The impact of microblogging data for stock market prediction: Using Twitter to predict returns, volatility, trading volume and survey sentiment indices

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• 作者：Nuno Oliveira ; ^a ; ^{nunomroliveira@gmail.com} ; Paulo Cortez^a ; ^{pcortez@dsi.uminho.pt} ; Nelson Areal^b ; ^{nareal@eeg.uminho.pt}
• 关键词：Stock market ; Twitter ; Data and text mining ; Regression
• 刊名：Expert Systems with Applications
• 出版年：2017
• 出版时间：1 May 2017
• 年：2017
• 卷：73
• 期：Complete
• 页码：125-144
• 全文大小：2251 K
• 卷排序：73

文摘

Evaluation of the predictive value of Twitter data for stock market variables. Creation of a Kalman Filter (KF) indicator by combining five distinct indicators. Forecasting of two popular survey sentiment indicators using Twitter data and KF. Twitter features and KF were informative to forecast returns of some stocks. Twitter and KF indicators were useful to predict some survey indicators.