Hybrid Neural Network Bankruptcy Prediction: An Integration of Financial Ratios, Intellectual Capital Ratios, MDA, and Neural Network Learning
نویسندگان
چکیده
One purpose of this paper is to propose the hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are, respectively, 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-assisted 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.
منابع مشابه
Investigating Financial Crisis Prediction Power using Neural Network and Non-Linear Genetic Algorithm
Bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. Therefore, correct prediction of bankruptcy is of high importance in the financial world. This research intends to investigate financial crisis prediction power using models based on Neural Network...
متن کاملEnhancing Efficiency of Neural Network Model in Prediction of Firms Financial Crisis Using Input Space Dimension Reduction Techniques
The main focus in this study is on data pre-processing, reduction in number of inputs or input space size reduction the purpose of which is the justified generalization of data set in smaller dimensions without losing the most significant data. In case the input space is large, the most important input variables can be identified from which insignificant variables are eliminated, or a variable ...
متن کاملUsing the Gamma Memory Neural Network for Bankruptcy Prediction: a Preliminary Study
Many static neural networks have been studied extensively in financial classification problems. However, dynamic time series predictive classification using neural networks with memory, such as the Gamma Memory neural network (GMNN), may prove more accurate. In this study we compare the predictive accuracy of the GMNN to the Multilayer Perceptron neural network and the statistical approaches of...
متن کاملAn Adaptive Fuzzy Neural Network Model for Bankruptcy Prediction of Listed Companies on the Tehran Stock Exchange
Nowadays, prediction of corporate bankruptcy is one of the most important issues which have received great attentions among academia and practitioners. Although several studies have been accomplished in the field of bankruptcy prediction, less attention has been devoted for proposing a systematic approach based on fuzzy neural networks. The present study proposes fuzzy neural networks to predi...
متن کاملThe hybrid approach based on genetic algorithm and neural network to predict financial fraud in banks
Audit has become an essential topic in the world because there is much evidence about deliberate manipulations in the reports. One of the concerns in the field of audit is discovery and search of the financial statements and the high volume of bulk data. This study tried to suggest the appropriate method to detect these frauds due to the data which has been available and a proposed algorithm. R...
متن کامل