文章基本信息

标题：Approach Based on Linear Regression for Stock Exchange Prediction - Case Study of Petr4 Petrobrás, Brazil
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作者：Nadson S. Timbó ; Sofiane Labidi ; Thiago P. do Nascimento 等
期刊名称：International Journal of Artificial Intelligence & Applications (IJAIA)
印刷版ISSN：0976-2191
电子版ISSN：0975-900X
出版年度：2016
卷号：7
期号：1
页码：21
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The stock exchange is an important apparatus for economic growth as it is an opportunity for investors toacquire equity and, at the same time, provide resources for organizations expansions. On the other hand, amajor concern regarding entering this market is related with the dynamic in which deals are made sincethe pricing of shares happens in a smart and oscillatory way. Due to this context, several researchers arestudying techniques in order to predict the stock exchange, maximize profits and reduce risks. Thus, thisstudy proposes a linear regression model for stock exchange prediction which, combined with financialindicators, provides support decision-making by investors.
关键词：Stock Exchange Prediction; Autoregressive Models & Linear Models