The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods - Technology and Investment

TI > Vol.8 No.3, August 2017

The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods ()

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Download as PDF (Size: 314KB) PP. 151-157

DOI: 10.4236/ti.2017.83013 1,558 Downloads 2,863 Views Citations

Author(s)

Shunquan Zhu

Affiliation(s)

School of Finance, Guangdong University of Finance & Economics, Guangzhou, China.

ABSTRACT

This paper analyzed 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, and 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.

KEYWORDS

Financial Data Samples, Support Vector Machines, Financial Forecasting, Modeling and Simulations

Share and Cite:

Zhu, S. (2017) The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods. Technology and Investment, 8, 151-157. doi: 10.4236/ti.2017.83013.

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