Stock price prediction using the Chaid rule-based algorithm and particle swarm optimization (pso)
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_AMFA-5-2_005
تاریخ نمایه سازی: 20 تیر 1400
Abstract:
Stock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to predict this trend to see if the trend continues to increase or decrease over time. In this research, stock price prediction for ۱۱۷۰ years -company during ۲۰۱۱-۲۰۱۶ (a six-year period) of listed companies in stock exchange has been studied using the machine learning method (Chaid rule-based algorithm and Particle Swarm Optimization Algorithm). The results of the research show that there is a significant relationship between earnings per share, e / p ratio, company size, inventory turnover ratio, and stock returns with stock prices. Also, particle swarm optimization (pso) algorithm has a good ability to predict stock prices.
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Authors
Aliasghar Davoodi Kasbi
Department of Accounting, Babol Branch, Islamic Azad University, Babol, Iran
Iman Dadashi
Department of Accounting, Babol Branch, Islamic Azad University, Babol, Iran
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