Rethinking Risk Measurement and Reporting VOL I

Rethinking Risk Measurement and Reporting VOL I

Stress Testing (2nd Edition)

Stress Testing (2nd Edition)

Rethinking Risk Measurement and Reporting Vol II


Model uncertainty must be accepted as an intrinsic part of risk measurement. This insight is the starting point for Rethinking Risk Measurement and Reporting, which identifies how uncertainty of risk figures can be better understood and expressed and how expert judgement can be absorbed into the fabric of modern risk management.

Edited by Klaus Böcker and published in two volumes, Rethinking Risk Measurement and Reporting, will raise the reader’s awareness of model and parameter uncertainty when using mathematical models in financial risk management.

This second volume is divided into three sections and discusses a broad spectrum of financial applications, with practical examples, by risk type. Volume II builds on the foundations of the first volume, providing a higher degree and intensity of technical content. Tools and techniques are divided by their application for:

  • Market Risk
  • Credit Risk
  • Operational Risk

Klaus Böcker has assembled leading practitioners and academics within risk management fraternity to provide a comprehensive and integrated approach for improving existing risk measurement, management and reporting.

Availability: In stock


The 2007-9 crisis highlighted the dangers of dependence on risk quantification and the importance of taking measurement uncertainty into account. Today, risk managers recognise the need to rethink the way they measure and control risk, and how their findings inform decision-making. Rethinking Risk Measurement and Reporting (volumes 1 and 2) speaks to these needs, providing the techniques and tools for a more effective risk management framework.

“...This book brings together the best researchers into how these deep ideas can benefit financial risk management.”

David Spiegelhalter, Winton Professor of the Public Understanding of Risk, University of Cambridge

More Information
ISBN 9781906348502
Navision code MRR2
Publication date 8 Nov 2010
Size 155mm x 235mm
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1 Efficient Bayesian Estimation and Combination of Garch-Type Models

David Ardia; Lennart F. Hoogerheide

aeris CAPITALAG Switzerland; Erasmus University Rotterdam

2 Bayesian Inference for Stochastic Volatility Modelling

Hedibert F. Lopes, Nicholas G. Polson

The University of Chicago Booth School of Business

3 Bayesian Prediction of Risk Measurements Using Copulas

Maria Concepcion Ausin; Hedibert Freitas Lopes

Universidad Carlos III de Madrid; University of Chicago Booth School of Business

4 Bayesian Inference for Hedge Funds with Stable Distribution of Returns

Biliana Güner; Svetlozar T. Rachev; Daniel Edelman; Frank J. Fabozzi

Yeditepe University; FinAnalytica; UBS Alternative and Quantitative Investments LLC; Yale School of Management

5 Model Uncertainty and Its Impact on Derivative Pricing

Alok Gupta, Christoph Reisinger, Alan Whitley

University of Oxford


6 Predictions Based on Certain Uncertainties: A Bayesian Credit Portfolio Approach

Christoff Gössl


7 Uncertainty in Credit Risk Parameters and Its Implication on Risk Figures

Christina R. Bender; Ludger Overbeck

d-fine GmbH; University of Giessen

8 Lessons from the Crisis in Mortgage-Backed Structured Securities: Where Did Credit Ratings Go Wrong?

Erik Heitfield

Federal Reserve Board

9 Rethinking Credit Risk Modelling

Christian Bluhm; Christoph Wagner

Technische Universität München; Allianz Risk Transfer

10 The Bayesian Approach to Default Risk: A Guide

Michael Jacobs Jr; Nicholas M. Kiefer

US Department of the Treasury, Office of the Comptroller of the Currency; Cornell University

11 Bayesian Modelling of Small and Medium-Sized Companies’ Defaults

Mathilde Wilhelmsen, Xeni K. Dimakos; Tore Anders Husebø, Marit Fiskaaen

Norwegian Computing Center; Centre of Excellence Credit Risk Modelling, Sparebank 1


12 Measuring Operational Risk in a Bayesian Framework

Luciana Dalla Valle

University of Milan

13 Operational Risk: Combining Internal Data, External Data and Expert Opinions

Pavel V. Shevchenko; Mario V. Wüthrich

CSIRO Mathematics, Informatics and Statistics; RiskLab ETH Zurich

14 Bayesian Estimation of Lévy Copulas for Multivariate Operational Risks

Philipp Gebhard, Gernot Müller; Klaus Böcker

Technische Universität München; UniCredit Group