Template-Type: ReDIF-Paper 1.0
Author-Name: Mikael Juselius
Author-X-Name-First: Mikael 
Author-X-Name-Last: Juselius
Author-Name: Nikola Tarashev
Author-X-Name-First: Nikola 
Author-X-Name-Last: Tarashev
Title: Forecasting expected and unexpected losses
Abstract: Extending a standard credit-risk model illustrates that a single factor can drive both expected losses and the extent to which they may be exceeded in extreme scenarios, ie "unexpected losses". This leads us to develop a framework for forecasting these losses jointly. In an application to quarterly US data on loan charge-offs from 1985 to 2019, we find that financial-cycle indicators – notably, the debt service ratio and credit-to-GDP gap – deliver reliable real-time forecasts, signalling turning points up to three years in advance. Provisions and capital that reflect such forecasts would help reduce the procyclicality of banks' loss-absorbing resources.
Length: 56 pages
Creation-Date: 2020-12
File-URL: https://www.bis.org/publ/work913.pdf
File-Format: Application/pdf
File-Function: Full PDF document
File-URL: https://www.bis.org/publ/work913.htm
File-Format: text/html
Number: 913
Keywords: loss rate forecasts, cyclical turning points, expected loss provisioning, bank capital
Classification-JEL: G17, G21, G28
Handle: RePEc:bis:biswps:913