Financial ratings with scarce information: a neural network approach
| Autor: | Greta Falavigna |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Finance
Actuarial science Artificial neural network business.industry Process (engineering) Computer science General Engineering Basel II Computer Science Applications Work (electrical) Artificial Intelligence Financial information Rating judgements business Artificial Neural Networks financial ratings |
| Zdroj: | Computing in Economics and Finance, Londra, 15-17 luglio, 2010 info:cnr-pdr/source/autori:Falavigna G./congresso_nome:Computing in Economics and Finance/congresso_luogo:Londra, 15-17 luglio/congresso_data:2010/anno:2010/pagina_da:/pagina_a:/intervallo_pagine Expert systems with applications 39 (2012): 1784–1792. doi:10.1016/j.eswa.2011.08.074 info:cnr-pdr/source/autori:Falavigna G./titolo:Financial ratings with scarce information: A neural network approach/doi:10.1016%2Fj.eswa.2011.08.074/rivista:Expert systems with applications/anno:2012/pagina_da:1784/pagina_a:1792/intervallo_pagine:1784–1792/volume:39 Salone internazionale del libro, Torino, 13/05/2011 info:cnr-pdr/source/autori:Falavigna G/congresso_nome:Salone internazionale del libro/congresso_luogo:Torino/congresso_data:13%2F05%2F2011/anno:2011/pagina_da:/pagina_a:/intervallo_pagine |
| DOI: | 10.1016/j.eswa.2011.08.074 |
| Popis: | On a wake of Basel II Accord in 2004, banks and financial institutions can build an internal rating system. This work focuses on Italian small firms that are more hard to judge because quite often financial data are not simply available. The aim of this paper is to propose a simulation model for assigning rating judgements to these firms, using poor financial information. The proposed model produces a simulated counterpart of Bureau van Dijk-K Finance (BvD) rating judgements. It is clear that there are problems when small firms must be judged because it is difficult to obtain financial data; indeed in Italy these enterprises must deposit the balance-sheet in reduced form. Suggested methodology is a three-layer process where each of them is formed by, respectively, one, two and four feed-forward artificial neural networks with back-propagation algorithm. The proposed model is a good solution for evaluating small firms with poor financial information but not only: the research underlines and supports the ability of artificial neural networks of learning and reproducing some aspects or some features or behaviours of reality. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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