Stock market trend forecasting based on multiple textual features: A deep learning method

• Main Authors: HU, Zhenda, WANG, Zhaoxia, HO, Seng-Beng, TAN, Ah-Hwee
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: stock market trend forecasting; textual features; deep learning; sentiment analysis; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/6882; https://ink.library.smu.edu.sg/context/sis_research/article/7885/viewcontent/ICTAI_Stock_Market_Trend_Forecasting_Based_on_MultipleTextual_Features_A_Deep_Learning_Method_Final_Version.pdf
• Institution: Singapore Management University

Stock market trend forecasting is a valuable and challenging research task for both industry and academia. In order to explore the influence of stock news information on the stock market trend, a textual embedding construction method is proposed to encode multiple textual features, including topic f...