Combining Machine Learning and Semantic Features in the Classification of Corporate Disclosures

Journal article


Publication Details

Author(s): Evert S, Heinrich P, Henselmann K, Rabenstein U, Scherr E, Schmitt M, Schröder L
Journal: Journal of Logic, Language and Information
Publication year: 2019
ISSN: 0925-8531


Abstract

We investigate an approach to improving statistical text classification by combining machine learners with an ontology-based identification of domain-specific topic categories. We apply this approach to ad hoc disclosures by public companies. This form of obligatory publicity concerns all information that might affect the stock price; relevant topic categories are governed by stringent regulations. Our goal is to classify disclosures according to their effect on stock prices (negative, neutral, positive). In the study reported here, we combine natural language parsing with a formal background ontology to recognize disclosures concerning particular topics from a prescribed list. The semantic analysis identifies some of these topics with reasonable accuracy. We then demonstrate that machine learners benefit from the additional ontology-based information when predicting the cumulative abnormal return attributed to the disclosure at hand.


FAU Authors / FAU Editors

Evert, Stefan Prof. Dr.
Lehrstuhl für Korpus- und Computerlinguistik
Heinrich, Philipp
Lehrstuhl für Korpus- und Computerlinguistik
Henselmann, Klaus Prof. Dr.
Fachbereich Wirtschaftswissenschaften
Rabenstein, Ulrich
Lehrstuhl für Informatik 8 (Theoretische Informatik)
Scherr, Elisabeth
Juniorprofessur für Wirtschaftsprüfung mit dem Schwerpunkt digitale Datenanalyse
Schröder, Lutz Prof. Dr.
Lehrstuhl für Informatik 8 (Theoretische Informatik)


External institutions with authors

Ludwig-Maximilians-Universität (LMU)


How to cite

APA:
Evert, S., Heinrich, P., Henselmann, K., Rabenstein, U., Scherr, E., Schmitt, M., & Schröder, L. (2019). Combining Machine Learning and Semantic Features in the Classification of Corporate Disclosures. Journal of Logic, Language and Information. https://dx.doi.org/10.1007/s10849-019-09283-6

MLA:
Evert, Stefan, et al. "Combining Machine Learning and Semantic Features in the Classification of Corporate Disclosures." Journal of Logic, Language and Information (2019).

BibTeX: 

Last updated on 2019-30-05 at 01:08