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Treatment of the Data Collection Threshold in Operational Risk: A Case Study with the Lognormal DistributionAlexander CavalloNorthern Trust Corporation Benjamin RosenthalNorthern Trust Corporation Xiao WangUniversity of Connecticut - Department of Statistics Jun YanUniversity of Connecticut - Department of Statistics February 1, 2012 The Journal of Operational Risk, Vol. 7, No. 1, Spring 2012. Abstract: Among operational risk practitioners there is some confusion about the implications of the loss data collection threshold and the estimation of "truncated" or "shifted" distributions. Claims that "shifted" models result in biased parameter estimates rely on the premise that the "true" model is known to be "truncated" and do not objectively evaluate "shifted" distributions. We systematically analyze the performance of "shifted" and "truncated" lognormal models and illustrate the use of Vuong's LR test for model selection. We conclude that truncated and shifted lognormal models are equally valid or invalid approaches for estimating loss severity with a data collection threshold.
Number of Pages in PDF File: 33 Keywords: Operational risk, Regulatory capital, Loss distribution, Data truncation, Shifted distribution, Vuong's test, Severity distribution, Basel II JEL Classification: C13, G20, G21, G32 working papers seriesDate posted: August 31, 2010 ; Last revised: February 10, 2012Suggested CitationContact Information
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