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Princeton Series in Finance
Series Editors
Darrell Duffie Stephen Schaefer
Stanford University London Business School
Finance as a discipline has been growing rapidly. The numbers of researchers in
academy and industry, of students, of methods and models have all proliferated in
the past decade or so. This growth and diversity manifests itself in the emerging
cross-disciplinary as well as cross-national mix of scholarship now driving the field
of finance forward. The intellectual roots of modern finance, as well as the branches,
will be represented in the Princeton Series in Finance.
详细介绍
Why have we written this book? In recent decades the field of financial risk management
has undergone explosive development. This book is devoted specifically to
quantitative modelling issues arising in this field. As a result of our own discussions
and joint projects with industry professionals and regulators over a number of years,
we felt there was a need for a textbook treatment of quantitative risk management
(QRM) at a technical yet accessible level, aimed at both industry participants and
students seeking an entrance to the area.
We have tried to bring together a body of methodology that we consider to be core
material for any course on the subject. This material and its mode of presentation
represent the blending of our own views, which come from the perspectives of
financial mathematics, insurance mathematics and statistics. We feel that a book
combining these viewpoints fills a gap in the existing literature and partly anticipates
the future need for quantitative risk managers in banks, insurance companies and
beyond with broad, interdisciplinary skills.
Who was this book written for? This book is primarily a textbook for courses
on QRM aimed at advanced undergraduate or graduate students and professionals
from the financial industry. A knowledge of probability and statistics at least at the
level of a first university course in a quantitative discipline and familiarity with
undergraduate calculus and linear algebra are fundamental prerequisites. Though
not absolutely necessary, some prior exposure to finance, economics or insurance
will be beneficial for a better understanding of some sections.
The book has a secondary function as a reference text for risk professionals interested
in a clear and concise treatment of concepts and techniques used in practice.
As such, we hope it will facilitate communication between regulators, end-users and
academics.
Athird audience for the book is the growing community of researchersworking in
the area. Most chapters take the reader to the frontier of current, practically relevant
research and contain extensive, annotated references that guide the reader through
the burgeoning literature.
Ways to use this book. Based on our experience of teaching university courses
on QRM at ETH Zurich, the Universities of Zurich and Leipzig and the London
School of Economics, a two-semester course of 3–4 hours a week can be based on
material in Chapters 2–8 and parts of Chapter 10; Chapter 1 is typically given as
background reading material. Chapter 9 is a more technically demanding chapter
that has been included because of the current interest in quantitative methods for
pricing and hedging credit derivatives; it is primarily intended for more advanced,
specialized courses on credit risk (see below).
A course on market risk can be based on a fairly complete treatment of
Chapters 2–4, with excursions into material in Chapters 5, 6 and 7 (normal mixture
copulas, coherent risk measures, extreme value methods for threshold exceedances)
as time permits.
Acourse on credit risk can be based on Chapters 8 and 9 but requires a preliminary
treatment of some topics in earlier chapters. Sections 2.1 and 2.2 give the necessary
grounding in basic concepts; Sections 3.1, 3.2, 3.4, 5.1 and 5.4 are necessary for
an understanding of multivariate models of portfolio credit risk; and Sections 6.1
and 6.3 are required to understand how capital is allocated to credit risks.
A short course or seminar on operational risk could be based on Chapter 10,
but would also benefit from some supplementary material from other chapters;
Sections 2.1 and 2.2 and Chapters 6 and 7 are particularly relevant.
It is also possible to devise more specialized courses, such as a course on riskmeasurement
and aggregation concepts based on Chapters 2, 5 and 6, or a course on
risk-management techniques for financial econometricians based on Chapters 2–4
and 7. Material from various chapters could be used as interesting examples to
enliven statistics courses on subjects like multivariate analysis, time series analysis
and generalized linear modelling.
What we have not covered. We have not been able to address all topics that a reader
might expect to find under the heading of QRM. Perhaps the most obvious omission
is the lack of a section on the risk management of derivatives by hedging.We felt here
that the relevant techniques, and the financial mathematics required to understand
them, are already well covered in a number of excellent textbooks. Other omissions
include RAROC (risk-adjusted return on capital) and performance-measurement
issues. Besides these larger areas, many smaller issues have been neglected for
reasons of space, but are mentioned with suggestions for further reading in the
“Notes and Comments” sections, which should be considered as integral parts of
the text.
