Quantitative risk management: concepts, techniques and tools
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Princeton [u.a.]
Princeton Univ. Press
2005
|
| Schriftenreihe: | Princeton series in finance
|
| Schlagworte: | |
| Online-Zugang: | Klappentext Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. [503] - 527 |
| Beschreibung: | XV, 538 S. graph. Darst. |
| ISBN: | 0691122555 9780691122557 |
Internformat
MARC
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| 100 | 1 | |a McNeil, Alexander J. |d 1967- |e Verfasser |0 (DE-588)131571338 |4 aut | |
| 245 | 1 | 0 | |a Quantitative risk management |b concepts, techniques and tools |c Alexander J. McNeil ; Rüdiger Frey ; Paul Embrechts |
| 264 | 1 | |a Princeton [u.a.] |b Princeton Univ. Press |c 2005 | |
| 300 | |a XV, 538 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 490 | 0 | |a Princeton series in finance | |
| 500 | |a Literaturverz. S. [503] - 527 | ||
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| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Risk management |x Mathematical models | |
| 650 | 4 | |a Finance |x Mathematical models | |
| 650 | 4 | |a Insurance |x Mathematical models | |
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Datensatz im Suchindex
| _version_ | 1812898667516919808 |
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| adam_text |
The implementation of sound quantitative
risk models is a vital concern for all finan¬
cial institutions, and this trend has acceler¬
ated in recent years with regulatory pro¬
cesses such as Basel II. This book provides
a comprehensive treatment of the theoreti¬
cal concepts and modelling techniques of
quantitative risk management and equips
readers—whether financial risk analysts,
actuaries, regulators, or students of quanti¬
tative finance—with practical tools to solve
real-world problems. The authors cover
methods for market, credit, and operation¬
al risk modelling; place standard industry
approaches on a more formal footing;
and describe recent developments that go
beyond, and address some of the main
deficiencies of, current practice.
The book's methodology draws on
diverse quantitative disciplines, from
mathematical finance through statistics
and econometrics to actuarial mathemat¬
ics. Main concepts discussed include
loss distributions, risk measures, and risk
aggregation and allocation principles. An
overarching theme is the need to satis¬
factorily address extreme outcomes and
the dependence of key risk drivers. The
techniques required derive from multivari-
ate statistical analysis, financial time series
modelling, copulas, and extreme value
theory. A more technical chapter address¬
es credit derivatives.
Contents
Preface
xiii
1
Risk in Perspective
1
1.1
Risk
1
1.1.1
Risk and Randomness
1
1.1.2
Financial Risk
2
1.1.3
Measurement and Management
3
1.2
A Brief History of Risk Management
5
1.2.1
From Babylon to Wall Street
5
1.2.2
The Road to Regulation
8
1.3
The New Regulatory Framework
10
1.3.1
Basel II
10
1.3.2
Solvency
2 13
1.4
Why Manage Financial Risk?
15
1.4.1
A Societal View
15
1.4.2
The Shareholder's View
16
1.4.3
Economic Capital
18
1.5
Quantitative Risk Management
19
1.5.1
The Nature of the Challenge
19
1.5.2
QRM for the Future
22
2
Basic Concepts in Risk Management
25
2.1
Risk Factors and Loss Distributions
25
2.1.1
General Definitions
25
2.1.2
Conditional and Unconditional Loss Distribution
28
2.1.3
Mapping of Risks: Some Examples
29
2.2
Risk Measurement
34
2.2.1
Approaches to Risk Measurement
34
2.2.2
Value-at-Risk
37
2.2.3
Further Comments on VaR
40
2.2.4
Other Risk Measures Based on Loss Distributions
43
2.3
Standard Methods for Market Risks
48
2.3.1
Variance-Covariance Method
48
2.3.2
Historical Simulation
50
2.3.3
Monte Carlo
52
2.3.4
Losses over Several Periods and Scaling
53
2.3.5
Backtesting
55
2.3.6
An Illustrative Example
55
3
Multivariate
Models 61
3.1 Basics
of
