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Stochastische Unternehmensmodelle als Kern innovativer Ratingsysteme

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  • Blum, Ulrich
  • Gleißner, Werner
  • Leibbrand, Frank

Abstract

Auf der Grundlage einer Stichprobe von 105 sächsischen Unternehmen wird deren Zukunftsfähigkeit mit Hilfe einer neuen Ratingtechnologie analysiert. Diese basiert - neben klassischen Analysewerkzeugen - auf einer direkten Einbeziehung von Risikogesichtspunkten und einer stochastischen Unternehmensmodellierung. Die Ergebnisse belegen, daß das Verfahren gegenüber den bisherigen Ansätzen zusätzlichen und ökonomisch bedeutsamen Erklärungsgehalt besitzt. Über den Aspekt Basel-II hinaus ist es insbesondere möglich, langfristige strategisch angelegte Entwicklungsprozesse nachzuzeichnen.

Suggested Citation

  • Blum, Ulrich & Gleißner, Werner & Leibbrand, Frank, 2005. "Stochastische Unternehmensmodelle als Kern innovativer Ratingsysteme," IWH Discussion Papers 6/2005, Halle Institute for Economic Research (IWH).
    • Handle: RePEc:zbw:iwhdps:iwh-6-05
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    File URL: https://www.econstor.eu/bitstream/10419/23745/1/6-05.pdf
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    References listed on IDEAS

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    1. Margaret Insley, 2003. "On the option to invest in pollution control under a regime of tradable emissions allowances," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 860-883, November.
    2. Bemmann, Martin, 2005. "Verbesserung der Vergleichbarkeit von Schätzgüteergebnissen von Insolvenzprognosestudien," Dresden Discussion Paper Series in Economics 08/05, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    3. Friedrich, B. Cornelia, 2004. "Competition and the Evolution of Market Structure in the E-conomy : A Simulation Analysis," Dresden Discussion Paper Series in Economics 02/04, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    4. Ulrich Blum & Frank Leibbrand, 2003. "Rating als Strategie- und Risikoberatung für kleine und mittlere Unternehmen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(03), pages 26-36, 06.
    5. Ulrich Blum & Frank Leibbrand, 2003. "Rating als Strategie- und Risikoberatung für kleine und mittlere Unternehmen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(03), pages .26-36, June.
    6. William F. Sharpe, 1963. "A Simplified Model for Portfolio Analysis," Management Science, INFORMS, vol. 9(2), pages 277-293, January.
    7. Norden, Lars & Weber, Martin, 2004. "Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2813-2843, November.
    8. Weber, Martin & Krahnen, Jan Pieter & Voßmann, Frank, 1998. "Risikomessung im Kreditgeschäft: Eine empirische Analyse bankinterner Ratingverfahren," Sonderforschungsbereich 504 Publications 98-45, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
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    Cited by:

    1. Thomas Günther & Werner Gleißner & Christian Walkshäusl, 2020. "What happened to financially sustainable firms in the Corona crisis?," Sustainability Nexus Forum, Springer, vol. 28(3), pages 83-90, December.

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    More about this item

    Keywords

    Rating; Sachsen; Unternehmensmodellierung; Stochastik; Risiko; Erfolgsfaktoren; rating; Saxony; modelling of enterprises; stochastics; risk; sucsess factors;
    All these keywords.

    JEL classification:

    • M4 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting
    • L6 - Industrial Organization - - Industry Studies: Manufacturing
    • G2 - Financial Economics - - Financial Institutions and Services

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