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Predicting SME's default: some old facts and a new idea

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Predicting SME's default: some old facts and a new idea

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dc.contributor.author Crosato, Lisa es_ES
dc.contributor.author Domenech, Josep es_ES
dc.contributor.author Liberati, Caterina es_ES
dc.date.accessioned 2020-09-08T12:21:09Z
dc.date.available 2020-09-08T12:21:09Z
dc.date.issued 2020-07-10
dc.identifier.isbn 9788490488324
dc.identifier.uri http://hdl.handle.net/10251/149606
dc.description.abstract [EN] The Small Business Act of the European Commission in 2008 acknowledge s the key role of Small and Medium Enterprises (SMEs) in the EU economy. Th is is particularly relevant for Italy, which has the largest share of SMEs in Europe, as well as for other countries such as Portugal, Spain and Greece. On the other hand, SMEs experience more difficulties in their early stages mainly due to high market competition and credit constraints, as highlighted by Fritsch and Weyh (2006). For these reasons, the study of SMEs default risk is always relevant. There are several papers studying firm default factors in a single country (see Ciampi, 2015, Fantazzini and Figini, 2009, Flix and dos Santos, 2018). The literature concentrates mainly on financial indicators built on businesses’ balance sheets, which are available about two years late wi th respect to their reference period. This diminishes the significance of the results, both for credit risk and policy aims, and particularly in a forecasting perspective. The purpose of this paper is to provide a preliminary study on a sample of spanish firms selected from the SABI, Sistema de Análisis de Balances Ibéricos, which is listed among Bureau van Dijk databases. The analysis will be carried out according to both parametric and non-parametric discrimination techniques, with the standard construction of a training set on which to build a model and a validation set to test the validity and robustness of the results, and, in the end, the reliability of the model in predicting default. Finally we present a new proposal: a scheme to understand to what ext ent firms’ default can be predicted by substituting the traditional data sour ces (offline information) with data collected from their corporate websites (onli ne information) in order to exploit more up-to-date information. es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Web data es_ES
dc.subject Internet data es_ES
dc.subject Big data es_ES
dc.subject Qca es_ES
dc.subject Pls es_ES
dc.subject Sem es_ES
dc.subject Conference es_ES
dc.subject Default risk es_ES
dc.subject SMEs es_ES
dc.subject Web scraping es_ES
dc.subject Corporate websites es_ES
dc.title Predicting SME's default: some old facts and a new idea es_ES
dc.type Comunicación en congreso es_ES
dc.type Otros es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Crosato, L.; Domenech, J.; Liberati, C. (2020). Predicting SME's default: some old facts and a new idea. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/149606 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Julio 08-09,2020 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2020/paper/view/10939 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\10939 es_ES


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