2022
DOI: 10.4236/jcc.2022.1012003
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Stock Price Forecasting with Artificial Neural Networks Long Short-Term Memory: A Bibliometric Analysis and Systematic Literature Review

Abstract: This study maps the academic literature on Stock Price Forecasting with Long-Term Memory Artificial Neural Networks-RNA LSTM. The objective is to know if it is suitable for time series studies, especially for stock price projection. Through bibliometric analysis and systematic literature review, it is observed that 333 authors wrote on the topic between 2018 and March 2022, and the journals Expert Systems with Applications, IEEE Access, Big Data Journal and Neural Computing and Applications, published the most… Show more

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Cited by 4 publications
(1 citation statement)
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“…The findings demonstrate the growing significance of studying upper bounds on stock prices as a field of study in the world of finance. (Fantin & Hadad, 2022) conducted a bibliometric study of the literature on China's stock price ceilings. Using a bibliometric approach, this paper explores the current landscape of research on stock price ceilings in China.…”
Section: B Bibliometricsmentioning
confidence: 99%
“…The findings demonstrate the growing significance of studying upper bounds on stock prices as a field of study in the world of finance. (Fantin & Hadad, 2022) conducted a bibliometric study of the literature on China's stock price ceilings. Using a bibliometric approach, this paper explores the current landscape of research on stock price ceilings in China.…”
Section: B Bibliometricsmentioning
confidence: 99%