A combined approach based on robust PCA to improve bankruptcy forecasting

Purpose Starting from a series of financial ratios analysis, this paper aims to build up two indices which take into account both the firm’s debt level and its sustainability to investigate if and to what extent the proposed indices are able to correctly predict firms’ financial bankruptcy probabili...

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Bibliographic Details
Published in:Review of accounting & finance 2019-05, Vol.18 (2), p.296-320
Main Authors: Succurro, Marianna, Arcuri, Giuseppe, Costanzo, Giuseppina Damiana
Format: Article
Language:English
Subjects:
Accounting
Bankruptcy
Default
Discriminant analysis
Economic crisis
Economics and Finance
Financial statements
Humanities and Social Sciences
Insolvency
International finance
Manufacturing
Principal components analysis
Research methodology
Risk exposure
Standard scores
Statistical methods
Studies
Variables
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Summary:Purpose Starting from a series of financial ratios analysis, this paper aims to build up two indices which take into account both the firm’s debt level and its sustainability to investigate if and to what extent the proposed indices are able to correctly predict firms’ financial bankruptcy probabilities. Design/methodology/approach The research implements a statistical approach (tandem analysis) based on both an original use of principal component analysis (PCA) and logit model. Findings The econometric results are compared with those of the popular Altman Z-score for different lengths of the reference period and with more recent classifiers. The empirical evidence would suggest a good performance of the proposed indices which, therefore, could be used as early warning signals of bankruptcy. Practical implications The potential application of the model is in the spirit of predicting bankruptcy and aiding companies’ evaluation with respect to going-concern considerations, among others, as the early detection of financial distress facilitates the use of rehabilitation measures. Originality/value The construction of the indebtedness indices is based on an original use of Robust PCA for skewed data.
ISSN:1475-7702
1758-7700
DOI:10.1108/RAF-04-2018-0077