Does Summarization Help Stock Prediction? A News Impact Analysis

X. Li; H. Xie; Y. Song; S. Zhu; Qing Li; F.L. Wang

doi:10.1109/MIS.2015.1

Does Summarization Help Stock Prediction? A News Impact Analysis

X. Li, H. Xie, Y. Song, S. Zhu, Qing Li, F.L. Wang

Research output: Journal article publication › Journal article › Academic research › peer-review

65 Citations (Scopus)

Abstract

© 2001-2011 IEEE.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 language	English
Pages (from-to)	26-34
Number of pages	9
Journal	IEEE Intelligent Systems
Volume	30
Issue number	3
DOIs	https://doi.org/10.1109/MIS.2015.1
Publication status	Published - 1 May 2015
Externally published	Yes

Keywords

Accuracy
artificial intelligence
stock prediction
Testing
Computer science
Educational institutions
Equations
Indexes
intelligent systems
news summarization
predictive analytics
Predictive models

ASJC Scopus subject areas

Computer Networks and Communications
Artificial Intelligence

More information

10.1109/MIS.2015.1

Cite this

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title = "Does Summarization Help Stock Prediction? A News Impact Analysis",

abstract = "{\textcopyright} 2001-2011 IEEE.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 = "Accuracy, artificial intelligence, stock prediction, Testing, Computer science, Educational institutions, Equations, Indexes, intelligent systems, news summarization, predictive analytics, Predictive models",

author = "X. Li and H. Xie and Y. Song and S. Zhu and Qing Li and F.L. Wang",

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AB - © 2001-2011 IEEE.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.

KW - Accuracy

KW - artificial intelligence

KW - stock prediction

KW - Testing

KW - Computer science

KW - Educational institutions

KW - Equations

KW - Indexes

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ER -

Does Summarization Help Stock Prediction? A News Impact Analysis

Abstract

Keywords

ASJC Scopus subject areas

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