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Rethinking Risk Measurement and Reporting - Volumes I and II

Rethinking Risk Measurement and Reporting - Volumes I and II

Name: Rethinking Risk Measurement and Reporting - Volumes I and II
Brand: Risk Books
SKU: 9781906348946
Price: 3022.50 HKD
Availability: OutOfStock
Author: Klaus Böcker
ISBN: 9781906348946

By Klaus Böcker

Risk Books November 2010

Specifications

ISBN-13: 9781906348946
Publisher: Risk Books
Publication: November 2010
Format: Paperback (2 volumes)
Jurisdiction: International ? Countri(es) for reference only

Details

Rethinking Risk Measurement and Reporting aims to increase the readers’ awareness of model and parameter uncertainty when using mathematical models in financial risk management. This book, which is being published in two volumes, helps the reader to discern that model uncertainty must be accepted as an intrinsic part of risk measurement.

The 2007-9 crisis has exposed the issue of reliability in mathematical risk quantification and highlighted the importance of taking measurement uncertainty into account when measuring and reporting risk and the subsequent decision-making process. It is essential that risk managers rethink the way they measure and control risk in order to avoid another industry shattering crisis. Uncertainty of risk figures needs to be better understood and expert judgement needs to be absorbed into the fabric of risk management. Rethinking Risk Measurement and Reporting contains the leading techniques and tools that the risk management industry will need to make the step towards a more effective risk management framework.

Both volumes of Rethinking Risk Measurement and Reporting provide critical reviews of standard risk models used in practice, useful techniques to assess model uncertainty such as expert judgement and tools that allow you to analyze the impact of this uncertainty on the final result; typically a risk figure that is used in risk control, risk management or decision making. Emphasis is given to Bayesian methods, by which it is possible to analyze model uncertainty in a statistically sound and efficient way.

The two volumes present practical examples relating to risk types and, in addition, you the reader will gain an overall picture of a 'complete’, improved risk management framework:

An Introduction to Bayesian Analysis
Expert Judgement
Credit Risk
Operational Risk
Market Risk and Time Series Analysis
Stress Testing and Risk Aggregation
Asset Allocation
Reporting, Decision Making and Regulation

Klaus Böcker brings together the most highly regarded practitioners and academics within risk management to provide a well-thought out, integrated approach for improving existing risk measurement, management and reporting. The first volume includes the PRMIA 2010 award winning paper as the chapter 'Bayesian Risk Aggregation: Correlation Uncertainty and Expert Judgement’. The experience collected in both volumes is invaluable and makes this a must read for everyone who is working in the financial industry, particularly in risk management.

Volume 1...

About the Editor

About the Authors

Foreword

Introduction

PART I AN INTRODUCTION TO BAYESIAN ANALYSIS

1 On Bayesian Data Analysis

Christian P. Robert, Judith Rousseau

Université Paris-Dauphine

2 On Computational Tools for Bayesian Data Analysis

Christian P. Robert; Jean-Michel Marin

Université Paris-Dauphine; Université Montpellier 2

3 Bayesian Analysis of the Normal Regression Model

Ioannis Ntzoufras

Athens University of Economics and Business

4 Market Correlations in the Euro Changeover Period with a View to Portfolio Management

Gernot Müller

Technische Universität München

5 Robustification of Bayesian Portfolio Allocation

Katrin Schöttle; Ralf Werner; Rudi Zagst

MEAG MUNICH ERGO AssetManagement GmbH; Deutsche Pfandbriefbank AG; Technische Universität München

PART II EXPERT JUDGEMENT

6 Eliciting Univariate Probability Distributions

Jeremy E. Oakley

University of Sheffield

7 Eliciting Multivariate Probability Distributions

Alireza Daneshkhah; Jeremy E. Oakley

University of Strathclyde; University of Sheffield

8 Multiple Dependent Experts’ Opinions: An Illustration from Operational-Risk Measurement

Jean-Philippe Peters

Deloitte

PART III STRESS TESTING, DEPENDENCE MODELLING, RISK AGGREGATION AND ALLOCATION

9 A Bayesian Approach to Coherent Stress Testing

Riccardo Rebonato

Royal Bank of Scotland, Risk Management and Quantitative Analytics, Oxford University, Imperial College, London

10 The Limits of Securitisation: Micro-correlations, Fat Tails and Tail Dependence

Carolyn Kousky; Roger M. Cooke

Resources for the Future; Resources for the Future and Delft University of Technology

11 Vines and Continuous Non-parametric Bayesian Belief Nets with Emphasis on Model Learning

Dorota Kurowicka; Roger M. Cooke

Delft University of Technology; Resources for the Future and Delft University of Technology

12 Bayesian Risk Aggregation: Correlation Uncertainty and Expert Judgement

Klaus Böcker, Alessandra Crimmi; Holger Fink

Risk Analytics and Methods, UniCredit Group; Technische Universität München

13 Bayesian Approaches for Portfolio Construction: A Review

Daniel Giamouridis

Athens University of Economics and Business and Cass Business School

PART IV REPORTING, DECISION MAKING AND REGULATION

14 Regulators under Uncertainty: The Impact of Model Uncertainty and Information Asymmetry

An Chen; Xia Su

University of Bonn; Commerzbank

15 The Psychology of Risk Management

Gaëlle Villejoubert, Frédéric Vallée-Tourangeau

Kingston University

16 What Is Risk? Towards a Unifying Approach

Terje Aven

University of Stavanger, Norway

17 Amalgamating Bayesian Experts: A Sceptical View

Joseph B. Kadane

Carnegie Mellon University

18 The Model and the Manager: Risks Identified and Resolved?

Sebastian Fritz-Morgenthal

HSH Nordbank, Hamburg

19 Re-Thinking Valuation: The Credit Crisis, Illiquid Markets and Model Risk

Dan Rosen

R2 Financial Technologies

20 Why Banks Failed the Stress Test

Andrew G. Haldane

Bank of England

Volume II...

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 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

Christoff Gössl

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 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

About the Author

Klaus Böcker

Klaus Böcker 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 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.

Reviews

“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.”

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

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