Acknowledgements. The origins of this book date back to 1996, when A.M. and
R.F. began postdoctoral studies in the group of P.E. at the Federal Institute of Technology
(ETH) in Zurich. All three authors are grateful to ETH for providing the
environment in which the project flourished. A.M. and R.F. thank Swiss Re and
UBS, respectively, for providing the financial support for their postdoctoral positions.
R.F. has subsequently held positions at the Swiss Banking Institute of the
University of Zurich and at the University of Leipzig and is grateful to both institutions
for their support.
The Forschungsinstitut f¨ur Mathematik (FIM) of the ETH Zurich provided financial
support at various stages of the project. At a crucial juncture in early 2004
the Mathematisches Foschungsinstitut Oberwolfach was the venue for a memorable
week of progress. P.E. recalls fondly his time as Centennial Professor of Finance at
the London School of Economics; numerous discussions with colleagues from the
Department ofAccounting and Finance helped in shaping his viewof the importance
of QRM.We also acknowledge the invaluable contribution of RiskLab Zurich to theenterprise: the agenda for the book was strongly influenced by joint projects and
discussions with the RiskLab sponsors UBS, Credit Suisse and Swiss Re.We have
also benefited greatly from the NCCR FINRISK research program in Switzerland,
which funded doctoral and postdoctoral research on topics in the book.
We are indebted to numerous proof-readers who have commented on various
parts of the manuscript, and to colleagues in Zurich, Leipzig and beyond who
have helped us in our understanding of QRM and the mathematics underlying it.
These include StefanAltner, PhilippeArtzner, Jochen Backhaus, Guus Balkema, Uta
Beckmann, Reto Baumgartner,Wolfgang Breymann, Reto Bucher, Hans B¨uhlmann,
Peter B¨uhlmann, Val´erie Chavez-Demoulin, Dominik Colangelo, Freddy Delbaen,
Rosario Dell’Aquila, Stefan Denzler, Alexandra Dias, Stefano Demarta, Damir
Filipovic, Gabriel Frahm, Hansj¨org Furrer, Rajna Gibson, Kay Giesecke, Enrico
De Giorgi, Bernhard Hodler, Andrea H¨oing, Christoph Hummel, Alessandro Juri,
Roger Kaufmann, Philipp Keller, Hans Rudolf K¨unsch, Filip Lindskog, Hans-Jakob
L¨uthi, Natalia Markovich, Benoˆıt Metayer, Johanna Neˇslehov´a, Monika Popp,
Giovanni Puccetti, Hanspeter Schmidli, Sylvia Schmidt, Thorsten Schmidt, Uwe
Schmock, Philipp Sch¨onbucher, Martin Schweizer, Torsten Steiger, Daniel Straumann,
Dirk Tasche, Eduardo Vilela, Marcel Visser and Jonathan Wendin. For her
help in preparing the manuscript we thank Gabriele Baltes.
We thank Richard Baggaley and the team at Princeton University Press for all
their help in the production of this book. We are also grateful to our anonymous
referees who provided us with exemplary feedback, which has shaped this book for
the better. Special thanks go to Sam Clark at T&T Productions Ltd, who took our
uneven LATEX code and turned it into a more polished book with remarkable speed
and efficiency.
To our wives, Janine, Catharina and Gerda, and our families our sincerest debt of
gratitude is due. Though driven to distraction no doubt by our long contemplation
of risk, without obvious reward, their support was constant.
Further resources. Readers are encouraged to visit the book’s homepage at
www.pupress.princeton.edu/titles/8056.html
to find supplementary resources for this book. Our intention is to make available the
computer code (mostly S-PLUS) used to generate the examples in this book, and to
list errata.
Special abbreviations. Anumber of abbreviations for common terms in probability
are used throughout the book; these include “rv” for random variable, “df” for
distribution function, “iid” for independent and identically distributed and “se” for
standard error.
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