文章基本信息

标题：Stock price analysis using machine learning method(Non-sensory-parametric backup regression algorithm in linear and nonlinear mode)
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作者：Aliasgar Davoodi Kasbi ; Iman Dadashi ; Kaveh Azinfar 等
期刊名称：Advances in Mathematical Finance and Applications
印刷版ISSN：2538-5569
电子版ISSN：2645-4610
出版年度：2021
卷号：6
期号：2
页码：285-301
DOI：10.22034/amfa.2019.1869838.1232
语种：English
出版社：Islamic Azad University of Arak
摘要：The most common starting point for investors when buying a stock is to look at the trend of price changes. In recent years, different models have been used to predict stock prices by researchers, and since artificial intelligence techniques, including neural networks, genetic algorithms and fuzzy logic, have achieved successful re-sults in solving complex problems; in this regard, more exploitation Are. In this research, the prediction of stock prices of companies accepted in the Tehran Stock Exchange using artificial intelligence algorithm (non-sensory-parametric support vector regression algorithm in linear and nonlinear mode) has been investigated. The results of the research show that the PINSVR algorithm in nonlinear mode has been able to predict the stock price over the years, rather than linear mode.