Presentation information

General Session

General Session » GS-2 Machine learning

[1G4-GS-2c] 機械学習:回帰

Tue. Jun 8, 2021 5:20 PM - 7:00 PM Room G (GS room 2)

座長:鈴木 雅大(東京大学)

6:40 PM - 7:00 PM

[1G4-GS-2c-05] Stock price forecast using news headlines

〇Motoki Takenaka1, Shoichi Urano1 (1. Meiji university)

Keywords:Natural language processing, Stock price forecast, Machine Learning

In this paper, we propose to introduce a new input variable by using natural language processing for company information related to stock prices such as net news, and apply it to the prediction model together with the "open price", "close price", "high price", and "low price" of the stock price. As a prediction method, a multiple regression model and a neural network are used. Aiming for highly accurate stock price forecasting by applying the proposal method to the stock price forecast of multiple individual company stocks and comparing and verifying the effectiveness of the proposal method by simulation.

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