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Model Risk: Identification, Measurement and Management

Edited By Daniel Rösch and Harald Scheule

Overview

Over the past decade the financial service industry has spent tremendous resources on building models to measure financial risks. Generally, these models’ predictions were used without acknowledging that reality may or may not reflect the assumptions made and thus the predictions. The book aims to provide solutions on how to include model risk into existing risk measurement frameworks. It also aims to provide solutions on how to build models of higher accuracy and thus lower model risk.

Publish date: 1 Feb 2010

Availability: In stock

Product Unit Price Qty
Model Risk: Identification, Measurement and Management
£125.00
eBook - Model Risk: Identification, Measurement and Management
EPUB
£95.00
OR

Book description

To date, model risk has lacked a clear definition and this book aims to i) explain the different types of model risk and ii) illustrate these with experiences from the current financial crisis. Examples include model risk related to the economy, stochastic volatility and areas that were previously deemed to be irrelevant or too unrealistic to incorporate into risk models. Thus, the book will provide guidance for regulators and practitioners on how to include model risk in existing risk models and how to evaluate risk models in light of model risk.

Model Risk stands out as a guide in uncertain times. This important book stands out as it enables financial institutions and their regulators to account for model risk. The result will be more accurate and pragmatic approaches to risk measurement and a more realistic view on the benefits as well as shortcomings of financial risk models. This book provides leadership and will shape industry thought in an area that currently lacks any authoritative literature on the subject.

Book details

ISBN
Book 9781906348250 / EBook 9781908823199
Publish date
1 Feb 2010
Format
Paperback
Size
155mm x 235mm

Editor biography

Daniel Rösch and Harald Scheule

Professor Dr Daniel Rösch, Institute of Banking and Finance, Leibniz Universität Hannover

Daniel Rösch is Professor of Finance and Head of the Institute of Banking and Finance at the Leibniz Universität Hannover. He received a Ph.D. from the University of Regensburg. His work covers a broad range in asset pricing and empirical finance. He has published numerous articles on risk management, credit risk, banking, and quantitative finance in leading international journals and has organized numerous executive training courses on these topics.

Dr Harald Scheule, Department of Finance, The University of Melbourne

Harald Scheule is teaching Banking and Finance at The University of Melbourne. He has worked globally as a consultant on credit risk, structured finance and securitisation projects for banks, insurance and other financial service companies. He maintains strong research relationships with the Australian, German and Hong Kong regulators for financial institutions. He has extensively published and organized executive training courses in his discipline.

Table of contents

Introduction

Daniel Rösch and Harald Scheule

Section 1: Concepts and Stochastic Frameworks for Model Risk

1 Downturn Model Risk – Another View on the Global Financial Crisis

Daniel Rösch and Harald Scheule

2 Follow the Money from Boom to Bust

Jorge Sobehart

3 Model Risk and Non-Gaussian Latent Risk Factors

Steffi Höse and Stefan Huschens

4 Model Risk in GARCH-type financial time series

Corinna Luedtke and Philipp Sibbertsen

Section 2: Regulatory Requirements for Model Risk

5 Monetary Policy, Asset Return Dynamics and the General Equilibrium Effect

Kuang-Liang Chang, Nan-Kuang Chen and Charles Ka Yui Leung

6 Capitals fall apart: Sensitivity of Economic and Regulatory Capital under Stress

Oleg Burd

Section 3: Credit Portfolio Risk Models

7 Diversified Asset Portfolio Modeling: Sources and Mitigants of Model Risk

Sean Keenan, Andrew Barnes, Stefano Santilli, Sukyul Suh, Colin McColloch and Harry Ma

8 Transmission of macro shocks to loan losses in a deep crisis: The case of Finland

Esa Jokivuolle, Oskari Vähämaa and Matti Virén

9 Comparison of credit risk models for portfolios of retail loans based on behavioural scores

Lyn C Thomas and Madhur Malik

10 Validating Structural Credit Portfolio Models

Michael Kalkbrener and Akwum Onwunta

11 Asymmetric Asset Correlation: Some Implications on the Estimation of Probability of Default

Peter Miu and Bogie Ozdemir

12 A Latent Variable Approach to Validate Credit Rating Systems

Kurt Hornik, Rainer Jankowitsch, Christoph Leitner, Manuel Lingo, Stefan Pichler and Gerhard Winkler

Section 4: Liquidity, Market and Operational risk models

13 Modelling Derivatives Cash Flows in Liquidity Risk Models

Stefan Reitz

14 Potential Future Market Risk

Manuela Spangler and Ralf Werner

15 Model Risk in Market Risk Modelling

Carsten S. Wehn

16 Estimation of Operational Value-at-Risk in the Presence of Minimum Collection Threshold: An Empirical Study

Anna Chernobai, Christian Menn, Svetlozar T. Rachev and Stefan Trück

17 Operational Risk and Hedge Fund Performance: Evidence from Australia

Robin Luo and Xiangkang Yin

Section 5: Risk Transfer and Securitisation Models

18 Identification and classification of Model Risks in Counterparty Credit Risk Measurement Systems

Marcus Martin

19 Boosting Systematic Risks with CDOs

Martin Donhauser, Alfred Hamerle and Kilian Plank

Epilogue

Joseph Breeden

Index

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