Opinion Mining and the Visualization of Stock Selection in Quantitative Trading

Autor: Ming-Chun Chen, I-Hsien Ting, Chian-Hsueng Chao, Tsung-Hsing Tsai
Rok vydání: 2019
Předmět:
Zdroj: TAAI
Popis: In the stock market, investors usually focus only on the quantifiable information such as stock price and volume. However, few attentions go to the social network. This study use visualized approach to mine voices of the netizens to find the stock tendency. A series of data mining, cleaning, and natural language processing combine with the algorithm of artificial intelligence/machine learning to do the prediction between stock price and the voices of the netizens. This study not only presented a novel approach but also won the most promising prize in Hua Nan Financial Holdings Fintech Competition.
Databáze: OpenAIRE