Estimation Uncertainty in Credit Risk Assessment: Comparison of Credit Risk Using Bootstrapping and an Asymptotic Approach
Henry Dannenberg
IWH Discussion Papers,
No. 3,
2009
Abstract
For credit risk assessment, probability of default and correlation have to be estimated simultaneously. However, these estimates are uncertain. To assess this uncertainty the literature has discussed the use of asymptotic confidence regions. This kind of region though needs a long credit history for exact assessment. An alternative method to generate a confidence region for a short credit history is bootstrapping. Hence, it could be more appropriate to assess estimation uncertainty with bootstrapping than with asymptotic methods if only a short credit history is available. Based on a simulation study, it is analyzed how many periods should be available for assessing credit risk – taking account of estimation uncertainty – if bootstrapping and a Wald confidence region shall achieve similar results. This article shows that more than 100 cycles have to be available for similar results.
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Vergleich der Kreditrisikobewertung bei Berücksichtigung von Schätzunsicherheit und Korrelation – Welche Risikokomponente Sollten Unternehmen bei der Bewertung von Forderungsportfoliorisiken wann berücksichtigen?
Henry Dannenberg
Die Unternehmung Swiss Journal of Business Research and Practice,
2008
Abstract
The use of probability of default estimates to assess the risks of a credit portfolio should not ignore estimation uncertainty. The latter can be quantified by confidence intervals. But assumptions about dependencies of these intervals are inconsistent with assumptions of conventional credit portfolio models. Based on simulation studies this paper shows that a model which includes estimation uncertainty but ignores default correlation might estimate the real credit risk more correctly than a model that implicates default correlation but ignore estimation uncertainty. The latter is a trait of conventional credit portfolio models. In this paper quantifying of estimation uncertainty based on the idea of confidence intervals and the underlying probability distributions of these intervals.
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Evaluating the German (New Keynesian) Phillips Curve
Rolf Scheufele
IWH Discussion Papers,
No. 10,
2008
Abstract
This paper evaluates the New Keynesian Phillips Curve (NKPC) and its hybrid
variant within a limited information framework for Germany. The main interest rests on the average frequency of price re-optimization of firms. We use the labor income share as the driving variable and consider a source of real rigidity by allowing for a fixed firm-specific capital stock. A GMM estimation strategy is employed as well as an identification robust method that is based upon the Anderson-Rubin statistic. We find out that the German Phillips Curve is purely forward looking. Moreover, our point estimates are consistent with the view that firms re-optimize prices every two to three quarters. While these estimates seem plausible from an economic point of view, the uncertainties around these estimates are very large and also consistent with perfect nominal price rigidity where firms never re-optimize prices. This analysis also offers some explanations why previous results for the German NKPC based on GMM differ considerably. First, standard GMM results are very sensitive to the way how orthogonality conditions are formulated. Additionally, model misspecifications may be left undetected by conventional J tests. Taken together, this analysis points out
the need for identification robust methods to get reliable estimates for the NKPC.
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Forecasting the CO2 certificate price risk
Henry Dannenberg, Wilfried Ehrenfeld
IWH Discussion Papers,
No. 5,
2008
Abstract
Modeling the price risk of CO2 certificates is one important aspect of integral corporate risk management related to emissions trading. The paper presents a risk model which may be the basis for evaluating the risk of emission certificate prices. We assume that the certificate price is determined by the expected marginal CO2 abatement costs prevailing at the current trade period and stochastically fluctuates around the respective level as returned from the mean reversion process. Due to uncertainties about future environmental states we suppose that within one trade period, erratic changes in the expected marginal abatement costs may occur leading to shifts in the price level. The aim of the work is to model the erratic changes of the expected reversion level and to estimate the parameters of the mean reversion process.
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Schätzunsicherheit oder Korrelation, Welche Risikokomponente sollten Unternehmen bei der Bewertung von Kreditportfoliorisiken wann berücksichtigen?
Henry Dannenberg
IWH Discussion Papers,
No. 5,
2007
Abstract
The use of probability of default estimates to assess the risks of a credit portfolio should not ignore estimation uncertainty. The latter can be quantified by confidence intervals. But assumptions about dependencies of these intervals are inconsistent with assumptions of conventional credit portfolio models. Based on simulation studies this paper shows, that a model which include estimation uncertainty but ignore default correlation might estimate the real credit risk more correctly than a model that implicates default correlation but ignore estimation uncertainty. The latter is a trait of conventional credit portfolio models. In this paper quantifying of estimation uncertainty based on the idea of confidence intervals and the underlying probability distributions of these intervals.
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