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

Published on Jan 1, 2019in Journal of Operational Risk0.727
· DOI :10.21314/jop.2018.217
Paul Larsen1
Estimated H-index: 1
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#1Francesca GreselinH-Index: 11
#2Fabio PiacenzaH-Index: 1
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We explore the Monte Carlo steps required to reduce the sampling error of the estimated 99.9% quantile within an acceptable threshold. Our research is of primary interest to practitioners working in the area of operational risk measurement, where the annual loss distribution cannot be analytically determined in advance. Usually, the frequency and the severity distributions should be adequately combined and elaborated with Monte Carlo methods, in order to estimate the loss distributions and risk ...
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