Editor: Marcelo Cruz
Published: 30 Jun 2012
Papers in this issue
by Jichuang Feng, Jianping Li, Lijun Gao and Zhongsheng Hua
by Santiago Carrillo, Henryk Gzyl and Aldo Tagliani
by J. R. Terblanché
by Rafael Hernández Barros and María Isabel Martínez Torre-Enciso
It seems as though we are back in crisis mode once again. We established The Journal of Operational Risk in 2004 and, for most of its existence, we have been in the midst of the most severe economic crisis since the Great Depression in the 1930s. The past four or five years have been very interesting for the financial community and it has proved difficult for the industry to shake off the 2007-8 crisis. This has been aggravated by economic problems in several countries, particularly in Europe. The positive side to this situation, if there is one, is that risk managers are being tested on a daily basis. It is hard to imagine a time in which risk management has received so much attention from investors, senior managers and regulators. Risk models and risk management are always tested in volatile times like these, and there is a good chance that the discipline will emerge stronger from the crisis than it ever was before.
I urge potential authors to continue to submit papers to the journal in the area of the state of operational risk research. Again, I would like to emphasize that the journal is not solely for academic authors. Please note that we do publish papers that do not have a quantitative focus, and indeed there are examples of this in the current issue. The Journal of Operational Risk would be happy to see more submissions containing practical, current views of relevant matters as well as papers focusing on the technical aspects of operational risk.
In this issue we have two Research Papers and two papers in the Forum section.
In the first paper, "Reconstructing heavy-tailed distributions by splicing with maximum entropy in the mean", Santiago Carrillo, Henryk Gzyl and Aldo Tagliani analyze the case in which a single distribution cannot explain the entire data set and where splicing is the best approach. This situation is very common in operational risk. Usually, modelers would splice the data set and the body and tail parts. Here, the authors try to assess how to assemble the two parts of the distribution in such a way that the properties of the whole data set are taken into account. This is achieved by applying the method of maximum entropy in the mean in order to splice the two parts together in such a way that the resulting global density has the first two moments of the full data set.
In the second paper, "A combination model for operational risk estimation in a Chinese banking industry case", Jichuang Feng, Jianping Li, Lijun Gao and Zhongsheng Hua highlight the impact of severity model choices upon overall operational risk capital. In order to integrate the characteristics of different heavy-tailed distributions and to increase the stability of the operational risk model, the authors propose a combination model to estimate operational risk. Their model has three stages. First, they estimate operational risk by using different heavy-tailed distributions under the loss distribution approach framework. Second, the model weights are decided according to criteria based on p-values of Kolmogorov-Smirnov tests and they are applied to decide the weight of each operational risk component. Finally, results obtained in the previous phases are combined into an integrated estimation to give the final result. The authors apply their method to a Chinese bank. It is always useful to see such a practical application.
We present two papers in the Operational Risk Forum section of this issue. The first paper is "Capital assessment of operational risk for the solvency of health insurance companies" by Rafael Hernández Barros and María Isabel Martínez Torre-Enciso. Solvency II is to insurers what Basel II is to banks. For the first time, insurers now have to allocate capital against operational risk, just as banks do. Based on a series of insured operational risk external data losses of health insurers in Spain, the authors derive an actuarial model from an operational value-at-risk analysis of the data. The paper is an interesting step-by-step account of the implementation of operational risk in an insurance environment.
The second Forum paper is "Legal risk and compliance for banks operating in a common law legal system" by J. R. Terblanché. This paper aims to provide a practical solution to the problems faced by countries with common law legal systems that wish to comply with the Basel standards. In the author's view, compliance, compliance risk and regulatory risk should all be viewed as constituent components of legal risk and, in turn, also as a component of operational risk in a common law legal system. The author defines legal risk as a wide concept that includes all aspects of a legal system, while compliance risk is a narrower concept that only includes the codified aspects of a legal system. Legal risk therefore encompasses compliance risk. However, the opposite is not true, since compliance risk does not include legal risk, and the two concepts are decidedly not synonymous in a common law system.
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