For the first time in a long while there is a positive economic perspective. According to the Federal Reserve the current economic recession in the US, which began in December 2007, apparently ended in August 2009. Many indicators tend to corroborate this theory as we can now see some recovery in demand, consumer confidence and corporate results. The same feeling is being felt worldwide. Despite this less gloomy mood in the industry unemployment is still peaking, which would tame any recovery for the time being. In any case, it looks like the banking industry is safe for now. However, this safety has cost hundreds of billions of dollars of taxpayers' money, particularly in the US and the UK, the most important financial centers. It has also changed perspectives on risk management. Risk managers are still working to find ways of improving governance and measurement models to avoid another crisis like the current one.
Regarding the state of operational risk research, I would like to ask potential authors not to feel discouraged by the crisis.We have seen a decreased flow of papers recently that we can attribute to the current economic environment. I would also like to re-emphasize that the Journal is not only intended for academics to publish papers. We at The Journal of Operational Risk encourage readers to submit papers to the “Forum” section. This section is aimed at discussion of current events without too much concentration on the technical aspect, formulas or mathematics. We would be extremely happy to see more submissions with a more practical, current view of relevant matters that affect day-to-day practice.
This issue is slightly unusual with regards to the allocation of papers. This time we bring you two papers in the research section and two papers in the forum section. Since we have requested more papers in the forum section we have received many contributions, which is fantastic for the journal. Thus, we are presenting two papers in this section.
In the first paper, “Operational risk quantification using extreme value theory and copulas: from theory to practice”, Gourier et al point out issues of stability in the coherence of value-at-risk (VaR) under heavy-tailed data, using copulas for correlation. They argue that standard economic thinking about risk diversification may be inappropriate when infinite-mean distributions are involved, as is the case in operational risk much of the time. This is a very important discussion and I invite readers to take time to read this excellent paper.
In the second paper, “Bayesian analysis of extreme operational losses”, Liang brings us his research on Bayesian analysis for operational risk distributions. This is a recurrent theme in recent research and one of the most exciting research lines in operational risk currently. Using Bayesian analysis to incorporate other information into operational VaR is probably the most elegant way to come up with a single risk measure in operational risk that incorporates the four types of data required by Basel II. In this paper the author investigates, with simulated examples, how Bayesian analysis can be used to estimate the parameters of extreme value models, both for the case where we have no prior knowledge and the case where we have prior knowledge in the form of expert opinion.
In the first paper of the forum section, “Swiss cheese and the PRiMA model: what can information technology learn from aviation accidents?”, Bergeon and Hensley introduce a predictive risk mitigation model based on a certain “Swiss cheese theory”. Their model, named predictive risk mitigation analysis (PRiMA) is designed to complement traditional risk assessment, management and mitigation techniques in order to prevent operational incidents and limit their impact, if they should occur. This type of modeling is interesting for operational risk control and prevention and is therefore good, non-technical reading.
In the second paper of the forum section, “Measuring causal influences in operational risk”, Cech identifies issues inherent in the development of an operational risk causal taxonomy. The author suggests a staged approach that firms may employ to generate useful causal content, consistent with their existing operational risk methodologies and program investments.