Variable Selection In Forecasting Models For Corporate Bankruptcy
AbstractIn 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.
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Bibliographic InfoPaper provided by Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno in its series Working Papers with number 3_216.
Date of creation: Nov 2010
Date of revision:
Publication status: Published in Working Papers, Novembre 2010, pages 1-43
Forecasting; Default Risk; Variable Selection; Shrinkage; Lasso.;
Find related papers by JEL classification:
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
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