We present a general approach for Web news items analysis in relation to stock prices. The framework that we introduce provides the ability to study the impact of events extracted from news on stock prices. The relation between events and price is quantified in terms of the i) paired-samples t-Test, ii) McNemar's test, and iii) confidence and support. The extraction, representation, and visualization of data are key components of the proposed framework. The validation of the framework is based on three case studies, involving Tesco, Shell, and British Petroleum, and the price reaction(s) to different news events.

Additional Metadata
Persistent URL dx.doi.org/10.1109/CIFEr.2014.6924073, hdl.handle.net/1765/84802
Conference 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014
Citation
Van Essen, R.M, Milea, V, & Frasincar, F. (2014). A framework for Web news items analysis in relation to share prices. Presented at the 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014. doi:10.1109/CIFEr.2014.6924073