Multivariate
Modelling
61
3.1.1
Random Vectors and Their Distributions
62
3.1.2
Standard Estimators of Covariance and Correlation
64
3.1.3
The Multivariate Normal Distribution
66
3.1.4
Testing Normality and Multivariate Normality
68
3.2
Normal Mixture Distributions
73
3.2.1
Normal Variance Mixtures
73
3.2.2
Normal Mean-Variance Mixtures
77
3.2.3
Generalized Hyperbolic Distributions
78
3.2.4
Fitting Generalized Hyperbolic Distributions to Data
81
3.2.5
Empirical Examples
84
3.3
Spherical and Elliptical Distributions
89
3.3.1
Spherical Distributions
89
3.3.2
Elliptical Distributions
93
3.3.3
Properties of Elliptical Distributions
95
3.3.4
Estimating Dispersion and Correlation
96
3.3.5
Testing for Elliptical Symmetry
99
3.4
Dimension Reduction Techniques
103
3.4.1
Factor Models
103
3.4.2
Statistical Calibration Strategies
105
3.4.3
Regression Analysis of Factor Models
106
3.4.4
Principal Component Analysis
109
4
Financial Time Series
116
4.1
Empirical Analyses of Financial Time Series
117
4.1.1
Stylized Facts
117
4.1.2
Multivariate Stylized Facts
123
4.2
Fundamentals of Time Series Analysis
125
4.2.1
Basic Definitions
125
4.2.2
ARMA
Processes
128
4.2.3
Analysis in the Time Domain
132
4.2.4
Statistical Analysis of Time Series
134
4.2.5
Prediction
136
4.3
GARCH Models for Changing Volatility
139
4.3.1
ARCH Processes
139
4.3.2
GARCH Processes
145
4.3.3
Simple Extensions of the GARCH Model
148
4.3.4
Fitting GARCH Models to Data
150
4.4
Volatility Models and Risk Estimation
158
4.4.1
Volatility Forecasting
158
4.4.2
Conditional Risk Measurement
160
4.4.3
Backtesting
162
4.5
Fundamentals of Multivariate Time Series
164
4.5.1
Basic Definitions
164
4.5.2
Analysis in the Time Domain
166
4.5.3
Multivariate
ARMA
Processes
168
4.6
Multivariate GARCH Processes
170
4.6.1
General Structure of Models
170
4.6.2
Models for Conditional Correlation
172
4.6.3
Models for Conditional Covariance
175
4.6.4
Fitting Multivariate GARCH Models
178
4.6.5
Dimension Reduction in MGARCH
179
4.6.6
MGARCH and Conditional Risk Measurement
182
5
Copulas and Dependence
184
5.1
Copulas
184
5.1.1
Basic Properties
185
5.1.2
Examples of Copulas
189
5.1.3
Meta
Distributions
192
5.1.4
Simulation of Copulas and
Meta
Distributions
193
5.1.5
Further Properties of Copulas
195
5.1.6
Perfect Dependence
199
5.2
Dependence Measures
201
5.2.1
Linear Correlation
201
5.2.2
Rank Correlation
206
5.2.3
Coefficients of Tail Dependence
208
5.3
Normal Mixture Copulas
210
5.3.1
Tail Dependence
210
5.3.2
Rank Correlations
215
5.3.3
Skewed Normal Mixture Copulas
217
5.3.4
Grouped Normal Mixture Copulas
218
5.4
Archimedean Copulas
220
5.4.1
Divariate
Archimedean Copulas
220
5.4.2
Multivariate Archimedean Copulas
222
5.4.3
Non-exchangeable Archimedean Copulas
224
5.5
Fitting Copulas to Data
228
5.5.1
Method-of-Moments using Rank Correlation
229
5.5.2
Forming a Pseudo-Sample from the Copula
232
5.5.3
Maximum Likelihood Estimation
234
6
Aggregate Risk
238
6.1
Coherent Measures of Risk
238
6.1.1
The Axioms of Coherence
238
6.1.2
Value-at-Risk
241
6.1.3
Coherent Risk Measures Based on Loss Distributions
243
6.1.4
Coherent Risk Measures as Generalized Scenarios
244
6.1.5
Mean-VaR Portfolio Optimization
246
6.2
Bounds for Aggregate Risks
248
6.2.1
The General
Fréchet
Problem
248
6.2.2
The Case of VaR
250
6.3
Capital Allocation
256
6.3.1
The Allocation Problem
256
6.3.2
The
Euler
Principle and Examples
257
6.3.3
Economic Justification of the
Euler
Principle
261
7
Extreme Value Theory
264
7.1
Maxima
264
7.1.1
Generalized Extreme Value Distribution
265
7.1.2
Maximum Domains of Attraction
267
7.1.3
Maxima of Strictly Stationary Time Series
270
7.1.4
The Block Maxima Method
271
7.2
Threshold Exceedances
,. 275
7.2.1
Generalized Pareto Distribution
* 275
7.2.2
Modelling Excess Losses
278
7.2.3
Modelling Tails and Measures of Tail Risk
282
7.2.4
The Hill Method
, 286
7.2.5
Simulation Study of EVT Quantile Estimators
289
7.2.6
