by Harry H. Panjer
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Product Description
Discover how to optimize business strategies from both qualitative and quantitative points of view
Operational 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 calibration
Assuming 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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Average Customer Review:
3 of 3 people found the following review helpful:
Best quantitative OR book, 2007-02-13
This book covers all the quantitative topics around the loss distribution approach for OR. It follows an actuarial-driven approach to explain the models for frequency, severity and aggregation of loss distribution, and the relative statistical estimating and testing. But do not look for OR management topics in this book: it give its best in the actuarial measurement of operational risk.
8 of 8 people found the following review helpful:
Best overview of operational risk modeling techniques currently available, 2006-12-06
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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