Hybrid Neural Network Bankruptcy Prediction: An Integration of Financial Ratios, Intellectual Capital Ratios, MDA, and Neural Network Learning

DOI

https://doi.org/10.2991/jcis.2006.323How to use a DOI?

Keywords

Bankruptcy prediction; Neural network; Hybrid neural network; MDA

Abstract

One purpose of this paper is to propose hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are, respecitvely, a MDA model integrated with financial ratios, a MDA model integrated with financial ratios and intellectual capital ratios, a MDA-assisted neural network model integrated with financial ratios, and a MDA-assissted neural network model integrated with financial ratios and intellectual capital ratios. The performance of the hybrid neural network model is compared with MDA model integrated with financial ratios as a benchmark. Empirical results using Taiwan bankruptcy data show that hybrid neural network models are very promising ones in terms of accuracy and adaptability.

Open Access

This is an open access article distributed under the CC BY-NC license.

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TY  - CONF
AU  - Wen-Kuei Hsieh
AU  - Shang-Ming Liu
AU  - Sung-Yi Hsieh
PY  - 2006/10
DA  - 2006/10
TI  - Hybrid Neural Network Bankruptcy Prediction: An Integration of Financial Ratios, Intellectual Capital Ratios, MDA, and Neural Network Learning
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.323
DO  - https://doi.org/10.2991/jcis.2006.323
ID  - Hsieh2006/10
ER  -