Quantitative Risk Management (QRM) has become a field of research of considerable importance to numerous areas of application, including insurance, banking, energy, medicine, and reliability. Mainly motivated by examples from insurance and finance, the authors develop a theory for handling multivariate extremes. The approach borrows ideas from portfolio theory and aims at an intuitive approach in the spirit of the Peaks over Thresholds method. The point of view is geometric. It leads to a probabilistic description of what in QRM language may be referred to as a high risk scenario: the conditional behaviour of risk factors given that a large move on a linear combination (portfolio, say) has been observed. The theoretical models which describe such conditional extremal behaviour are characterized and their relation to the limit theory for coordinatewise maxima is explained. The first part is an elegant exposition of coordinatewise extreme value theory; the second half develops the more basic geometric theory. Besides a precise mathematical deduction of the main results, the text yields numerous discussions of a more applied nature. A twenty page preview introduces the key concepts; the extensive introduction provides links to financial mathematics and insurance theory. The book is based on a graduate course on point processes and extremes. It could form the basis for an advanced course on multivariate extreme value theory or a course on mathematical issues underlying risk. Students in statistics and finance with a mathematical, quantitative background are the prime audience. Actuaries and risk managers involved in data based risk analysis will find the models discussed in the book stimulating. The text contains many indications for further research. A publication of the European Mathematical Society (EMS). Distributed within the Americas by the American Mathematical Society.
Author(s): Guus Balkema
Series: Zurich Lectures in Advanced Mathematics
Edition: 1
Publisher: European Mathematical Society
Year: 2007
Language: English
Commentary: no
Pages: 391
Cover......Page 1
Zurich Lectures in Advanced Mathematics......Page 3
Title......Page 4
ISBN 978-3-03719-035-7......Page 5
Dedications......Page 6
Foreword......Page 8
Introduction......Page 16
A recipe......Page 28
Contents......Page 46
Notation......Page 51
Contents......Page 10
1 An intuitive approach......Page 56
2 Poisson point processes......Page 63
3 The distribution......Page 78
4 Convergence......Page 84
5 Converging sample clouds......Page 96
Maxima......Page 115
Exceedances......Page 116
7 Componentwise maxima......Page 125
8 High risk scenarios......Page 138
9 The Gauss-exponential domain, rotund sets......Page 150
10 The Gauss-exponential domain, unimodal distributions......Page 162
11 Flat functions and flat measures......Page 171
12 Heavy tails and bounded vectors......Page 185
13 The multivariate GPDs......Page 191
IV Thresholds......Page 197
Introduction......Page 198
Convergence of the vertical component......Page 200
15 Horizontal thresholds – examples......Page 226
16 Heavy tails and elliptic thresholds......Page 245
17 Heavy tails – examples......Page 278
18 Regular variation and excess measures......Page 310
Open problems......Page 363
19 The stochastic model......Page 364
20 The statistical analysis......Page 371
Bibliography......Page 376
Index......Page 384
Back Cover......Page 391