An intraday market risk management approach based on textual analysis
Authors: Groth, Sven S.; Muntermann, Jan
Journal: Decision Support Systems (2011)
DOI: 10.1016/j.dss.2010.08.019
The management of financial risk is one of the most challenging tasks of financial institutions. In the last two decades, diverse quantitative models and approaches have been developed and refined to address the impact of volatile markets on business. Whereas existing approaches have intensively utilized structured data such as historical price series, little attention has been paid to unstructured (textual) data, which could be a large source of information in this context. Previous empirical research has shown that certain news stories, such as corporate disclosures, can cause abnormal price behavior subsequent to their publication. On the basis of a data set comprising such news stories as well as intraday stock prices, this paper explores the risk implications of information being newly available to market participants. After showing that such events can significantly drive stock price volatilities, this research aims at identifying among the textual data provided those disclosures that have resulted in most supranormal risk exposures. To this end, four different learners — Naïve Bayes, k-Nearest Neighbour, Neural Network, and Support Vector Machine — have been applied in orde…