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Bank Loan Loss Accounting Treatments, Credit Cycles and Crash Risk

54 Pages Posted: 3 Aug 2015 Last revised: 22 Feb 2017

Panayiotis C. Andreou

Cyprus University of Technology

Ian A. Cooper

London Business School

Christodoulos Louca

Cyprus University of Technology

Dennis Philip

Durham University Business School

Date Written: January 26, 2017

Abstract

Banks that follow conditional conservatism in their loan loss accounting treatments benefit from a reduction in crash risk. The key discretionary loan loss accounting channels are provisions and allowances. We show that conditional conservatism reduces crash risk of small banks during periods of credit contraction and boom. Interestingly, for large banks, crash risk is not reduced by more conservative accounting even for those with higher levels of opacity. Hence regulation prompting for more conservative bank loan loss accounting does not present a significant opportunity to limit systemic effects arising from abrupt price declines in the stocks of large banks.

Keywords: Accounting conservatism, loan loss accounting, bank lending, crash risk

JEL Classification: G21, G28

Suggested Citation

Andreou, Panayiotis C. and Cooper, Ian A. and Louca, Christodoulos and Philip, Dennis, Bank Loan Loss Accounting Treatments, Credit Cycles and Crash Risk (January 26, 2017). London Business School Accounting Research Paper Series. Available at SSRN: https://ssrn.com/abstract=2638875 or http://dx.doi.org/10.2139/ssrn.2638875

Panayiotis Andreou

Cyprus University of Technology ( email )

School Of Management and Economics
P.O. Box 50329
Lemesos, 3036
Cyprus

HOME PAGE: http://www.pandreou.com

Ian Cooper

London Business School ( email )

Sussex Place
Regent's Park
London, London NW1 4SA
United Kingdom
+44 171 262 5050 (Phone)

Christodoulos Louca

Cyprus University of Technology ( email )

Limassol, 3603
Cyprus

Dennis Philip (Contact Author)

Durham University Business School ( email )

Department of Economics and Finance
Mill Hill Lane
Durham, DH1 3LB
United Kingdom

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