Variabile Selection in Forecasting Models for Corporate Bankruptcy

Alessandra Amendola (), Marialuisa Restaino () and Luca Sensini ()
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Luca Sensini: Dipartimento di Studi e Ricerche Aziendali (Management & Information Technology), Università degli Studi di Salerno

No 3_216, Working Papers from Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno

Abstract: In this paper we develop statistical models for bankruptcy prediction of Italian firms in the limited liability sector, using annual balance sheet information. Several issues involved in default risk analysis are investigated, such as the structure of the data-base, the sampling procedure and the influence of predictors. In particular we focus on the variable selection problem, comparing innovative techniques based on shrinkage with traditional stepwise methods. The predictive performance of the proposed default risk model has been evaluated by means of different accuracy measures. The results of the analysis, carried out on a data-set of financial ratios expressly created from a sample of industrial firms annual reports, give evidence in favor of the proposed model over traditional ones.

Keywords: Forecasting; Default Risk; Variable Selection; Shrinkage; Lasso. (search for similar items in EconPapers)
JEL-codes: C24 C40 G33 G34 (search for similar items in EconPapers)
Date: 2010-11
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Published in Working Papers, Novembre 2010, pages 1-43

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https://www.dises.unisa.it/RePEc/sep/wpaper/3_216.pdf First version, 2012

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