Different models have been proposed in corporate finance literature for predicting the risk of firm bankruptcy and insolvency. In spite of the large amount of empirical findings, significant issues are still unsolved. In this paper we developed dynamic statistical models for bankruptcy prediction of Italian firms in the industrial sector using financial indicators. The model specification has been obtained via different variable selection techniques and the predictive accuracy of the proposed default risk models has been evaluated at various horizons by means of different accuracy measures. The reached results give evidence that dynamical models have a better performance in any of the scenarios considered.

Dynamic Statistical Models for Corporate Failure Prediction in Italy (Vol. 8, n.8)

AMENDOLA, Alessandra;RESTAINO, MARIALUISA;SENSINI, LUCA
2012

Abstract

Different models have been proposed in corporate finance literature for predicting the risk of firm bankruptcy and insolvency. In spite of the large amount of empirical findings, significant issues are still unsolved. In this paper we developed dynamic statistical models for bankruptcy prediction of Italian firms in the industrial sector using financial indicators. The model specification has been obtained via different variable selection techniques and the predictive accuracy of the proposed default risk models has been evaluated at various horizons by means of different accuracy measures. The reached results give evidence that dynamical models have a better performance in any of the scenarios considered.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/3753078
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