Does summarization help stock prediction? A news impact analysis

Xiaodong LI, Haoran XIE*, Yangqiu SONG, Shanfeng ZHU, Qing LI, Fu Lee WANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)

33 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)26-34
Number of pages9
JournalIEEE Intelligent Systems
Volume30
Issue number3
Early online date12 Jan 2015
DOIs
Publication statusPublished - May 2015
Externally publishedYes

Keywords

  • intelligent systems
  • news summarization
  • predictive analytics
  • Predictive models
  • stock prediction

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