Abstract
This paper analysised the present domestic and foreign financial forecasting situation of listed companies and it is based on least squares support vector machines. According to our country’s capital markets, 44 listed companies are modeling data samples, 10 listed companies are forecasting data samples, building financial forecasting model of listed companies obtains satisfaction financial forecasting results. The empirical study results show that we may use entirely least squares support vector machines methods to build financial forecasting models, and to distinguish financial credit risks of listed companies; comparing to traditional statistical methods and neural network methods, financial forecasting method based on least squares support vector machines is an ideal listed company’s financial forecasting method. It is used to extensive fields that have high extending value.
Cite
CITATION STYLE
Zhu, S. (2017). The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods. Technology and Investment, 08(03), 151–157. https://doi.org/10.4236/ti.2017.83013
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