Text Mining Systems for Market Response to News: A Survey

By Marc-André Mittermayer, G. Knolmayer. 2007

105 citations recorded by the source corpus.

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Citations in the corpus

Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, background): “Mittermayer and Knolmayer compared various text mining implementations that extract market response to news for prediction [18].”
Deep Learning for Financial Applications : A Survey (2020, background): “It is worth to mention that there are also some studies [163, 164] of text mining for financial prediction models.”
News-based trading strategies (2016, background): “In fact, sentiment analysis can be utilized [31, 34] to extract subjective information from text sources, as well as to measure how market participants perceive and react to news.”
An Automated Framework for Incorporating News into Stock Trading Strategies (2014, background): “We find that the news variable is often included in the optimal trading rules, indicating the added value of news for predictive purposes and validating our proposed framework for automatically incorporating news in stock trading strategies.”
Applications of news analytics in finance: A review (2012, background): “Sophisticated machine-learning algorithms applied without an understanding of the structure and dynamics of financial markets and the use of realistic trading assumptions can lead to applications with little commercial use (see Mittermayer and Knolmayer, 2006).”
Content-Based Collaborative Filtering for News Topic Recommendation (2015, unknown): “The initial attempts (Mittermayer and Knolmayer 2006) are NLP oriented.”
Asymmetric Roles of Advertising and Marketing Capability in Financial Returns to News: Turning Bad into Good and Good into Great (2013, background): “An increasing body of artificial intelligence research has recently examined the use of computerized sentiment analysis based on text mining of news articles to develop stock trading strategies (Mittermayer and Knolmayer 2006b; Zhang and Skiena 2010).”
Improving Decision Analytics with Deep Learning: the Case of Financial Disclosures (2015, background): “While Pang and Lee [16] provide a comprehensive domain-independent survey, other overviews concentrate solely on the ﬁnan-cial domain [15, 20].”