TITLE:
The Corporate Financial Forecasting Based on Least Squares Support Vector Machines Methods
AUTHORS:
Shunquan Zhu
KEYWORDS:
Financial Data Samples, Support Vector Machines, Financial Forecasting, Modeling and Simulations
JOURNAL NAME:
Technology and Investment,
Vol.8 No.3,
August
9,
2017
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.