Evaluating Operational Risk by an Inhomogeneous Counting Process Based on Panjer Recursion

22 Pages Posted: 14 Jun 2016

Date Written: March 21, 2016

Abstract

Operational risk (OpRisk) is increasingly being considered an important financial risk. In recent years, it has been given more consideration due to economically disturbing events. The loss distribution approach (LDA) is one of the demanding models suggested by the Basel Committee on Banking Supervision (BCBS). The purpose of this paper is to propose a new approach for determining operational value-at-risk (OpVaR) using an inhomogeneous counting process based on Panjer recursion as the frequency distribution, and generalized Pareto distributions and generalized extreme value distributions are used to model the severities. We focus on the inhomogeneous Panjer process (IPP) and investigate its properties. In this paper, we present the LDA for computing OpRisk using IPP. The closed-form expression for the moment generating function for determining the aggregate loss distribution is derived. We generalize well-known classical models and derive the statistical characteristics for modeling loss distribution. An illustration is presented to demonstrate the applicability of the proposed model in OpRisk and also discuss various special cases of the model.

Keywords: Panjer distribution, Pochhammer symbol, operational risk (OpRisk), loss distribution approach (LDA), compound random variable

Suggested Citation

Jiménez Moscoso, José Alfredo and Arunachalam, Viswanathan, Evaluating Operational Risk by an Inhomogeneous Counting Process Based on Panjer Recursion (March 21, 2016). Journal of Operational Risk, Vol. 11, No. 1, 2016, Available at SSRN: https://ssrn.com/abstract=2795056

José Alfredo Jiménez Moscoso

National University of Colombia ( email )

Carrera 30 45-03
Bogota, CO 111321
Colombia
(571)3165000 (Phone)

HOME PAGE: http://www.unal.edu.co

Viswanathan Arunachalam (Contact Author)

National University of Colombia ( email )

Carrera 30 45-03
Bogota, None
Colombia

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