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Forecasting expected and unexpected losses

John Juselius and Nikola Tarashev ()

No 913, BIS Working Papers from Bank for International Settlements

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.

Keywords: loss rate forecasts; cyclical turning points; expected loss provisioning; bank capital (search for similar items in EconPapers)
JEL-codes: G17 G21 G28 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2020-12
New Economics Papers: this item is included in nep-ban, nep-for, nep-mac and nep-rmg
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