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http://dx.doi.org/10.14400/JDC.2020.18.11.267

A Research on stock price prediction based on Deep Learning and Economic Indicators  

Hong, Sunghyuck (Baekseok University, Division of ICT)
Publication Information
Journal of Digital Convergence / v.18, no.11, 2020 , pp. 267-272 More about this Journal
Abstract
Macroeconomics are one of the indicators that are preceded and analyzed when analyzing stocks because it shows the movement of a country's economy as a whole. The overall economic situation at the national level, such as national income, inflation, unemployment, exchange rates, currency, interest rates, and balance of payments, has a great affect on the stock market, and economic indicators are actually correlated with stock prices. It is the main source of data for analysts to watch with interest and to determine buy and sell considering the impact on individual stock prices. Therefore, economic indicators that impact on the stock price are analyzed as leading indicators, and the stock price prediction is predicted through deep learning-based prediction, after that the actual stock price is compared. If you decide to buy or sell stocks by analysis of stock prediction, then stocks can be investments, not gambling. Therefore, this research was conducted to enable automated stock trading by using macro-indicators and deep learning algorithms in artificial intelligence.
Keywords
Stock analysis; Big data; Text mining; AI; Prediction;
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Times Cited By KSCI : 10  (Citation Analysis)
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