Operational risk: modeling analytics
Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical mode...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley Interscience
2006
|
| Schriftenreihe: | Wiley series in probability and statistics
|
| Schlagworte: | |
| Online-Zugang: | Publisher description Inhaltsverzeichnis Klappentext |
| Zusammenfassung: | Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors. Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts. Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science. |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XV, 431 S. graph. Darst. |
| ISBN: | 0471760897 9780471760894 |
Internformat
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| 100 | 1 | |a Panjer, Harry H. |d 1946- |e Verfasser |0 (DE-588)1044735732 |4 aut | |
| 245 | 1 | 0 | |a Operational risk |b modeling analytics |c Harry H. Panjer |
| 246 | 1 | 3 | |a Operational risks |
| 264 | 1 | |a Hoboken, NJ |b Wiley Interscience |c 2006 | |
| 300 | |a XV, 431 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Wiley series in probability and statistics | |
| 500 | |a Includes bibliographical references and index | ||
| 520 | 3 | |a Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors. Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts. Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science. | |
| 650 | 4 | |a Gestion du risque | |
| 650 | 4 | |a Risk management | |
| 650 | 0 | 7 | |a Risikomanagement |0 (DE-588)4121590-4 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Risikomanagement |0 (DE-588)4121590-4 |D s |
| 689 | 0 | |5 DE-604 | |
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| 856 | 4 | 2 | |m Digitalisierung UB Passau |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014961473&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-014961473 | ||
Datensatz im Suchindex
| _version_ | 1804135603798802432 |
|---|---|
| adam_text | Contents
Preface
xiii
Acknowledgments
xv
Part I Introduction to operational risk modeling
1
Operational risk
3
1.1
Introduction
3
1.1.1
Basel II
-
General
6
1.1.2
Basel II
-
Operational risk
8
1.2
Operational risk in insurance
11
1.3
The analysis of operational risk
12
1.Ą
The model-based approach
H
1.4-1
The modeling process
15
1.5
Organization of this book
16
2
Basic probability concepts
19
2.1
Introduction
19
2.2
Distribution functions and related concepts
20
2.3
Moments
30
2.
Ą
Quantités
of
a distribution
ƒ 38
2.5
Generating functions
38
2.6
Exercises
Ąl
3
Measures of risk
Ą5
3.1
Introduction
4-5
3.2
Risk measures
46
3.3
Tail-Value- at-Risk
50
Probabilistic tools for operational risk modeling
Models for the size of losses: Continuous distributions
57
4-І
Introduction
57
4-2
An inventory of continuous distributions
58
4.2.I One-parameter distributions
58
4-2.2
Two-parameter distributions
59
4.2.З
Three-parameter distributions
64
4-2-4
Four-parameter distributions
67
4-2.5
Distributions with finite support
68
4-3
Selected distributions and their relationships
68
4.3.1
Introduction
68
4.3.2
Two important parametric families
69
4-4
Limiting distributions
70
4-5
The role of parameters
73
4.5.I Parametric and scale distributions
74
4-5.2
Finite mixture distributions
75
4.5.3
D ata-
dependent distributions
78
4-6
Tails of distributions
80
4.6.I Classification based on moments
80
4-6.2
Classification based on tail behavior
81
4.6.З
Classification based on hazard rate
function
82
4.7
Creating new distributions
84
4-7.1
Introduction
84
4-7.2
Multiplication by a constant
84
4.7.3
Transformation by raising to a power
85
4.7.4
Transformation by exponentiation
87
4-7.5
Continuous mixture of distributions
88
4-7.6
Frailty models
90
4-7.7
Splicing pieces of distributions
92
4.8
TVaR for continuous distributions
93
4-8.1
Continuous elliptical distributions
94
4-8.2
Continuous exponential dispersion
distributions
97
4.9
Exercises
102
Models
for the number of losses: Counting distributions
107
5.1
Introduction
107
5.2
The
Poisson
distribution
108
5.3
The negative binomial distribution
110
5.4
The binomial distribution
1Ц
5.5
The
(a,
6,0)
class
114
5.6
The (a,
6,1)
class
118
5.7
Compound frequency models
122
5.8
Recursive calculation of compound probabilities
126
5.9
An inventory of discrete distributions
130
5.9.1
The (a,
6,0)
class
130
5.9.2
The (a,
6,1)
class
132
5.9.3
The zero-truncated subclass
132
5.9-4
The zero-modified subclass
134
5.9.5
The compound class
135
5.10
A hierarchy of discrete distributions
136
5.11
Further properties of the compound
Poisson
class
137
5.12
Mixed frequency models
Ц2
5.13
Poisson
mixtures
144
5.Ц
Effect of exposure on loss counts
149
5.15
