Rabu, 12 Februari 2014

[Y972.Ebook] Ebook Download The Validation of Risk Models: A Handbook for Practitioners (Applied Quantitative Finance), by S. Scandizzo

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The Validation of Risk Models: A Handbook for Practitioners (Applied Quantitative Finance), by S. Scandizzo

The Validation of Risk Models: A Handbook for Practitioners (Applied Quantitative Finance), by S. Scandizzo



The Validation of Risk Models: A Handbook for Practitioners (Applied Quantitative Finance), by S. Scandizzo

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The Validation of Risk Models: A Handbook for Practitioners (Applied Quantitative Finance), by S. Scandizzo

This book is a one-stop-shop reference for risk management practitioners involved in the validation of risk models. It is a comprehensive manual about the tools, techniques and processes to be followed, focused on all the models that are relevant in the capital requirements and supervisory review of large international banks.

  • Sales Rank: #1154167 in Books
  • Published on: 2016-04-20
  • Released on: 2016-04-20
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.30" h x .90" w x 6.10" l, .0 pounds
  • Binding: Hardcover
  • 242 pages

Review

“A book that sheds a required and well-timed light on the perpetual debate, inside any organisation, between risk validation of model, models for risk validation and model risk.  The tools and techniques proposed are valid not only for practitioners working within regulated entities but for all the risk managers in search of a guide into the model validation’s definition and best practices.” (Cosimo Pacciani, Chief Risk Officer, European Stability Mechanism)

“This book is a very useful reference for professionals and ought to be a core text book for every professional in charge of risk models or their validation. It is well written and explains the nature of model risks in finance, introduces a framework for risk model validation and provides further illustrations for specific type of risks and risk measurement approaches. A distinctive feature of this book is its focus on practical challenges most practitioners may have already come across together with a sound reference to finance theory. There is no book I am aware of that covers risk model validation in that practical and comprehensive manner.” (Sven Muehlenbrock, Partner, Head of Risk Advisory, KPMG Luxembourg)

From the Back Cover
The practice of quantitative risk management has reached unprecedented levels of sophistication. The pricing, the assessment of risk as well as the computation of the capital requirements for highly complex transactions are performed through equally complex mathematical models, running on sophisticated computer systems, developed and operated by dedicated, highly qualified specialists. With this sophistication, however, come risks that are unpredictable, globally challenging and difficult to manage. Model risk is a prime example of these and precisely the kind of risk that those tasked with managing financial institutions as well as those overseeing the soundness and stability of the financial system should worry about.

This book starts with setting the problem of the validation of risk models within the context of banking governance and proposes a comprehensive methodological framework for the assessment of models against compliance, qualitative and quantitative benchmarks. It provides a comprehensive guide to the tools and techniques required for the qualitative and quantitative validation of the key categories of risk models and introduces a practical methodology for the measurement of the resulting model risk and its translation into prudent adjustments to capital requirements and other estimates.

About the Author
Sergio Scandizzo is the Head of Model Validation at the European Investment Bank (EIB) in Luxembourg. He is the author of Risk and Governance: A Framework for Banking Organisations; The Operational Risk Manager's Guide, now in its second edition, and of Validation and Use Test in AMA. He is Associate Editor of The Journal of Operational Risk and has published several journal papers on fuzzy logic, genetic algorithms and risk management.

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