Maximum likelihood estimation error and operational value-at-risk stability

Paul Larsen

Journal of Operational Risk

Abstract: The challenge of using small sample sizes for operational risk capital models fitted via maximum likelihood estimation is well recognized, yet the literature generally provides warning examples rather than a systematic approach. We present a general framework for analyzing maximum likelihood estimation error on operational value- at-risk as a function of sample size for five severity distributions commonly used in operational risk capital models. More specifically, we study the estimation error along three dimensions: the choice of severity distribution, the sample size and the heaviness of the underlying losses. We apply these results to model selection and explore implications for operational risk modeling.

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Persistent link: https://EconPapers.repec.org/RePEc:rsk:journ3:6446746

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