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An artificial neural network approach for assigning rating judgements to Italian Small Firms

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Abstract

Based on new regulations of Basel II Accord in 2004, banks and financial nstitutions have now the possibility to develop internal rating systems with the aim of correctly udging financial health status of firms. This study analyses the situation of Italian small firms that are difficult to judge because their economic and financial data are often not available. The intend of this work is to propose a simulation framework to give a rating judgements to firms presenting poor financial information. The model assigns a rating judgement that is a simulated counterpart of that done by Bureau van Dijk-K Finance (BvD). Assigning rating score to small firms with problem of poor availability of financial data is really problematic. Nevertheless, in Italy the majority of firms are small and there is not a law that requires to firms to deposit balance-sheet in a detailed form. For this reason the model proposed in this work is a three-layer framework that allows us to assign ating judgements to small enterprises using simple balance-sheet data.

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Paper provided by Institute for Economic Research on Firms and Growth - Moncalieri (TO) in its series CERIS Working Paper with number 201104.

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Length: 26 pages
Date of creation: Jun 2011
Date of revision:
Handle: RePEc:csc:cerisp:201104

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Keywords: rating judgements; artificial neural networks; feature selection;

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  1. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
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  6. Olmeda, Ignacio & Fernandez, Eugenio, 1997. "Hybrid Classifiers for Financial Multicriteria Decision Making: The Case of Bankruptcy Prediction," Computational Economics, Society for Computational Economics, vol. 10(4), pages 317-35, November.
  7. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
  8. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
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