分类
情绪分析
库存(枪支)
财务
深度学习
投资(军事)
金融科技
计算机科学
人工智能
业务
金融服务
工程类
政治学
机械工程
政治
法学
作者
Min-Yuh Day,Chia-Chou Lee
标识
DOI:10.1109/asonam.2016.7752381
摘要
Investors have always been interested in stock price forecasting. Since the development of electronic media, hundreds pieces of financial news are released on different media every day. Numerous studies have attempted to examine whether the stock price forecasting through text mining technology and machine learning could lead to abnormal returns. However, few of them involved the discussion on whether using different media could affect forecasting results. Financial sentiment analysis is an important research area of financial technology (FinTech). This research focuses on investigating the influence of using different financial resources to investment and how to improve the accuracy of forecasting through deep learning. The experimental result shows various financial resources have significantly different effects to investors and their investments, while the accuracy of news categorization could be improved through deep learning.
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