Augmented trading: From news articles to stock price predictions using syntactic analysis

@mastersthesis{citeulike:1177668, abstract = {This thesis tries to answer the question how to predict the reaction of the stock market to news articles using the latest suitable developments in Natural Language Processing. This is done using text classification where a new article is matched to a category of articles which have a certain influence on the stock price. The thesis first discusses why analysis of news articles is a feasible approach to predicting the stock market and why analysis of past prices should not be build upon. From...}, author = {van Bunningen, Arthur}, citeulike-article-id = {1177668}, keywords = {analysis, article, news, prediction, price, stock, syntactic, trading}, posted-at = {2007-03-20 16:08:23}, priority = {3}, school = {University of Twente}, title = {Augmented trading: From news articles to stock price predictions using syntactic analysis}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2287}, year = {2004} }

TY - THES ID - citeulike:1177668 L3 - citeulike-article-id:1177668 N2 - This thesis tries to answer the question how to predict the reaction of the stock market to news articles using the latest suitable developments in Natural Language Processing. This is done using text classification where a new article is matched to a category of articles which have a certain influence on the stock price. The thesis first discusses why analysis of news articles is a feasible approach to predicting the stock market and why analysis of past prices should not be build upon. From... TI - Augmented trading: From news articles to stock price predictions using syntactic analysis PB - University of Twente KW - analysis KW - article KW - news KW - prediction KW - price KW - stock KW - syntactic KW - trading AU - van Bunningen, Arthur PY - 2004/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2287 ER -