Expropriation of the Biggest Shareholdings Based on Principal Component Analysis in Neural Networks

摘要

The neural networks may play an important role in statistical model building. As the basic model building tool of the mathematics and economics neural networks can help specialist and researcher. The neural networks will improve the financial research work. The expropriation is a kind of extra interest, which exceeds the income of the biggest share-holdings normally, illegally occupied by the biggest ones. After the true repayment of control power and social expenditure, it should be shared originally by the small ones commonly. The empirical evidence results indicate that the expropriation of extra interest from the primary power is negatively related to the income per share. Consequently, we provide theoretical and practical evidence for neural networks as a standard approach.