Text mining for market prediction: A systematic review

By Arman Khadjeh Nassirtoussi, Saeed Reza Aghabozorgi, Teh Ying Wah, David Chek Ling Ngo. 2014

621 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Economics & Operations Research, Time-Series & Forecasting

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Citations in the corpus

Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “reviewed text mining studies for stock or forex market prediction [20].”
Improving Sentiment Analysis with Document-Level Semantic Relationships from Rhetoric Discourse Structures (2017, background): “The corresponding evidence points out that investors in financial markets frequently refer to textual information in order to decide upon exercising ownership in stocks [24]–[28].”
A survey of the applications of text mining in financial domain (2016, methodology): “Recently, Nassirtoussi et al. (2014) conducted a survey on various methods for market prediction using Text mining.”
Improving Decision Analytics with Deep Learning: the Case of Financial Disclosures (2015, methodology): “In addition, neural network models have been used more rarely, but are slowly gaining traction, just as in other application domains [14].”
Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment (2015, methodology): “Major components and flow in ma lists the reviewed available works and points out their featureselection, -reduction and -representation strategy (Khadjeh Nassirtoussi et al., 2014). Another important aspect in reviewing the available works that are in this space is the type of machine-learning algo”
The evolution of sentiment analysis - A review of research topics, venues, and top cited papers (2016, methodology): “Since then, the use of sentiment analysis has reached numerous other areas such as the prediction of financial markets [Nassirtoussi et al. 2014] and reactions to terrorist attacks [Burnap et al. 2014].”
Natural language based financial forecasting: a survey (2017, methodology): “Sometimes, a primary linear regression is directly used with ordinary least square (OLS) to estimate coefficients [81].”
Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research (2016, methodology): “Literature Selection We began our search for relevant literature by scanning the bibliographies of four literature reviews that surveyed NLP developments in the accounting, audit, and finance domains (Fisher et al., 2010; Li, 2010c; Kearney & Liu, 2014; Nassirtoussi et al., 2014).”
Temporal Relational Ranking for Stock Prediction (2018, methodology): “MSE has been widely used for evaluating regression tasks such as stock price prediction [25, 32, 49].”