E-Book, Englisch, Band 361, 188 Seiten, eBook
Risk Measurement and Computational Aspects
E-Book, Englisch, Band 361, 188 Seiten, eBook
Reihe: neue betriebswirtschaftliche forschung (nbf)
ISBN: 978-3-8349-9689-3
Verlag: Betriebswirtschaftlicher Verlag Gabler
Format: PDF
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)
PD Dr. Peter Grundke habilitierte am Seminar für Allgemeine Betriebswirtschaftslehre und Bankbetriebslehre der Universität zu Köln.
Er leitet zur Zeit das Fachgebiet Finance an der Universität Osnabrück.
Zielgruppe
Research
Weitere Infos & Material
1;Preface;6
2;Acknowledgments;8
3;Contents;9
4;List of Tables;12
5;List of Figures;14
6;List of Acronyms;15
7;List of Symbols;16
8;Chapter 1 Introduction;22
8.1;Motivation;22
8.2;Structure;25
9;Chapter 2 The Integrated Market and Credit Portfolio Model;27
9.1;General Approach;27
9.2;Industry Standards as Special Cases;29
9.3;Example of an Integrated Market and Credit Portfolio Model;31
10;Chapter 3 Effects of Integrating Market Risk into Credit Portfolio Models;39
10.1;Introduction;39
10.2;Review of the Literature;40
10.3;Modifications of the Base Case Model;45
10.4;Numerical Results;58
10.5;Conclusions;80
11;Chapter 4 On the Applicability of Fourier-Based Methods to Integrated Market and Credit Portfolio Models;82
11.1;Introduction;82
11.2;Review of the Literature;85
11.3;General Computation Approach;87
11.4;Numerical Results;90
11.5;Discussion;104
11.6;Importance Sampling Techniques for the Fourier-Based Approach;109
11.7;Conclusions;116
12;Chapter 5 Importance Sampling for Integrated Market and Credit Portfolio Models;118
12.1;Introduction;118
12.2;Review of the Literature;120
12.3;Importance Sampling Techniques for the General Approach;123
12.4;Numerical Results;154
12.5;Conclusions;173
13;Chapter 6 Conclusions;175
14;Appendices;178
15;Bibliography;183
The Integrated Market and Credit Portfolio Model.- Effects of Integrating Market Risk into Credit Portfolio Models.- On the Applicability of Fourier-Based Methods to Integrated Market and Credit Portfolio Models.- Importance Sampling for Integrated Market and Credit Portfolio Models.- Conclusions.
Chapter 5 Importance Sampling for Integrated Market and Credit Portfolio Models (p. 99-100)
5.1 Introduction
As already mentioned in chapter 4, beside Fourier-based approaches, another efficiency enhancing computational approach developed for standard credit portfolio models is based on Monte Carlo simulations combined with variance reduction techniques. Most common is the application of importance sampling (IS) techniques.
In this chapter, it is shown in detail how a two-step-IS technique presented by Glasserman and Li (2005) for a pure default mode model can be applied to the general integrated market and credit portfolio model of section 2.1, and what differences exist. Glasserman and Li (2005) employ IS for the probability distribution of the systematic risk factors as well as for the conditional default probabilities to make higher losses more probable under the IS distribution.
In contrast, almost all other papers which deal with IS for credit portfolio models only apply one-step-IS techniques.56 That is why the technique suggested by Glasserman and Li (2005) is expected to be especially effective and why it is employed in this chapter. Furthermore, it is discussed how an IS approach originally developed by Glasserman, Heidelberger and Shahabuddin (2000) for pure market risk portfolio models can be combined with the two-step-IS approach to build up a potentially even more effective three-step-IS technique.
Glasserman, Heidelberger and Shahabuddin (2000) use a delta-gamma approximation of the loss variable of a portfolio of default risk-free instruments for selecting an effective IS distribution for the normally distributed vector of market risk factors. As we deal with integrated market and credit portfolio models, the idea to combine methods originally developed for pure market risk portfolio models with those originally developed for pure (default mode) credit portfolio models might suggest itself. However, up to now this has not been tried.
Summarizing, the main questions answered in this chapter are:
1) Are IS techniques originally developed for pure default mode credit portfolio models also applicable to integrated market and credit portfolio models?
2) How effective are they for these extended models?
3) Is it possible to increase the effectiveness by combining IS techniques originally developed for pure default mode credit portfolio models with those originally developed for pure market risk portfolio models ?
Chapter 5 is structured as follows. In section 5.2, related literature is reviewed. In section 5.3, after a short introduction into the IS technique, two- and three-step-IS techniques when applied to the general integrated market and credit portfolio model are presented. The particularities resulting from the integrated market risk are discussed. The effectiveness of the presented IS techniques is tested by means of numerical experiments in section 5.4. Finally, the conclusions and main results are summarized in section 5.5.
