Modelling Correlations in Portfolio Credit Risk

The risk of a credit portfolio depends crucially on correlations between the probability of default (PD) in different economic sectors. Often, PD correlations have to be estimated from relatively short time series of default rates, and the resulting estimation error hinders the detection of a signal. We present statistical evidence that PD correlations are well described by a (one-)factorial model. We suggest a method of parameter estimation which avoids in a controlled way the underestimation of correlation risk. Empirical evidence is presented that, in the framework of the CreditRisk+ model with integrated correlations, this method leads to an increased reliability of the economic capital estimate.Comment: 5 pages, 4 figure

Modelling correlations in credit portfolio risk II

The risk of a credit portfolio depends crucially on correlations between latent covariates, for instance the probability of default (PD) in different economic sectors. Often, correlations have to be estimated from relatively short time series, and the resulting estimation error hinders the detection of a signal. We suggest a general method of parameter estimation which avoids in a controlled way the underestimation of correlation risk. Empirical evidence is presented how, in the framework of the CreditRisk+ model with integrated correlations, this method leads to an increased economic capital estimate. Thus, the limits of detecting the portfolio's diversification potential are adequately reflected

Steuerklienteleffekte und Steuerstundungsoptionen auf dem deutschen Rentenmarkt - Ein Binomialbaummodell

Tax-Clientele Effects and Tax-Timing Options in the German Bond Market - A Binomial Tree Model Tax-clientele models consider the optimization problems of differentially taxed investors under a buy-and-hold assumption whereas tax-timing option models draw on homogeneously taxed investors with the opportunity of future asset trading at (ex ante) uncertain prices. In the latter models, optimal trading strategies imply a tax postponement in certain cases. Tian’s (1996) discrete-time dynamic trading model is the first to analyze future asset trading among differentially taxed investors. In this paper, the Tian (1996)-model, which is customized for the US-investor taxation, is adopted for German taxation rules. The Niederstwertrule that applies to German corporations requires a path-dependent valuation approach. The numerical (this being another American put-option pricing problem) results are: Under German taxation rules, too, tax-clientele effects have a significant impact on simulated asset prices. However, the benefits of tax postponement do not stem from future asset trading possibilities (as under US-investor taxation) but are generated by the Niederstwert-rule. There are no tax advantages from future asset trading over a simple buy-and-hold investment policy

Wider die falschen Kalkulationszinsen: zur Investitionsvorteilhaftigkeit bei periodenverschobener Steuerzahlung

Available from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel W 1039 (95.02) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Erwartungsbildung, Marktgleichgewicht und Zinsstruktur: ein einfaches Modell der Zinsspekulation

Available from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, D-21400 Kiel W 1039 (96.02) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Fuehrungsorganisation deutscher Grossunternehmungen: Gestaltungsalternativen und ihre empirische Relevanz

Available from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel W 549 (93.1) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Joint spatial analysis of gastrointestinal infectious diseases

A major obstacle in the spatial analysis of infectious disease surveillance data is the problem of under-reporting. This article investigates the possibility of inferring reporting rates through joint statistical modelling of several infectious diseases with different aetiologies. Once variation in under-reporting can be estimated, geographic risk patterns for infections associated with specific food vehicles may be discerned. We adopt the shared component model, proposed by Knorr-Held and Best for two chronic diseases and further extended by (Held L, Natario I, Fenton S, Rue H, Becker N. Towards joint disease mapping. Statistical Methods in Medical Research 2005b; 14: 61-82) for more than two chronic diseases to the infectious disease setting. Our goal is to estimate a shared component, common to all diseases, which may be interpreted as representing the spatial variation in reporting rates. Additional components are introduced to describe the real spatial variation of the different diseases. Of course, this interpretation is only allowed under specific assumptions, in particular, the geographical variation in under-reporting should be similar for the diseases considered. In addition, it is vital that the data do not contain large local outbreaks, so adjustment based on a time series method recently proposed by (Held L, Höhle M, Hofmann M. A statistical framework for the analysis of multivariate infectious disease surveillance data. Statistical Modelling 2005a; 5: 187-99) is made at a preliminary stage. We will illustrate our approach through the analysis of gastrointestinal diseases notification data obtained from the German infectious disease surveillance system, administered by the Robert Koch Institute in Berlin