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.
“This volume offers the reader an introduction to Bayesian analysis followed by the consideration of techniques for eliciting and weighting expert judgments. Incorporating seasoned judgment and a greater appreciation of what we do not and cannot know about the future will be a long and arduous journey, but as the Chinese philosopher Lao-tzu said: “A journey of a thousand miles begins with a single step.” Hopefully, this book represents a first step on this much needed transformation of the practice of risk management.”
David M. Rowe, Risk Advisory
“Rethinking Risk Measurement and Reporting is an important new collection of essays thst should have a significant impact on the practice of risk management in many fields. In particular, as the world tries to learn the lessons of the global financial crisis of 2007-9 this book should be required reading for both regulatory agencies and financial institutions.
Klaus Böcker has created a well-organised and balanced development, with chapters written by some outstanding thinkers and researchers. His ‘Introduction’ displays his own careful thought and makes a powerful case for adopting the tools of Bayesian analysis and expert judgement. The over-arching theme is uncertainty: uncertainty as the driver of risk, uncertainty and probability as the language of Bayesian statistics, and the role of expert judgement in quantifying and mitigating uncertainty.
Risk is a multidisciplinary field, and Rethinking Risk Measurement and Reporting will be of interest to statisticians, psychologists and mathematical modellers, as well as to risk professionals.”
Tony O'Hagan, University of Sheffield
“The current financial crisis is a wake up call for risk measurement methodology. This book takes up the gauntlet and presents a broad array of papers addressing issues from the realm of uncertainty and risk relevant for banking and finance. As to be expected, the Bayesian paradigm figures prominently. Risk managers from academia to practice will highly welcome this volume.”
Paul Embrechts, Director of RiskLab, ETH Zurich.
“The financial crisis has clearly shown the dangers of overreliance on pure quantitative models, and there is now a widespread awareness that algorithms must be carefully calibrated through expert judgement. Yet, the latter has weaknesses of its own, unless managed through appropriate techniques and schemes. Award-winner Klaus Böcker, following his path-breaking contributions on Bayesian analysis in risk aggregation, now provides a rigorous yet refreshing book on how risk should be conceived and dealt with in financial institutions: definitely a must-read for those looking for new ideas to revive the dented axioms of risk management.”
Andrea Resti, Bocconi University
“Of the many failings of risk management prior to the crisis of 2007-09, the neglect of parameter uncertainty is perhaps the least forgivable because this uncertainty could have been measured and recognized ex-ante and with available data. Practitioners will find in this book a variety of practicable approaches to rigorous estimation and robust treatment of parameter uncertainty and other forms of model risk.”
“Bayesian analysis allows us to consider uncertainty in a rich and subtle way. We are all used to essential unpredictability, but we can also use probability theory to express our doubts about appropriate values for parameters in our models. Then the Bayesian approach goes deeper: encouraging us to confront our ignorance about how the world works and how well our models might be able to mimic what is going on. 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
About the Authors
PART I MARKET RISK AND FINANCIAL TIME SERIES
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
PART II CREDIT RISK
6 Predictions Based on Certain Uncertainties: A Bayesian Credit Portfolio Approach
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?
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
PART III OPERATIONAL RISK
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
Klaus is also a research fellow at the Center for Mathematical Sciences at the Technische Universität München. He is conducting research in various fields of finance where he has authored and co-authored several articles that have been published in various recognized finance and mathematical journals.
Klaus is also a frequent speaker at international risk conferences and at seminars about risk management and quantitative finance. In 2007, 2008 and 2010, he won the PRMIA Institute’s Award for New Frontiers in Risk Management related to his research activities. In August 2007, Klaus was inducted by his peers as a charter member of the international Risk Who's Who honor society. He holds a degree in Theoretical Physics and a PhD in Mathematics from the Technische Universität München.