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Riesgo operacional: Un enfoque Bayesiano
[Operational Risk: A Bayesian Approach]

Listed author(s):
  • Venegas-Martínez, Francisco

Spanish Abstract: Este trabajo de investigación se concentra en el análisis de eventos de riesgo operacional, es decir, eventos que conducen a pérdidas económicas por fallas en los sistemas administrativos y en los procedimientos internos, así como por errores humanos, intencionales o no. Los diferentes tipos de eventos de riesgo operacional pueden ser estudiados en términos de su frecuencia (el número de eventos por unidad de tiempo) y su severidad (el impacto en términos monetarios). Este trabajo presenta, bajo ciertos supuestos, un conjunto de distribuciones de probabilidad sobre la frecuencia y severidad de dichas pérdidas. La estimación de los parámetros de dichas distribuciones se lleva a cabo mediante el teorema de Bayes en donde se combinan la densidad a priori del parámetro de interés con la función de verosimilitud para obtener una densidad a posteriori sobre dicho parámetro. Subsecuentemente, la distribución a posteriori se utiliza para hacer inferencias sobre el parámetro en cuestión. English Abstract: This paper focuses on the analysis of operational risk events, that is, events that lead to economic losses due to failures in the administrative systems and in the inner procedures, as well as human errors, on purpose or not. The different kinds of operational risk events can be studied in terms of their frequency (the number of events per unit of time) and their severity (the impact in monetary terms). This research presents, under certain assumptions, a set of probability distributions on the frequency and severity of such losses. The estimation of the parameters of the distributions is carried out through the Bayes theorem where the prior density of the parameter of interest is combined with the likelihood function to obtain a posterior density of such a parameter. Subsequently, the posterior density is used to make inferences about the parameter of concern.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 54849.

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Date of creation: 28 Mar 2014
Handle: RePEc:pra:mprapa:54849
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  1. Francisco Venegas-Martínez, 2005. "Bayesian Inference, Prior Information On Volatility, And Option Pricing: A Maximum Entropy Approach," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 1-12.
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