TVaR for discrete distributions
150
5.15.1
TVaR for discrete exponential dispersion
distributions
151
5.16
Exercises
156
Aggregate loss models
161
6.1
Introduction
161
6.2
Model choices
162
6.3
The compound model for aggregate losses
163
6.4
Some analytic results
168
6.5
Evaluation of the aggregate loss distribution
171
f
6.6
The recursive method
< 174
6.6.1
Compound frequency models
175
6.6.2
Underflow/overflow problems
178
6.6.3
Numerical stability
179
6.6.4
Continuous severity
179
6.6.5
Constructing arithmetic distributions
180
6.7
Fast Fourier transform methods
183
6.8
Using approximating severity distributions
187
6.8.1
Arithmetic distributions
187
6.9
Comparison of methods
190
6.10
TVaR for aggregate losses
191
6.10.1
TVaR for discrete aggregate loss
distributions
191
6.10.2
TVaR for some frequency distributions
192
6.10.3
TVaR for some severity distributions
19Ą
6.10.4 Summary
198
6.11
Exercises
198
Extreme value theory: The study of jumbo losses
205
7.1
Introduction
205
7.2
Extreme value distributions
207
7.3
Distribution of the maximum
208
7.3.1
From a fixed number of losses
208
7.3.2
From a random number of losses
210
7.4
Stability of the maximum of the extreme value
distribution
213
7.5
The Fisher-Tippett theorem
21Ą
7.6
Maximum domain of attraction
217
7.7
Generalized Pareto distributions
219
7.8
The frequency of exceedences
221
7.8.1
From a fixed number of losses
221
7.8.2
From a random number of losses
222
7.9
Stability of excesses of the generalized Pareto
226
7.10
Mean excess function
227
7.11
Limiting distributions of excesses
228
7.12
TVaR for extreme value distributions
229
7.13
Further reading
230
7.14 Exercises
230
8
Multivariate
models
233
8.1
Introduction
233
8.2
Sklár s
theorem and copulas
23
Ą
8.3
Measures of dependency
231
84
Tail dependence
239
8.5
Archimedean copulas
2Ą0
8.6
Elliptical copulas
253
8.7
Extreme value copulas
257
8.8 .
Archimax copulas
262
8.9
Exercises
263
Part III Statistical methods for calibrating models of operational
risk
9
Review of mathematical statistics
267
9.1
Introduction
267
9.2
Point estimation
268
9.2.1
Introduction
268
9.2.2
Measures of quality of estimators
269
9.3
Interval estimation
275
9.4
Tests of hypotheses
277
9.5
Exercises
280
10
Parameter estimation
283
10.1
Introduction
283
10.2
Method of moments and percentile matching
286
10.3
Maximum likelihood estimation
289
10.3.1
Introduction
289
10.3.2
Complete, individual data
291
10.3.3
Complete, grouped data
293
10.3.4
Truncated or censored data
293
10.4 Variance and interval estimation
297
10.5
Bayesian estimation
ЗО4
10.5.1
Definitions and
Bayes
theorem
ЗО4
10.5.2
Inference and prediction
307
10.5.3
Computational issues
315
10.6
Exercises
316
11
Estimation
for discrete distributions
ƒ 329
11.1
Introduction
* 329
11.2
Poisson
distribution
329
11.3
Negative binomial distribution
333
11.4
Binomial distribution
336
11.5
The (a,
6,1)
class
338
11.6
Compound models
3Ą3
11.7
Effect of exposure on maximum likelihood
estimation
344
11.8
Exercises
3Ą5
12
Model selection
3Ą9
12.1
Introduction
3Ą9
12.2
Representations of the data and model
350
12.3
Graphical comparison of the density and
distribution functions
351
124
Hypothesis tests
356
12.4-1
Kolmogorov-Smirnov test
357
12.4-2
Anderson-Darling test
360
12.4-3
Chi-square goodness-of-fit test
360
12-4-4
Likelihood ratio test
365
12.5
Selecting a model
367
12.5.1
Introduction
367
12.5.2
Judgment-based approaches
368
12.5.3
Score-based approaches
368
12.6
Exercises
375
13
Fitting extreme value models
383
13.1
Introduction
383
13.2
Parameter estimation
384
13.2.1
ML estimation from the extreme value
distribution
384
13.2.2
ML estimation from the generalized
Pareto distribution
387
13.2.3
Estimating the Pareto shape parameter
389
13.2-4
Estimating extreme probabilities
391
13.3
Model selection
392
13.3.1
Mean excess plots
392
1Ą
Fitting
copula
models
395
1Ą.1
Introduction
395
1Ą.2
Maximum likelihood estimation
396
1Ą.3
S emiparametric
estimation of the copula
398
144
The role of thresholds
399
14-5
Goodness-of-fit testing 4OI
I4.6 An example
402
Appendix A Gamma and related functions
407
Appendix
В
Discretization of the severity distribution
B.I The method of rounding
B.2 Mean preserving
B.3 Undiscretization of
a dis
cretized distribution
413
Appendix
С
Nelder-
Mead simplex method
415
References
4
Π
Index
426
Oßerational Rist
Modeling Analytics is organized around the principle that the analysis of operational risk consists, in
part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide
risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of
operational risk in both the banking and insurance sectors.
Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically
to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of opera¬
tional risk. Exercises are included in chapters involving numerical computations for students practice and reinforcement
of concepts.
Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business
management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using
the tools of probability, statistics, and actuarial science.
In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features:
Ample exercises to further elucidate the concepts in the text
Definitive coverage of distribution functions and related concepts
Models for the size of losses
Models for frequency of loss
Aggregate loss modeling
Extreme value modeling
Dependency modeling using copulas
Statistical methods in model selection and calibration
Assuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for
beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also
useful as a reference for practitioners in both enterprise risk management and risk and operational management.
|
| adam_txt |
Contents
Preface
xiii
Acknowledgments
xv
Part I Introduction to operational risk modeling
1
Operational risk
3
1.1
Introduction
3
1.1.1
Basel II
-
General
6
1.1.2
Basel II
-
Operational risk
8
1.2
Operational risk in insurance
11
1.3
The analysis of operational risk
12
1.Ą
The model-based approach
H
1.4-1
The modeling process
15
1.5
Organization of this book
16
2
Basic probability concepts
19
2.1
Introduction
19
2.2
Distribution functions and related concepts
20
2.3
Moments
30
2.
Ą
Quantités
of
a distribution
ƒ 38
2.5
Generating functions
38
2.6
Exercises
Ąl
3
Measures of risk
Ą5
3.1
Introduction
4-5
3.2
Risk measures
46
3.3
Tail-Value- at-Risk
50
Probabilistic tools for operational risk modeling
Models for the size of losses: Continuous distributions
57
4-І
Introduction
57
4-2
An inventory of continuous distributions
58
4.2.I One-parameter distributions
58
4-2.2
Two-parameter distributions
59
4.2.З
Three-parameter distributions
64
4-2-4
Four-parameter distributions
67
4-2.5
Distributions with finite support
68
4-3
Selected distributions and their relationships
68
4.3.1
Introduction
68
4.3.2
Two important parametric families
69
4-4
Limiting distributions
70
4-5
The role of parameters
73
4.5.I Parametric and scale distributions
74
4-5.2
Finite mixture distributions
75
4.5.3
D ata-
dependent distributions
78
4-6
Tails of distributions
80
4.6.I Classification based on moments
80
4-6.2
Classification based on tail behavior
81
4.6.З
Classification based on hazard rate
function
82
4.7
Creating new distributions
84
4-7.1
Introduction
84
4-7.2
Multiplication by a constant
84
4.7.3
Transformation by raising to a power
85
4.7.4
Transformation by exponentiation
87
4-7.5
Continuous mixture of distributions
88
4-7.6
Frailty models
90
4-7.7
Splicing pieces of distributions
92
4.8
TVaR for continuous distributions
93
4-8.1
Continuous elliptical distributions
94
4-8.2
Continuous exponential dispersion
distributions
97
4.9
Exercises
102
Models
for the number of losses: Counting distributions
107
5.1
Introduction
107
5.2
The
Poisson
distribution
108
5.3
The negative binomial distribution
110
5.4
The binomial distribution
1Ц
5.5
The
(a,
6,0)
class
114
5.6
The (a,
6,1)
class
118
5.7
Compound frequency models
122
5.8
Recursive calculation of compound probabilities
126
5.9
An inventory of discrete distributions
130
5.9.1
The (a,
6,0)
class
130
5.9.2
The (a,
6,1)
class
132
5.9.3
The zero-truncated subclass
132
5.9-4
The zero-modified subclass
134
5.9.5
The compound class
135
5.10
A hierarchy of discrete distributions
136
5.11
Further properties of the compound
Poisson
class
137
5.12
Mixed frequency models
Ц2
5.13
Poisson
mixtures
144
5.Ц
Effect of exposure on loss counts
