Financial Failure Prediction Based on Learning Vector Quantization
Zhengding Qiu · Microcomputer Development · 2004
Effective financial failure prediction is the important requirement of banks, corporations and government management organizations. And the related research is always a hot topic in finance information processing field. Recent years, neural networks have been introduced into this new field and have become new hot. This paper applies learning vector quantization to financial failure prediction based on companies in Chinese Stock Markets firstly and compares it with BP neural network, logistic regression and C4.5 models. The dataset includes 160 companies as train set and 384 ones as test set. The results show that LVQ method outperforms these models and has good application prospect in this field.