Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4951066 | Journal of Computational Science | 2017 | 37 Pages |
Abstract
Evidence suggests that it is possible to extract predictive information from stock message boards. Furthermore, we find that adding this information improves the performance of classification systems trained solely on technical indicators. Our results suggest that information from online text data is complementary to the one available in the past evolution of stock prices. Additionally, we find that highly predictive features derived from the message board data seem to have an important and relevant semantic content.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Ramiro H. Gálvez, AgustÃn Gravano,