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http://dx.doi.org/10.22156/CS4SMB.2021.11.01.028

A study on stock price prediction through analysis of sales growth performance and macro-indicators using artificial intelligence  

Hong, Sunghyuck (Division of ICT, Baekseok University)
Publication Information
Journal of Convergence for Information Technology / v.11, no.1, 2021 , pp. 28-33 More about this Journal
Abstract
Since the stock price is a measure of the future value of the company, when analyzing the stock price, the company's growth potential, such as sales and profits, is considered and invested in stocks. In order to set the criteria for selecting stocks, institutional investors look at current industry trends and macroeconomic indicators, first select relevant fields that can grow, then select related companies, analyze them, set a target price, then buy, and sell when the target price is reached. Stock trading is carried out in the same way. However, general individual investors do not have any knowledge of investment, and invest in items recommended by experts or acquaintances without analysis of financial statements or growth potential of the company, which is lower in terms of return than institutional investors and foreign investors. Therefore, in this study, we propose a research method to select undervalued stocks by analyzing ROE, an indicator that considers the growth potential of a company, such as sales and profits, and predict the stock price flow of the selected stock through deep learning algorithms. This study is conducted to help with investment.
Keywords
Stock price analysis; Big data; Macro-indicative artificial intelligence; Prediction system; LSTM;
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