Predicting bank distress: testing the additional predictive power of an equity market indicator with machine learning algorithms

Additional Metadata
Keywords	Bank distress; machine learning; equity market information; distance to default; implied cost of capital
Thesis Advisor	Elfers, FM
Persistent URL	hdl.handle.net/2105/58949
Series	Business Economics
Organisation	Erasmus School of Economics
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	Drift, J.H.W. van der. (2021, September 3). Predicting bank distress: testing the additional predictive power of an equity market indicator with machine learning algorithms. Business Economics. Retrieved from http://hdl.handle.net/2105/58949

Publication