Rethinking Risk Measurement and Reporting: v. 2

Table of Contents:
About the Editor About the Authors Introduction 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 Guner; 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 Christoff Gossl UniCredit 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 Universitat Munchen; 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 Husebo, 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. Wuthrich CSIRO Mathematics, Informatics and Statistics; RiskLab ETH Zurich 14 Bayesian Estimation of Levy Copulas for Multivariate Operational Risks Philipp Gebhard, Gernot Muller; Klaus Bocker Technische Universitat Munchen; UniCredit Group

About the Author :
Klaus Bocker Klaus Bocker works as a senior risk controller in UniCredit Group and is the team head of Risk Analytics and Methods. In this capacity, one of his primary responsibilities is overseeing all quantitative aspects of UniCredit Group's economic capital model, in particular business risk, real-estate risk, financial investment risk and risk aggregation. Klaus is also a research fellow at the Center for Mathematical Sciences at the Technische Universitat Munchen. 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 Universitat Munchen.

Review :
"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 Bocker 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 Bocker, 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." Michael Gordy "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