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Predictive Dynamic Models for SMEs

  • Silvia FiginiEmail author
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Considering the fundamental role played by small and medium sized enterprises (namely SMEs) in the economy of many countries and the considerable attention placed on them in the new Basel Capital Accord, we analyze a set of classical and Bayesian longitudinal models to predict SME default probability. In this contribution we present a real application based on a panel data set of German SMEs provided in our Musing European project by Creditreform, which is one of the major rating agencies for SMEs in Germany. Creditreform deals with balance sheet services, credit risk and portfolio analyses as well as consultation and support for the development of internal rating systems.

Keywords

Credit Risk Linear Predictor Financial Ratio Default Probability Credit Scoring 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The author acknowledge financial support from the MIUR-FIRB 2006–2009 and Musing.

I am grateful to Prof. Paolo Giudici for the useful suggestions.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of Statistics and Applied Economics L. LentiUniversity of PaviaPaviaItaly

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