Using weighted distributions to model operational risk

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<title>Using weighted distributions to model operational risk</title>
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<namePart>Afonso, Lourdes B.</namePart>
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<namePart>Corte Real, Pedro</namePart>
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<abstract displayLabel="Summary">The quantification of operational risk has to deal with various concerns regarding data, much more than other types of risk which banks and insurers are obliged to manage. One of the main questions that worries both researchers and practitioners is the bias in the data on the operational losses amounts recorded. This concern is serious when modeling operational losses data and, typically, is presented in all the databases. It is shows that it's possible, based on mild assumptions on the internal procedures put in place to manage operational losses, to make parametric inference using loss data statistics, that is, to estimate the parameters for the losses amounts, taking in consideration the bias that, not being considered, generates a two fold error in the estimators for the mean loss amount and the total loss amount, the former being overvalued and the last undervalued</abstract>
<note type="statement of responsibility">Lourdes B. Afonso, Pedro Corte Real</note>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
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<text>02/05/2016 Volumen 46 Número 2 - mayo 2016 , p. 469-485</text>
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