TITLE

DEVELOPMENT OF STOCK EVALUATION SYSTEM BASED ON QUASI-LINEAR REGRESSION MODEL

AUTHOR(S)
Yuling Lin; Wurong Shih; Jinglu Hu
PUB. DATE
March 2013
SOURCE
International Journal of Electronic Business Management;2013, Vol. 11 Issue 1, p23
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
In this paper, a quasi-Linear Regression (quasi-LR) model is proposed for developing a stock evaluation system. The main idea is to build the system by using machine learning method, instead of using ANP analysis based on the results of expert questionnaire. The proposed quasi- LR model consists of linear part and nonlinear part, which is identified by using a hierarchical algorithm in such a way that the linear part of the model describes the importance relations among the input financial indicators, while the nonlinear part of the model represents the nonlinear mapping between the financial indexes and the stock performance. Numerical experiments on the past real stock data of 150 Taiwanese stocks are used to have a pilot run of the system. The results show the promising effectiveness of the proposed stock evaluation system.
ACCESSION #
87590856

 

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