Conditional EVT for Financial Time Series
291
7.3
Tails of Specific Models
293
7.3.1
Domain of Attraction of
Fréchet
Distribution
293
7.3.2
Domain of Attraction of Gumbel Distribution
294
7.3.3
Mixture Models
295
7.4
Point Process Models
298
7.4.1
Threshold Exceedances for Strict White Noise
299
7.4.2
The POT Model
301
7.4.3
Self-Exciting Processes
306
7.4.4
A Self-Exciting POT Model
307
7.5
Multivariate Maxima
311
7.5.1
Multivariate Extreme Value Copulas
311
7.5.2
Copulas for Multivariate Minima
314
7.5.3
Copula Domains of Attraction
314
7.5.4
Modelling Multivariate Block Maxima
317
7.6
Multivariate Threshold Exceedances
319
7.6.1
Threshold Models Using EV Copulas
319
7.6.2
Fitting a Multivariate Tail Model
320
7.6.3
Threshold Copulas and Their Limits
322
Credit Risk Management
327
8.1
Introduction to Credit Risk Modelling
327
8.1.1
Credit Risk Models
327
8.1.2
The Nature of the Challenge
329
8.2
Structural Models of Default
331
8.2.1
The Merton Model
331
8.2.2
Pricing in Merton's Model
332
8.2.3
The KMV Model
336
8.2.4
Models Based on Credit Migration
338
8.2.5
Multivariate Firm-Value Models
342
8.3
Threshold Models
343
8.3.1
Notation for One-Period Portfolio Models
344
8.3.2
Threshold Models and Copulas
345
8.3.3
Industry Examples
347
8.3.4
Models Based on Alternative Copulas
348
8.3.5
Model Risk Issues
350
8.4
The Mixture Model Approach
352
8.4.1
One-Factor Bernoulli Mixture Models
353
8.4.2
CreditRisk-l-
356
8.4.3
Asymptotics for Large Portfolios
357
8.4.4
Threshold Models as Mixture Models
359
8.4.5
Model-Theoretic Aspects of Basel II
362
8.4.6
Model Risk Issues
364
8.5
Monte Carlo Methods
367
8.5.1
Basics of Importance Sampling
367
8.5.2
Application to Bernoulli-Mixture Models
370
8.6
Statistical Inference for Mixture Models
374
8.6.1
Motivation
374
8.6.2
Exchangeable Bernoulli-Mixture Models
375
8.6.3
Mixture Models as GLMMs
377
8.6.4
One-Factor Model with Rating Effect
381
9
Dynamic Credit Risk Models
385
9.1
Credit Derivatives
386
9.1.1
Overview
386
9.1.2
Single-Name Credit Derivatives
387
9.1.3
Portfolio Credit Derivatives
389
9.2
Mathematical Tools
392
9.2.1
Random Times and Hazard Rates
393
9.2.2
Modelling Additional Information
395
9.2.3
Doubly Stochastic Random Times
397
9.3
Financial and Actuarial Pricing of Credit Risk
400
9.3.1
Physical and Risk-Neutral Probability Measure
401
9.3.2
Risk-Neutral Pricing and Market Completeness
405
9.3.3
Martingale Modelling
408
9.3.4
The Actuarial Approach to Credit Risk Pricing
411
9.4
Pricing with Doubly Stochastic Default Times
414
9.4.1
Recovery Payments of Corporate Bonds
414
9.4.2
The Model
415
9.4.3
Pricing Formulas
416
9.4.4
Applications
418
9.5 Affine
Models
421
9.5.1
Basic Results
422
9.5.2
The
CIR
Square-Root Diffusion
423
9.5.3
Extensions
425
9.6
Conditionally Independent Defaults
429
9.6.1
Reduced-Form Models for Portfolio Credit Risk
429
9.6.2
Conditionally Independent Default Times
431
9.6.3
Examples and Applications
435
9.7
Copula Models
440
9.7.1
Definition and General Properties
440
9.7.2
Factor Copula Models
444
9.8
Default Contagion in Reduced-Form Models
448
9.8.1
Default Contagion and Default Dependence
448
9.8.2
Information-Based Default Contagion
453
9.8.3
Interacting Intensities
456
10
Operational Risk and Insurance Analytics
463
10.1
Operational Risk in Perspective
463
10.1.1
A New Risk Class
463
10.1.2
The Elementary Approaches
465
10.1.3
Advanced Measurement Approaches
466
10.1.4
Operational Loss Data
468
10.2
Elements of Insurance Analytics
471
10.2.1
The Case for Actuarial Methodology
471
10.2.2
The Total Loss Amount
472
10.2.3
Approximations and Panjer Recursion
476
10.2.4
Poisson
Mixtures
482
xii Contents
10.2.5
Tails of
Aggregate
Loss
Distributions
484
10.2.6
The Homogeneous
Poisson
Process
"' 484
10.2.7
Processes Related to the
Poisson
Process
487
494
494
494
494
495
496
496
496
496
496
497
497
498
498
498
499
499
499
500
501
501
502
503
Index
529
Appendix
A.
