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Predicting Operational Loss Exposure Using Past Losses

Author

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  • Curti, Filippo

    () (Federal Reserve Bank of Richmond)

  • Migueis, Marco

    () (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.

Suggested Citation

  • Curti, Filippo & Migueis, Marco, 2016. "Predicting Operational Loss Exposure Using Past Losses," Finance and Economics Discussion Series 2016-2, Board of Governors of the Federal Reserve System (US), revised 12 Oct 2016.
  • Handle: RePEc:fip:fedgfe:2016-02
    DOI: 10.17016/FEDS.2016.002r1
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    References listed on IDEAS

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    More about this item

    Keywords

    Banking Regulation; Risk Management; Operational Risk; Tail Risk; Quantile Regression;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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