Integrated Market and Credit Portfolio Models Risk Measurement and C
Due to their business activities, banks are exposed to many different risk types. Aggregating various risk exposures to a comprehensive risk position is an important but up-to-date not satisfactorily solved task. This shortfall goes back to conceptual pro
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nbf neue betriebswirtschaftliche forschung Band 361
Peter Grundke
Integrated Market and Credit Portfolio Models Risk Measurement and Computational Aspects
With a foreword by Univ.-Prof. Dr. Thomas Hartmann-Wendels
GABLER EDITION WISSENSCHAFT
Bibliographic information published by Die Deutsche Nationalbibliothek Die Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the Internet at .
Habilitationsschrift Universität zu Köln 2006
1st Edition 2008 All rights reserved © Betriebswirtschaftlicher Verlag Dr. Th. Gabler | GWV Fachverlage GmbH, Wiesbaden 2008 Editorial Office: Claudia Jeske Gabler-Verlag is a company of Springer Science+Business Media. www.gabler.de No part of this publication may be reproduced, stored in a retrieval system or transmitted, mechanical, photocopying or otherwise without prior permission of the copyright holder. Registered and/or industrial names, trade names, trade descriptions etc. cited in this publication are part of the law for trade-mark protection and may not be used free in any form or by any means even if this is not specifically marked. Cover design: Regine Zimmer, Dipl.-Designerin, Frankfurt/Main Printed on acid-free paper Printed in Germany ISBN 978-3-8349-0875-9
Preface Banks are exposed to various kinds of risks; among them are credit default risks, market price risks and operational risks the most important ones. Aggregating these different risk exposures to a comprehensive risk position is an important, yet challenging and up to now unresolved task. Banks’ current state of the art in risk management is still far away from achieving a fully integrated view of the risks they are exposed to. This shortfall traces back to both, to conceptual problems of constructing an appropriate risk model and to the computational burden of calculating a loss distribution.
The approach presented in this book takes credit default risk as a starting point. By integrating market risks, a general credit risk model is constructed that comprises the standard industry credit risk models as special cases. Within the framework of this general credit risk model, the effects of simplifying assumptions that are typical for standard credit risk models can be analyzed. Important insights gained by this analysis are that neglecting market price risks and losses given default correlated to default rates can cause a significant understatement of value at risk figures.
While solving the conceptual problems of designing an integrated risk model has its own merits for scientific purposes, it is of limited use for practical applications as long as the computational problems remain unsolved. As the value at risk of a complex credit risk model cannot be determined analytically, simulation techniques that are both, sufficiently precise and not too time-consuming, are needed. Fourier transformations and importance sampling are two simulation procedures that proved to be successful in cutting down the computational burden in pu
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