A Novel Early Warning Model for Companies’ Financial Health Status Using Hybrid BAT-ANN Model

Document Type : Research Paper

Authors

1 Faculty member at University of Tehran

2 Faculty member at Shahrood University of Technology

3 Faculty at Tehran University

4 Financial management Ph.D Candidate at ,University of Tehran

Abstract

Most managers, shareholders, creditors, and other stakeholders are looking for the practical tools to evaluate and predict companies' financial health. Having such models give them enough time to make right decisions before falling into the bankruptcy.
In the following research, a new early warning model for prediction of companies' financial health using hybrid Bat Artificial neural network developed.
The research population encompasses Iranian public manufacturing companies, and sample used in the model includes 80 random healthy and bankrupt manufacturing companies listed in the Tehran stock market from 2008 to 2017. Also, for developing the model, 12 various and independent financial ratios as explanatory variables employed.
For performance evaluation, the outputs of suggested hybrid BAT-ANN model compared to the Altman model and back-propagation artificial neural networks. The proposed model is able to predict signs of companies' financial unhealthiness up to 3 years before the failure. The statistical evidence demonstrated that the hybrid model outperformed the other two models at 5% significant level.

Keywords

Financial Management Strategy

Articles in Press, Accepted Manuscript
Available Online from 25 February 2023

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History

  • Receive Date: 22 November 2019
  • Revise Date: 23 May 2020
  • Accept Date: 01 August 2020

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