The effectiveness of combining XBRL reporting data with machine learning approaches for fundamental earnings movement forecasting

Additional Metadata
Keywords	Machine Learning, XBRL, Earnings Forecasting, Random Forests, Gradient Boosting Machines
Thesis Advisor	Bongaerts, Dion, Li, Yonghan
Persistent URL	hdl.handle.net/2105/57526
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	de Jong, Jelto. (2021, July 15). The effectiveness of combining XBRL reporting data with machine learning approaches for fundamental earnings movement forecasting. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/57526

Publication