1
Miscellaneous Definitions and Results
A.I.I
Type of Distribution
A.
1.2
Generalized Inverses and Quantiles
A.1.3
Karamata's Theorem
A.2 Probability Distributions
A.2.1
Beta
A.2.2
Exponential
A.2.3
F
A.2.4
Gamma
A.2.5
Generalized Inverse Gaussian
A.2.6
Inverse Gamma
A.2.7
Negative Binomial
A.2.8
Pareto
A.2.9
Stable
A.3 Likelihood Inference
A.3.1
Maximum Likelihood Estimators
A.3.2
Asymptotic Results: Scalar Parameter
A.3.3
Asymptotic Results: Vector of Parameters
A.3.4
Wald Test
and Confidence Intervals
A.3.5
Likelihood Ratio Test and Confidence Intervals
A.3.6
Akaiké
Information Criterion
References |
| any_adam_object | 1 |
| author | McNeil, Alexander J. 1967- Frey, Rüdiger 1966- Embrechts, Paul 1953- |
| author_GND | (DE-588)131571338 (DE-588)132012367 (DE-588)115254447 |
| author_facet | McNeil, Alexander J. 1967- Frey, Rüdiger 1966- Embrechts, Paul 1953- |
| author_role | aut aut aut |
| author_sort | McNeil, Alexander J. 1967- |
| author_variant | a j m aj ajm r f rf p e pe |
| building | Verbundindex |
| bvnumber | BV019862960 |
| callnumber-first | H - Social Science |
| callnumber-label | HD61 |
| callnumber-raw | HD61.M395 2005 |
| callnumber-search | HD61.M395 2005 |
| callnumber-sort | HD 261 M395 42005 |
| callnumber-subject | HD - Industries, Land Use, Labor |
| classification_rvk | QH 237 QK 300 QP 300 QP 710 QP 890 SK 980 |
| classification_tum | WIR 190f MAT 902f WIR 160f MAT 620f |
| ctrlnum | (OCoLC)605937202 (DE-599)BVBBV019862960 |
| dewey-full | 658.15/5/015122 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.15/5/0151 22 |
| dewey-search | 658.15/5/0151 22 |
| dewey-sort | 3658.15 15 3151 222 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV019862960 |
| illustrated | Illustrated |
| indexdate | 2024-10-14T14:08:16Z |
| institution | BVB |
| isbn | 0691122555 9780691122557 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-013187437 |
| oclc_num | 605937202 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM DE-N2 DE-19 DE-BY-UBM DE-1047 DE-29T DE-898 DE-BY-UBR DE-384 DE-1049 DE-706 DE-20 DE-739 DE-945 DE-521 DE-83 DE-M347 DE-11 DE-355 DE-BY-UBR DE-523 DE-188 DE-634 DE-2070s DE-473 DE-BY-UBG |
| owner_facet | DE-91G DE-BY-TUM DE-N2 DE-19 DE-BY-UBM DE-1047 DE-29T DE-898 DE-BY-UBR DE-384 DE-1049 DE-706 DE-20 DE-739 DE-945 DE-521 DE-83 DE-M347 DE-11 DE-355 DE-BY-UBR DE-523 DE-188 DE-634 DE-2070s DE-473 DE-BY-UBG |
| physical | XV, 538 S. graph. Darst. |
| publishDate | 2005 |
| publishDateSearch | 2005 |
| publishDateSort | 2005 |
| publisher | Princeton Univ. Press |
| record_format | marc |
| series2 | Princeton series in finance |
| spelling | McNeil, Alexander J. 1967- Verfasser (DE-588)131571338 aut Quantitative risk management concepts, techniques and tools Alexander J. McNeil ; Rüdiger Frey ; Paul Embrechts Princeton [u.a.] Princeton Univ. Press 2005 XV, 538 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Princeton series in finance Literaturverz. S. [503] - 527 Rizični management - Kvantitativne metode - Priročniki Tveganje, odpravljanje - Matematični modeli - Priročniki ssg Mathematisches Modell Risk management Mathematical models Finance Mathematical models Insurance Mathematical models Mathematical statistics Finanzmanagement (DE-588)4139075-1 gnd rswk-swf Mathematische Methode (DE-588)4155620-3 gnd rswk-swf Financial Engineering (DE-588)4208404-0 