Stock Market Prediction without Sentiment Analysis: Using a Web-Traffic Based Classifier and User-Level Analysis

Pierpaolo Dondio
2013 2013 46th Hawaii International Conference on System Sciences  
This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline classifier solely based on price time-series, and to have similar performances as the
more » ... fier built considering price and traffic features together. The best predictive performances are achieved when information about stock capitalization is coupled with long-term and midterm web traffic levels. In the second part of the paper we show how there exists a group of users whose traffic patterns constantly outperform the other users in predictive capacity. The findings set interesting future works in the definition of novel market indicators for market analysis.
doi:10.1109/hicss.2013.498 dblp:conf/hicss/Dondio13 fatcat:bklgious45bthd7v5dconuq2ma