Predicting Bank Failures: Comparing and Extending Existing Models

30 Pages Posted: 30 Jan 2019 Last revised: 24 May 2019

See all articles by Rebel A. Cole

Rebel A. Cole

Florida Atlantic University

Jon Taylor

Florida Gulf Coast University - Department of Accounting, Finance & Business Law

Date Written: May 22, 2019

Abstract

We replicate three bank failure models (Martin (1977), Cole and White (2012), and DeYoung and Torna (2013)) and introduce a new predictive model along with several evaluation methods to compare their out-of-sample predictive accuracy. We find that the models are highly accurate individually, and despite their similarities, are significantly different. Our new model is compared to the existing models using evaluation methods which are new to the extant field of bank failure research. Our model is significantly different from and more accurate than the existing models. Our paper makes an important contribution to bank failure research by demonstrating and validating evaluation methods which allow researchers and regulators to determine if a new bank failure model is different from and better than what has already been published.

Keywords: bank, bank failure, CAMELS, FDIC, McNemar’s Test, early warning system

JEL Classification: C52, G01, G17, G21, G28

Suggested Citation

Cole, Rebel A. and Taylor, Jon, Predicting Bank Failures: Comparing and Extending Existing Models (May 22, 2019). Available at SSRN: https://ssrn.com/abstract=3318303 or http://dx.doi.org/10.2139/ssrn.3318303

Rebel A. Cole

Florida Atlantic University ( email )

College of Business
777 Glades Road
Boca Raton, FL 33431
United States
1-561-297-4969 (Phone)

HOME PAGE: http://rebelcole.com

Jon Taylor (Contact Author)

Florida Gulf Coast University - Department of Accounting, Finance & Business Law ( email )

Ft. Myers, FL 33965-6565
United States
239-590-7316 (Phone)

HOME PAGE: http://www.fgcu.edu

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
166
Abstract Views
1,352
Rank
306,913
PlumX Metrics