Dr.[AkademischeR BetreuerIn]
	121081648
	Universität Rostock, Lehrstuhl für Geld und Kredit

Beteiligte Körperschaften:

Universität Rostock, Wirtschafts- und Sozialwissenschaftliche Fakultät[Grad-verleihende Institution]
	2140292-9

Zusammenfassung:

Implementation 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. [Englisch]

Dokumenttyp:

Dissertation

Einrichtung:

Wirtschafts- und Sozialwissenschaftliche Fakultät

Sprache:

Englisch

Sachgruppe der DNB:

330 Wirtschaft

Veröffentlichung /
Entstehung:

Rostock

Rostock: Universität Rostock

2017