Title :
Does Summarization Help Stock Prediction? A News Impact Analysis
Author :
Xiaodong Li ; Haoran Xie ; Yangqiu Song ; Shanfeng Zhu ; Qing Li ; Fu Lee Wang
Abstract :
The authors study the problem of how news summarization can help stock price prediction, proposing a generic stock price prediction framework to enable the use of different external signals to predict stock prices. Experiments were conducted on five years of Hong Kong Stock Exchange data, with news reported by Finet; evaluations were performed at individual stock, sector index, and market index levels. The authors´ results show that prediction based on news article summarization can effectively outperform prediction based on full-length articles on both validation and independent testing sets.
Keywords :
information retrieval; stock markets; text analysis; information retrieval; news impact analysis; news summarization; stock price prediction framework; Investments; Predictive models; Stock market; artificial intelligence; intelligent systems; news summarization; predictive analytics; stock prediction;
Journal_Title :
Intelligent Systems, IEEE