Deriving the Term Structure of Banking Crisis Risk with a Compound Option Approach: The Case of Kazakhstan
Stefan Eichler, Alexander Karmann, Dominik Maltritz
Discussion paper, Series 2: Banking and financial studies, No. 01/2010,
No. 1,
2010
Abstract
We use a compound option-based structural credit risk model to infer a term structure of banking crisis risk from market data on bank stocks in daily frequency. Considering debt service payments with different maturities this term structure assigns a separate estimator for short- and long-term default risk to each maturity. Applying the Duan (1994) maximum likelihood approach, we find for Kazakhstan that the overall crisis probability was mainly driven by short-term risk, which increased from 25% in March 2007 to 80% in December 2008. Concurrently, the long-term default risk increased from 20% to only 25% during the same period.
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The Identification of Technology Regimes in Banking: Implications for the Market Power-Fragility Nexus
Michael Koetter, Tigran Poghosyan
Journal of Banking and Finance,
No. 8,
2009
Abstract
Neglecting the existence of different technologies in banking can contaminate efficiency, market power, and other performance measures. By simultaneously estimating (i) technology regimes conditional on exogenous factors, (ii) efficiency conditional on risk management, and (iii) Lerner indices of German banks, we identify three distinct technology regimes: Public & Retail, Small & Specialized, and Universal & Relationship. System estimation at the regional level reveals that greater bank market power increases bank profitability but also fosters corporate defaults. Corporate defaults, in turn, lead to higher probabilities of bank distress, which supports the market power-fragility hypothesis.
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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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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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The Loss Distribution of the Entrepreneurial Bad Debt Risk – a Simulation-based Model
Henry Dannenberg
IWH Discussion Papers,
No. 10,
2006
Abstract
The risk of bad debt losses evolves for companies which grant payment targets. Possible losses have to be covered by these companies equity and liquidity reserves. The question of how to quantify the level of risk of bad debt losses will be discussed in this paper. Input values of this risk are the probability of default, exposure at default and loss given default. It is shown how companies can derive probability functions to describe uncertainty and variability for each input value. Based on these probability functions a simulation model is developed to quantify the risk of bad debt losses. Based on an empirical study probability functions for probability of default and loss given default are presented.
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