Text Opinion Mining for Stock Market Prediction using News Reports of Securities in Taiwan

Ray-I Chang ； Chang-Ling Hsu ； Shu-Yu Lin ； Wen-Shong Huan

《資訊與管理科學》 8卷1期 (2015/06) Pp. 25-35

並列摘要

In this paper, we introduce a method to predict stock price by mining text opinions in news reports of securities. In Taiwan, the populace investors usually read/watch the news reports of securities before doing their stock investments. It motivated us to analyze the relations between the changes of stock prices and the opinions in news reports of securities. Our method consists of carrying out the text processing of news report, describe the features, extracting the expressed opinions, and predicting stock price tendency. We use an association rule mining method to analyze the opinions shown in news reports and the changes of stock prices. Our method produces some interesting rules to predict stock prices. Based on the obtained results, we find that the opinions in news reports usually have a great influence on the changes of stock prices. However, not all opinions are equal. Researches can aim at identifying these relationships for the populace investors in Taiwan to predict stock prices.

並列關鍵字

Opinion Mining ； Financial Data Mining ； Stock Prediction ； Association Rules

參考文獻

Lung, Y. M.(2000).Application of neural network with stock price trend forecasting and stock choosing.Institute of Information Management, National Central University.

Chiang, C. H.(2002).Using genetic algorithms to find fundamental selection and technical timing rules.Institute of Information Management, National Central University.

Han, C. B.(2001).A study on stock market transaction data mining with RSS Algorithm.Institute of Information Management, National Central University.

Bollen, J.,Mao, H.,Zeng, X.(2011).Twitter mood predicts the stock market.Journal of Computational Science.2,1-8.

Kim, Y.,Kim, N.,Jeong, S.R.(2012).Stock-index Invest Model Using News Big Data Opinion Mining.Journal of Intelligence and Information Systems.18(2),143-156.