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Soft Computing
Erschienen in: Soft Computing 6/2020

28.06.2019 | Methodologies and Application

A multivariate grey prediction model with grey relational analysis for bankruptcy prediction problems

verfasst von: Yi-Chung Hu

Erschienen in: Soft Computing | Ausgabe 6/2020

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Abstract

Regarding bankruptcy prediction as a kind of grey system problem, this study aims to develop multivariate grey prediction models based on the most representative GM(1, N) for bankruptcy prediction. There are several distinctive features of the proposed grey prediction model. First, to improve the prediction performance of the GM(1, N), grey relational analysis is used to sift relevant features that have the strongest relationship with the class feature. Next, the proposed model effectively extends the multivariate grey prediction model for time series to bankruptcy prediction irrespective of time series. It turns out that the proposed model uses the genetic algorithms to avoid indexing by time and using the ordinary least squares with statistical assumptions for the traditional GM(1, N). The empirical results obtained from the financial data of Taiwanese firms in the information and technology industry demonstrated that the proposed prediction model performs well compared with other GM(1, N) variants considered.
Vorheriger Artikel An integrated decision making model for supplier and carrier selection with emphasis on the environmental factors
Nächster Artikel The effects of consumer confusion on hotel brand loyalty: an application of linguistic nonlinear regression model in the hospitality sector

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Metadaten
Titel
A multivariate grey prediction model with grey relational analysis for bankruptcy prediction problems
verfasst von
Yi-Chung Hu
Publikationsdatum
28.06.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 6/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04191-0

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