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Die Verlustverteilung des unternehmerischen Forderungsausfallrisikos – Eine simulationsbasierte Modellierung

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  • Henry Dannenberg

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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Bibliographic Info

Paper provided by Halle Institute for Economic Research in its series IWH Discussion Papers with number 10.

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Date of creation: May 2006
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Handle: RePEc:iwh:dispap:10-06

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Keywords: simulation; risk of bad debt losses; risk assessment;

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  1. Henry Dannenberg, 2005. "Sind Kreditoreneigenschaften als Indikatoren zur Quantifizierung der Höhe des Forderungsausfallrisikos nutzbar?," Wirtschaft im Wandel, Halle Institute for Economic Research, vol. 11(12), pages 388-396.
  2. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, 07.
  3. Bemmann, Martin, 2005. "Verbesserung der Vergleichbarkeit von Schätzgüteergebnissen von Insolvenzprognosestudien," Dresden Discussion Paper Series in Economics 08/05, Dresden University of Technology, Faculty of Business and Economics, Department of Economics.
  4. Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  5. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
  6. Kleijnen, J.P.C., 1997. "Sensitivity analysis and related analyses: A review of some statistical techniques," Open Access publications from Tilburg University urn:nbn:nl:ui:12-73904, Tilburg University.
  7. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
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