Welcome to the first issue of the fourth year of The Journal of Operational Risk. I would like to compliment the entire Journal family for this major accomplishment! In such testing times when quite a few larger publications face tremendous difficulties we are stronger than ever with rising numbers of subscribers, top-quality subscriptions and a very motivated editorial board. As I travel across the globe on business trips or when speaking at conferences it still surprises me to see how influential within the industry our Journal has become.
Being published in the Journal is a true honor for authors, and operational risk practitioners cannot afford to miss the articles we have here every quarter. I would like this time to give a special thanks to Lucie Carter for her dedication and excellent work and also for her patience with the innumerous correspondence the both of us exchange on a daily basis to get the issues out. The entire Journal community should be immensely thankful to her.
Regarding the perennial financial crisis, it seems likely that it is bound to stay with us for quite a while. The US is now in a 14-month recession with no signs so far of any recovery. The depth of this crisis has also been previously unseen by our generation. This has taken a heavy toll on our profession. As the financial industry, particularly in the US and the UK, fights for survival and the largest banks are in very fragile health, we witness that many of our colleagues have been laid off and even worse blamed for not properly managing the crisis. This is very unfortunate and unfair. As we mentioned before, there is a real need for reinventing risk governance. This crisis is a great opportunity for rethinking these issues.
Concerning the state of operational risk research, I would like to ask potential authors not to feel discouraged by the crisis to submit to the Journal. We have seen a decreased flow of papers recently that we are blaming on the current economic environment. I would also like to re-emphasize that the Journal is not just for academics to publish in. We at The Journal of Operational Risk incentivize readers to submit papers to the ‘Forum’ section. This section is aimed at discussing current events without too much concern for the technical aspect, formulas and mathematics. We at the Journal will be extremely happy to see more submissions with more practical, current views of relevant matters that affect dayto- day operations.
In this issue we bring you three papers in the research section and one paper in the forum section. For the first time we bring a paper on supply risk, which is also related to operational risk as you will notice. I would like to highlight the importance that Bayesian analysis is taking in operational risk as two of the papers presented use this technique to cope with data aggregation.
In the first paper, “Modeling operational risk in financial institutions using hybrid dynamic Bayesian networks”, Neil et al propose the use of causal model hybrid dynamic Bayesian networks to model operational risk that also generates a value-atrisk figure. This model is particularly interesting as its outcomes allow us not only to satisfy economic and regulatory capital needs but also to manage operational risk within the organization.
In the second paper, “Estimating the lognormal-gamma model of operational risk using the MCMC method”, Ergashev, a regular contributor to the Journal, tackles the difficulties in modeling the lognormal-gamma distribution, a very attractive aggregate distribution for operational risk modeling given its heavy tail characteristics and also closed form solutions. He addresses the issues by using Markov chain Monte Carlo techniques, another Bayesian approach.
In the third paper, “Supply portfolio risk”, Haksoz and Kadam use the Credit- Risk+ framework to measure the risk of contract breaches (an operational risk) to a supply chain. This is the first paper that we publish on supply chains and this is a subject that we would like to see more authors submitting works on.
Operational Risk Forum
In the forum section, Brunner et al provide a short discussion note on fat tails, expected shortfall and Monte Carlo simulations. In their short note they try to demonstrate that the Monte Carlo method can have extremely bad convergence properties for heavy tailed distributions in combination with specific risk measures, including conditional value-at-risk.