@inproceedings{7a84f9fe0d4542bd977cc9f08a003652,
title = "Textual analysis of stock market prediction using financial news articles",
abstract = "This paper examines the role of financial news articles on three different textual representations; Bag of Words, Noun Phrases, and Named Entities and their ability to predict discrete number stock prices twenty minutes after an article release. Using a Support Vector Machine (SVM) derivative, we show that our model had a statistically significant impact on predicting future stock prices compared to linear regression. We further demonstrate that using a Noun Phrase representation scheme performs better than the de facto standard of Bag of Words.",
keywords = "Bag of words, Named entities, Noun phrases, Prediction, SVM, Stock market",
author = "Schumaker, {Robert P.} and Hsinchun Chen",
year = "2006",
language = "English (US)",
isbn = "9781604236262",
series = "Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006",
pages = "1422--1430",
booktitle = "Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006",
note = "12th Americas Conference on Information Systems, AMCIS 2006 ; Conference date: 04-08-2006 Through 06-08-2006",
}