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Modeling, Measuring and Hedging Operational Risk - Hardcover

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Synopsis

Worldwide banks are keen to find ways of effectively measuring and managing operational risk , yet many find themselves poorly equipped to do this. Operational risk includes concerns about such issues as transaction processing errors, liability situations, and back-office failure. Measuring and Modelling Operational Risk focuses on the measuring and modelling techniques banks and investment companies need to quantify operational risk and provides practical, sensible solutions for doing so.
* Author is one of the leading experts in the field of operational risk.
* Interest in the field is growing rapidly and this is the only book that focuses on the quantitative measuring and modelling of operational risk.
* Includes case vignettes and real-world examples based on the author's extensive experience.

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From the Back Cover

"Dr Marcelo Cruz is rightfully acknowledged as a world expert in the quantification of operational risk. He has set out to produce a book that is comprehensive yet also comprehensible to non-mathematicians - and is to be congratulated for succeeding in this aim. This book should be regarded as essential reading for all professional risk managers, irrespective of their particular lens of perception." Brendan Young, Chairman, Operational Risk Research Forum

"As a technically trained analyst, Marcelo Cruz summarizes a wide range of mathematical techniques. As an experienced capital markets trader and risk manager, he provides real world examples of their relevance for operational risk. This will be a common reference work in the field for years to come." David M. Rowe, Ph.D., Group Executive Vice President for Risk Management Sun Gard Trading and Risk Systems

Operational risk is an important, yet little explored, area within risk management. The need to model and measure the risks arising from operational errors and to allocate capital against them will be soon become a regulatory requirement for financial institutions. In this book, Marcelo Cruz provides a quantitative look at the subject, presenting several mathematical models that can be used and adapted to measure, manage and hedge operational risk.

Based on the author's extensive experience, the book maps out state-of-the-art mathematical and statistical techniques that can be used to model operational risk. In addition, the book describes a variety of appropriate models that can be applied to specific structures or areas, including operational risk database modeling, stochastic models, statistical distributions for frequency and severity, extreme value theory, operational VaR models, artificial intelligence models, dynamic multifactor models, Bayesian analysis, Monte Carlo simulation, stress test/ scenario analysis, real options, state-space models and the Kalman filter, Markovian stochastic models and others. These models have been tested with real data in real operational events. Based on this experience, numerous examples are sited throughout.

Modeling, Measuring and Hedging Operational Risk provides a complete quantitative reference for all those involved in modeling and managing operational risk as well as for those involved with developing hedging products for operational risk within insurance companies and derivatives houses.

From the Inside Flap

The interest in operational risk has evolved exponentially in the last few years. Up until the Barings Bank collapse in 1995, the term had never been used. Dr Marcelo Cruz is one of the first people to attempt to explain clearly and technically the patterns of this new risk. He has been lecturing on operational risk since 1997 and wrote one of the first academic articles on it, in 1998.

Written in a clear and accessible manner, Modeling, Measuring and Hedging Operational Risk is essential reading for all those concerned with this evolving area of risk.

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  • PublisherWiley
  • Publication date2002
  • ISBN 10 0471515604
  • ISBN 13 9780471515609
  • BindingHardcover
  • LanguageEnglish
  • Edition number1
  • Number of pages348
  • Rating
    • 3.33 out of 5 stars
      6 ratings by Goodreads

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