Forecasting the Opening and Closing Price Trends of Stock Using Hybrid Models and Artificial Intelligence Algorithm

被引:0
|
作者
Thuan, Nguyen Dinh [1 ]
Nhut, Nguyen Minh [1 ]
Huong, Nguyen Thi Viet [1 ]
Uyen, Dang Vu Phuong [1 ]
机构
[1] VNU HCM, Univ Informat Technol, Ho Chi Minh City, Vietnam
关键词
DJIA prediction; TSLA prediction; META prediction; Artificial intelligence; Deep learning; Machine learning; ARIMA; SVR; LR; GRU; Hybrid model;
D O I
10.1007/978-981-19-8069-5_36
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The stock has been a long-standing and potential investment field until now, attracting much investment in this field every year. In particular, favorite stocks such as Dow Jones Industrial Average (DJIA), Tesla Inc (TSLA), and Meta Platforms Inc (META) have attracted many investments in recent years. The volatility of stock prices is very unpredictable, causing many difficulties for investors in this field. Furthermore, this study uses artificial intelligence models such as Autoregressive Integrated Moving Average (ARIMA), Support Vector Regression (SVR), Linear Regression (LR), and Gated Recurrent Unit (GRU) to predict closing prices and opening prices of three stock DJIA, TSLA, and META. Furthermore, proposing hybrid methods of the above models to improve and improve the accuracy of stock price prediction. The comparison results will be based on three evaluation parameters: RMSE, MAE, and MAPE.
引用
收藏
页码:532 / 546
页数:15
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