Journal of Operational Risk

Marcelo Cruz

Lehman Brothers

Welcome to the fourth issue of the second volume of The Journal of Operational Risk. With this issue we close the second year of the Journal.We are very pleased with the increasing support that the Journal has been receiving from the financial industry, practitioners and academics. The Journal of Operational Risk is one of the publishers most successful publications thanks to your contributions and continuous support.

In terms of the economic environment, most of these two years were spent during a reasonably quiet moment in the world markets yet this is not the current perspective. The financial markets are still trying to understand the full impact of the US subprime mortgage crisis and the world markets keep seeing high levels of volatility.

For the first time in many years there are conjectures about a possible recession in the US that would certainly have a strong impact everywhere. It would be interesting to see how operational risk behaves in moments like this.

For those of you who are just getting hold of this Journal for the first time, the main objective of The Journal of Operational Risk is to publish high-quality research on the risk measurement and management of operational risk and to promote greater understanding of this new and fast growing area of risk. There are currently many lines of research, most of them trying to overcome the challenges presented by the new regulatory standards created by the Basel II Accord. However, currently there is not a single forum for the debate of these ideas. The mission of the Forum section is to promote active discussions of current issues in operational risk. The articles that we would like to see in the Forum are designed to be tutorial and highly educational in nature. The main goal of the submitted articles is to bring a higher level of understanding to both industry and academia on issues and topics that might not normally be readily and easily accessible to either side. The Journal of Operational Risk comes to fulfill this much needed role, please visit the website www.journalofoperationalrisk.com for more details.

The Journal of Operational Risk is the vehicle for communicating results in the modeling and management of operational risk. Examples of some areas of interest are: statistical/actuarial methods and estimation issues, causal models, extreme value theory, scenario analysis based models, Bayesian methods, uses of external data within the framework, etc. We also encourage the submission of papers on new ideas and research on subjects such as corporate governance, business continuity plans, enterprise-wide risk, financial crime and the development of controls to avoid them, insurance, etc.

At this moment I would like to invite you to really appreciate the high quality of the articles in this edition of The Journal of Operational Risk.We thank the authors for their trust in this growing publication and appreciate all the encouraging messages sent by a number of colleagues in the industry and academia. All of this gives us comfort that we are taking the right steps to build this new global industry forum for operational risk.

In this issue, there are four exceptional research papers in the main section. We usually have two or three but, given that we are receiving a greater number of higher quality papers, we decided to select these four papers and not to present any papers in the Forum section.

In the first paper, "Addressing the impact of data truncation and parameter uncertainty on operational risk estimates", Luo et al tackle one of the emerging subjects in operational risk estimation, analyzing the issue of data truncation, which is very common in this area as frequently losses are reported only above a certain threshold. The authors analyze two cases in which data truncation is ignored: the "naive model" - fitting a lognormal distribution with support on a positive semi-infinite interval, and a "shifted model" - fitting a lognormal distribution shifted to the truncation level.What they have found is that the "naive model" leads to underestimation (that can be severe) of the 0.999 quantile. The "shifted model" overestimates the 0.999 quantile except in some cases of smaller underestimation for larger truncation levels.

In the second paper, "A systemic approach to operational risk measurement in financial institutions", Kessler sees operational risk from a different perspective. She sees operational risk measurement from a systemic approach. Her guiding method is general systems theory, which is used to describe the essential system features of a complex domain.

In the third paper, "A statistical method to optimize the combination of internal and external data in operational risk measurement", Figini et al tackle the issue of combining data from different sources. Here the authors claim to have found an optimal way to combine internal and external data.

In the fourth paper, "Statistical models for business continuity management", Bonafede et al address the issue of business continuity management using statistical models, which is very innovative.

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here: