Welcome to the second issue of the second volume of The Journal of Operational Risk. I would like to thank you all for making this publication a success. In such a short existence this Journal is already one of the best sellers from within the Journals oeuvre published by Risk Journals!
For those of you who have just got 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. This Journal also aims at being a forum for discussions on this subject, facilitating the publication of not only top-quality operational risk technical papers but also papers that discuss hot topics in the industry. Research in operational risk is a field that is growing at a fast pace in both the financial industry and academia. 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 Journal of Operational Risk has been published to fulfill this much needed role. Please see the website www.journalofoperationalrisk.com for more details.
The Journal of Operational Risk is a 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 you to submit 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 three research papers in the main section. Two of them focus on the issue of dealing with heavy tails in severity statistical distributions. The remaining paper depicts a methodology based on business processes to measure and manage operational risk.
In the first paper, “Operational risk: the sting is still in the tail but the poison depends on the dose”, Jobst investigates parametric operational risk measurement methods that are Basel II compliant. Employing extreme value theory and the increasingly popular g-and-h distribution in his work, Jobst notices that a reduction in the confidence interval (or, a “smaller dose”) from the current 99.9% would probably allow financial firms to better select distributions. Jobst uses data from previous QIS to substantiate his findings.
In the following paper, “Operational risk capital: asymptotics in the case of heavy-tailed severity”, Sahay et al present a second-order asymptotic approximation of the operational VaR under heavy-tailed assumption. They compare this approximation with other relevant frequency and severity distributions characteristics.
In the final paper, “Modeling operational risk in business processes”, Cheng et al propose a different approach to model and measure operational risk that is complementary to the LDA and try to understand the risk embedded in the processes of a firm.
Operational Risk Forum
This section is intended to provide a less formal forum on findings and ideas about operational risk without the academic rigor demanded in the main section. The mission of the Forum is to promote active discussions of current issues in operational risk.
In this current issue, Adusei-Poku et al show a real case of the application of Bayesian techniques in measuring operational risk in their article “Implementing a Bayesian network for foreign exchange settlement: a case study in operational risk management”.
Implementing a Bayesian network for foreign exchange settlement: a case study in operational risk management