Predicting Operational Loss Exposure Using Past Losses

Filippo Curti and Marco Migueis

No 2016-2, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: Operational risk models, such as the loss distribution approach, frequently use past internal losses to forecast operational loss exposure. However, the ability of past losses to predict exposure, particularly tail exposure, has not been thoroughly examined in the literature. In this paper, we test whether simple metrics derived from past loss experience are predictive of future tail operational loss exposure using quantile regression. We find evidence that past losses are predictive of future exposure, particularly metrics related to loss frequency.

Keywords: Banking Regulation; Risk Management; Operational Risk; Tail Risk; Quantile Regression (search for similar items in EconPapers)
JEL-codes: G21 G28 G32 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2016-02-03
New Economics Papers: this item is included in nep-cfn, nep-for and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2016-02

DOI: 10.17016/FEDS.2016.002r1

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