Combining data and text mining techniques for analysing financial reports: Research Articles
Antonina Kloptchenko, Tomas Eklund, Jonas Karlsson, Barbro Back, Hannu Vanharanta, Ari J. E. Visa · 2004
There is a vast amount of fnancial information on companies' fnancial performance available to investors in electronic form today. While automatic analysis of fnancial fgures is common, it has been diffcult to extract meaning from the textual parts of fnancial reports automatically. The textual part of an annual report contains richer information than the fnancial ratios. In this paper, we combine data and text mining methods for analysing quantitative and qualitative data from fnancial reports, in order to see if the textual part of the report contains some indications about future fnancial performance. The quantitative analysis has been performed using self-organizing maps, and the qualitative analysis using prototype-matching text clustering. The analysis is performed on the quarterly reports of three leading companies in the telecommunications sector. Copyright © 2004 John Wiley & Sons, Ltd.