La previsione delle insolvenze. Teorie, modelli, applicazioni alle società partecipate pubbliche

In recent years, a lot of attentioni spaid, in Italy, to the financial trouble of the public owned companies which are systematically financial distressed. Therefore,to monitor the financial situation of public owned companies is clearly usefull. To do this a bankrupt cyprediction model could be realized. The aim of this doctoral thesisis to realize a distress prediction model applied to a sample of Italian public owned companies. To achive this goal logit methodologies and multiple dicriminant analysis were employed to a sample of 460 public owned companies. Accounting data were selected over the period 2010-2014. To verify the model accuracy an holdout sample of 10 sound companies and 11 unsound companies is used. Results show that binary logit model outperform multiple discriminant analysis with a prediction accuracy of 98%. [edited by Author]