Showing posts with label operational risk. Show all posts
Showing posts with label operational risk. Show all posts

Modeling, Measuring and Hedging Operational Risk Review

Modeling, Measuring and Hedging Operational Risk
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This is a much expected book in the operational risk area. I have got one as soon as it was released and I am getting more impressed with it every day as I try the models suggested by the author. The book is composed by a coherent sequence of mathematical models and techniques (all nicely explained with examples and extremely well-written)that at the end help you to measure and manage operational risk in practice. All the examples use real loss data and key risk indicators.
It is hard to identify the best part of the book. The chapters on causal models and stress tests are just a prime in the area as much as those on operational VaR. The text on stochastic models left me asking "why didn't I think of that before?". The chapters on the measurement of "soft risks" as those on reputational and key personnel risks are the first that I have seen on the subject and give an excellent insight on how to deal with this extremely difficult subject. This book should be on the shelf of any financial risk manager and it will set up the standards in the area for the next years. Operational risk finally find its "riskmetrics". As much as one day 'riskmetrics', 'creditmetrics' and CreditRisk+ were released by JP Morgan and CSFB setting up the grounds for the development of the both market and credit risk measurement, this book do the same for operational risk. At least everyone involved with operational risk should have it if not for anything just as a reference.

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Operational Risk : Modeling Analytics (Wiley Series in Probability and Statistics) Review

Operational Risk : Modeling Analytics (Wiley Series in Probability and Statistics)
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I train and consult bankers in credit and operational risk modeling for a living. I mention this because I think I have a decent feel for the pedagogy necessary for helping practitioners grasp the step-by-step application of these often highly theoretical concepts. Not all of us are rocket-scientists from birth and even though I have a quantitative PhD from Princeton, my often slow brain likes having things explained in simple terms. Panjer's book does this beautifully.
He has found the perfect balance between rigor and application--both in the exposition and scope of the book. He also includes examples of every concept that are easy to follow, replicate and extend. Moreover, Panjer takes you right to the edge of where advanced modeling of operational risk is at present. For example, he discusses EVT, copulas, infinite-mean models, kernel smoothing, robust methods, Bayesian methods, aggregation principles and compound processes as well as model selection--all of which characterize the current state of operational risk modeling and research. Indeed, beyond these points of technical modeling, most researchers (even mathematicians) are starting to agree that the returns are greatly diminishing and better qualitative/quantitative mixtures need to be developed (see Neslehova, et.al. Journal of Operational Risk, Spring, (2006)).
"Weak" spots in the book relate, for example, to how it fails to base itself firmly within the current operational risk literature. This is without loss of generality during this the infancy of operational risk modeling but I believe subsequent editions should address (at least to comment on) the growing number of papers popping up on websites and in trade journals. On the other hand, since I am not a statistician, I appreciated the author's references within that field as many of the topics are not part of the standard statistics canon. Finally, the book does not discuss operational risk management though, buying a book entitled "Operational Risk Modeling", I am not sure whether or why anyone would expect it to.
If this book were twice the price (such as for RiskBooks) I would still be happy with my purchase.

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Discover how to optimize business strategies from both qualitative and quantitative points of viewOperational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors.Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts.Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science.In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features:* Ample exercises to further elucidate the concepts in the text* Definitive coverage of distribution functions and related concepts* Models for the size of losses* Models for frequency of loss* Aggregate loss modeling* Extreme value modeling* Dependency modeling using copulas* Statistical methods in model selection and calibrationAssuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also useful as a reference for practitioners in both enterprise risk management and risk and operational management.

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