Regulation and Risk management in banks depend on underlying risk measures. In general this is the only purpose that is seen for risk measures. In this paper, we suggest that the reporting of risk measures can be used to determine the loss distribution function for a financial entity. We...

The banking systems that deal with risk management depend on underlying risk measures. Following the recommendation of the Basel II accord, most banks have developed internal models to determine their capital requirement. The Value at Risk measure plays an important role in computing this...

The banking systems that deal with risk management depend on underlying risk measures. Following the recommendation of the Basel II accord, most banks have developed internal models to determine their capital requirement. The Value at Risk measure plays an important role in computing this...

Regulation and Risk management in banks depend on underlying risk measures. In general this is the only purpose that is seen for risk measures. In this paper, we suggest that the reporting of risk measures can be used to determine the loss distribution function for a financial entity. We...

The banking systems that deal with risk management depend on underlying risk measures. Following the recommendation of the Basel II accord, most banks have developed internal models to determine their capital requirement. The Value at Risk measure plays an important role in computing this...

This work presents a contribution on operational risk under a general Bayesian context incorporating information on market risk pro le, experts and operational losses, taking into account the general macroeconomic environment as well. It aims at estimating a characteristic parameter of the...

Operational risks inside banks and insurance companies is currently an important task. The computation of a risk measure associated to these risks lies on the knowledge of the so-called Loss Distribution Function. Traditionally this distribution function is computed via the Panjer algorithm...

Operational risk management inside banks and insurance companies is an important task. The computation of a risk measure associated to these kinds of risks lies in the knowledge of the so-called loss distribution function (LDF). Traditionally, this LDF is computed via Monte Carlo simulations or...

This paper proposes a simple continuous time model to analyze capital charges for operational risk. We find that undercapitalized banks have less incentives to reduce their operational risk exposure. We view operational risk charge as a tool to reduce the moral hazard problem. Our results show,...

Operational risk quantification requires dealing with data sets which often present extreme values which have a tremendous impact on capital computations (VaR). In order to take into account these effects we use extreme value distributions to model the tail of the loss distribution function. We...