EconPapers    
Economics at your fingertips  
 

Can statistics-based early warning systems detect problem banks before markets?

Randall K. Kimmel, John Thornton and Sara E. Bennett

The North American Journal of Economics and Finance, 2016, vol. 37, issue C, 190-216

Abstract: Statistical early warning systems (EWS) to identify problematic banks have grown in sophistication, complexity, and accuracy, but can they inform markets? We utilize five “archetypical” EWS using a unique dataset which accumulates data from 1986 through 2009. An arbitrage portfolio is formed by shorting problematic banks and going long the remaining banks. We find accumulating data allows the models to function during long periods with few or no bank failures and that the factors used are stable. While all models studied do a good job predicting bank failure, we find that EWS are unable to inform markets.

Keywords: Bank failure prediction models; Market efficiency (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940816300328
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:37:y:2016:i:c:p:190-216

DOI: 10.1016/j.najef.2016.04.004

Access Statistics for this article

The North American Journal of Economics and Finance is currently edited by Hamid Beladi

More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Haili He ().

 
Page updated 2021-01-11
Handle: RePEc:eee:ecofin:v:37:y:2016:i:c:p:190-216