Forecasting Intraday stock price trends with text mining techniques

By Marc-André Mittermayer. 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the, 2004

302 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/e13227c5d2bfc1e04d982b2ebf13407cb3d27bc9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Information Systems

In Management Science and Operations Research

Citations in the corpus

A survey of the applications of text mining in financial domain (2016, methodology): “(2013) Corporate News SVM, SVR Up/ Down Schumaker et al. (2012) US Financial News SVR Error Rate Groth and Muntermann (2011) German ad hoc Announcements NB, k-NN, SVM, NN Up/ Down Bollen et al. (2010) Tweets SOFNN Error Rate Huang et al. (2010) Financial News Weighted AR Up/ Down Li (2010) The US co”
Deep learning for stock prediction using numerical and textual information (2016, background): “There has been a number of efforts for predicting the trend of stock prices on the basis of textual information [14], [15], [16], [17], [18].”
Big Data Analytics in Financial Statement Audits (2015, background): “In addition to social media, news articles are also known to predict movements of stock prices (Chan 2003; Mittermayer 2004).”
Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment (2015, background): “Frequency divided by total number of words Mahajan et al. (2008) Latent Dirichlet Allocation (LDA) Extraction of twenty-five topics Binary Butler and Kešelj (2009) Character N-grams, three readability scores, last year’s performance Minimum occurrence per document.”
Deep learning for financial sentiment analysis on finance news providers (2016, unknown): “[10] [11] 2.”
Evaluating sentiment in financial news articles (2012, background): “The act of correlating financial news articles to a quantifiable price movement is a difficult task, even when the information within a financial news article can have a visible impact on price (Wuthrich, Cho et al., 1998; Lavrenko, Schmill et al., 2000a; Gidofalvi, 2001; Mittermayer, 2004).”
A quantitative stock prediction system based on financial news (2009, methodology): “Fundamentalists are interested in the internal makeup of a security, such as numeric data on the overall economy, individual stock health ratios such as inflation, interest rates, return on assets, debt to equity and price to earnings among others.”
Text mining for market prediction: A systematic review (2014, methodology): “Top 30 concepts Binary, TF-IDF Rachlin et al. (2007) Bag-of-words, commonly used financial values Most influential keywords list (Automatic extraction) TF, Boolean, Extractor software output Tetlock et al. (2008) Bag-of-words for negative words Pre-defined dictionary.”
Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research (2016, methodology): “Mittermayer (2004) established an association between the narrative content of 6602 corporate press releases and stock prices by employing their NewsCATS (News Categorization and Trading System) software, which featured TF-IDF term weighting, enhanced with an unsupervised SVM light classifier.”
Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news (2014, methodology): “Yet, in contrast to the myriad of studies using market-based explanatory data, relatively few studies have explored ﬁ - nancial recommendation based only on explanatory variables obtained from textual data (e.g., [22,23,32,39,41,42,46]).”
Pattern graph tracking-based stock price prediction using big data (2018, background): “Unlike machine learning, there are several prediction research works based on the word analysis of news articles ([29, 38, 39]).”
News-based trading strategies (2016, methodology): “Another research stream develops a news categorization and trading system to predict stock price trends [27].”
Machine Learning Techniques and Use of Event Information for Stock Market Prediction: A Survey and Evaluation (2005, background): “Many believed the integration of event-knowledge and NNs hold great promise for improved prediction in stock markets [7] [12] [13] [16] [19] [20] [27] [32].”
Textual analysis of stock market prediction using breaking financial news: The AZFin text system (2009, methodology): “Table I. Prior Algorithmic Research Algorithm Categories Source Material Examples Genetic Algorithm 2 categories Undisclosed number of chatroom posts Thomas & Sycara, 2002 Na¨ive Bayesian 3 categories 5,000 articles from Lavrenko s collection Gidofalvi et al. 2001 5 categories 38,469 articles”