Forecasting expected and unexpected losses

John Juselius and Nikola A. Tarashev

No 18/2020, Bank of Finland Research Discussion Papers from Bank of Finland

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)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Forecasting expected and unexpected losses (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:bofrdp:rdp2020_018

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