Stock Market Prediction using LSTM Model

Konferenz: CAIBDA 2022 - 2nd International Conference on Artificial Intelligence, Big Data and Algorithms
17.06.2022 - 19.06.2022 in Nanjing, China

Tagungsband: CAIBDA 2022

Seiten: 4Sprache: EnglischTyp: PDF

Autoren:
Yu, Chuxiao (College of Liberal Arts and Science, Iowa State University, Ames, IA, USA)

Inhalt:
As we all know, the stock market's direction is very volatile and difficult to predict. The purpose of this paper is to predict the future trend of the stock market based on the existing data. The stock market is not only a market with interests but also a market with high risks. Making accurate predictions on the changing stock market trend is valuable for individuals and organizations. First, it will help users to avoid some risks. Second, understanding possible future trends allow users to make reasonable operations or allocation of investments in advance. Also, we are able to do more related research and analysis based on the predictions, such as finding the reason why a stock act abnormally. This paper will use the Long-Short Term Memory model to achieve the above purpose.