gnd rswk-swf Kreditrisiko (DE-588)4114309-7 gnd rswk-swf Finanzmathematik (DE-588)4017195-4 gnd rswk-swf Risikomanagement (DE-588)4121590-4 gnd rswk-swf Risikomanagement (DE-588)4121590-4 s Financial Engineering (DE-588)4208404-0 s Mathematische Methode (DE-588)4155620-3 s DE-604 Finanzmanagement (DE-588)4139075-1 s DE-188 Kreditrisiko (DE-588)4114309-7 s Finanzmathematik (DE-588)4017195-4 s Frey, Rüdiger 1966- Verfasser (DE-588)132012367 aut Embrechts, Paul 1953- Verfasser (DE-588)115254447 aut Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013187437&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013187437&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | McNeil, Alexander J. 1967- Frey, Rüdiger 1966- Embrechts, Paul 1953- Quantitative risk management concepts, techniques and tools Rizični management - Kvantitativne metode - Priročniki Tveganje, odpravljanje - Matematični modeli - Priročniki ssg Mathematisches Modell Risk management Mathematical models Finance Mathematical models Insurance Mathematical models Mathematical statistics Finanzmanagement (DE-588)4139075-1 gnd Mathematische Methode (DE-588)4155620-3 gnd Financial Engineering (DE-588)4208404-0 gnd Kreditrisiko (DE-588)4114309-7 gnd Finanzmathematik (DE-588)4017195-4 gnd Risikomanagement (DE-588)4121590-4 gnd |
| subject_GND | (DE-588)4139075-1 (DE-588)4155620-3 (DE-588)4208404-0 (DE-588)4114309-7 (DE-588)4017195-4 (DE-588)4121590-4 |
| title | Quantitative risk management concepts, techniques and tools |
| title_auth | Quantitative risk management concepts, techniques and tools |
| title_exact_search | Quantitative risk management concepts, techniques and tools |
| title_full | Quantitative risk management concepts, techniques and tools Alexander J. McNeil ; Rüdiger Frey ; Paul Embrechts |
| title_fullStr | Quantitative risk management concepts, techniques and tools Alexander J. McNeil ; Rüdiger Frey ; Paul Embrechts |
| title_full_unstemmed | Quantitative risk management concepts, techniques and tools Alexander J. McNeil ; Rüdiger Frey ; Paul Embrechts |
| title_short | Quantitative risk management |
| title_sort | quantitative risk management concepts techniques and tools |
| title_sub | concepts, techniques and tools |
| topic | Rizični management - Kvantitativne metode - Priročniki Tveganje, odpravljanje - Matematični modeli - Priročniki ssg Mathematisches Modell Risk management Mathematical models Finance Mathematical models Insurance Mathematical models Mathematical statistics Finanzmanagement (DE-588)4139075-1 gnd Mathematische Methode (DE-588)4155620-3 gnd Financial Engineering (DE-588)4208404-0 gnd Kreditrisiko (DE-588)4114309-7 gnd Finanzmathematik (DE-588)4017195-4 gnd Risikomanagement (DE-588)4121590-4 gnd |
| topic_facet | Rizični management - Kvantitativne metode - Priročniki Tveganje, odpravljanje - Matematični modeli - Priročniki Mathematisches Modell Risk management Mathematical models Finance Mathematical models Insurance Mathematical models Mathematical statistics Finanzmanagement Mathematische Methode Financial Engineering Kreditrisiko Finanzmathematik Risikomanagement |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013187437&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013187437&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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