Building a Hybrid Prediction Model to Evaluation of Financial Distress Corporate

Abstract:

Exploring financial distress activity within a listed target of stock markets focused on creating such prediction models can provide insight into the technological requirements of corporate and the demands placed upon a stock investor in this field. This study integrates professional knowledge to financial ratios into the emerging soft computing techniques for building up a hybrid corporate distress prediction of early warning systems in regarding application fields. Conclusively, the empirical results indicate that the proposed procedure is a great potential alternative of helpful hybrid models to demonstrate its technological merit and application value, and it has increasing the application filings. In terms of managerial implications, the analysis results may be relevant to other types of prediction models seeking to identify financial ratios for the planning processes.

• Periodical: Applied Mechanics and Materials (Volumes 651-653)
• Pages: 1543-1546
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.651-653.1543
• Online since: September 2014
• Authors: You Shyang Chen*
• Keywords: Financial Distress, Financial Prediction, Hybrid Procedure, Rough Set Classifier

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