149
5.15
TVaR for discrete distributions
150
5.15.1
TVaR for discrete exponential dispersion
distributions
151
5.16
Exercises
156
Aggregate loss models
161
6.1
Introduction
161
6.2
Model choices
162
6.3
The compound model for aggregate losses
163
6.4
Some analytic results
168
6.5
Evaluation of the aggregate loss distribution
171
f
6.6
The recursive method
< 174
6.6.1
Compound frequency models
175
6.6.2
Underflow/overflow problems
178
6.6.3
Numerical stability
179
6.6.4
Continuous severity
179
6.6.5
Constructing arithmetic distributions
180
6.7
Fast Fourier transform methods
183
6.8
Using approximating severity distributions
187
6.8.1
Arithmetic distributions
187
6.9
Comparison of methods
190
6.10
TVaR for aggregate losses
191
6.10.1
TVaR for discrete aggregate loss
distributions
191
6.10.2
TVaR for some frequency distributions
192
6.10.3
TVaR for some severity distributions
19Ą
6.10.4 Summary
198
6.11
Exercises
198
Extreme value theory: The study of jumbo losses
205
7.1
Introduction
205
7.2
Extreme value distributions
207
7.3
Distribution of the maximum
208
7.3.1
From a fixed number of losses
208
7.3.2
From a random number of losses
210
7.4
Stability of the maximum of the extreme value
distribution
213
7.5
The Fisher-Tippett theorem
21Ą
7.6
Maximum domain of attraction
217
7.7
Generalized Pareto distributions
219
7.8
The frequency of exceedences
221
7.8.1
From a fixed number of losses
221
7.8.2
From a random number of losses
222
7.9
Stability of excesses of the generalized Pareto
226
7.10
Mean excess function
227
7.11
Limiting distributions of excesses
228
7.12
TVaR for extreme value distributions
229
7.13
Further reading
230
7.14 Exercises
230
8
Multivariate
models
233
8.1
Introduction
233
8.2
Sklár's
theorem and copulas
23
Ą
8.3
Measures of dependency
231
84
Tail dependence
239
8.5
Archimedean copulas
2Ą0
8.6
Elliptical copulas
253
8.7
Extreme value copulas
257
8.8 .
Archimax copulas
262
8.9
Exercises
263
Part III Statistical methods for calibrating models of operational
risk
9
Review of mathematical statistics
267
9.1
Introduction
267
9.2
Point estimation
268
9.2.1
Introduction
268
9.2.2
Measures of quality of estimators
269
9.3
Interval estimation
275
9.4
Tests of hypotheses
277
9.5
Exercises
280
10
Parameter estimation
283
10.1
Introduction
283
10.2
Method of moments and percentile matching
286
10.3
Maximum likelihood estimation
289
10.3.1
Introduction
289
10.3.2
Complete, individual data
291
10.3.3
Complete, grouped data
293
10.3.4
Truncated or censored data
293
10.4 Variance and interval estimation
297
10.5
Bayesian estimation
ЗО4
10.5.1
Definitions and
Bayes'
theorem
ЗО4
10.5.2
Inference and prediction
307
10.5.3
Computational issues
315
10.6
Exercises
316
11
Estimation
for discrete distributions
ƒ 329
11.1
Introduction
* 329
11.2
Poisson
distribution
329
11.3
Negative binomial distribution
333
11.4
Binomial distribution
336
11.5
The (a,
6,1)
class
338
11.6
Compound models
3Ą3
11.7
Effect of exposure on maximum likelihood
estimation
344
11.8
Exercises
3Ą5
12
Model selection
3Ą9
12.1
Introduction
3Ą9
12.2
Representations of the data and model
350
12.3
Graphical comparison of the density and
distribution functions
351
124
Hypothesis tests
356
12.4-1
Kolmogorov-Smirnov test
357
12.4-2
Anderson-Darling test
360
12.4-3
Chi-square goodness-of-fit test
360
12-4-4
Likelihood ratio test
365
12.5
Selecting a model
367
12.5.1
Introduction
367
12.5.2
Judgment-based approaches
368
12.5.3
Score-based approaches
368
12.6
Exercises
375
13
Fitting extreme value models
383
13.1
Introduction
383
13.2
Parameter estimation
384
13.2.1
ML estimation from the extreme value
distribution
384
13.2.2
ML estimation from the generalized
Pareto distribution
387
13.2.3
Estimating the Pareto shape parameter
389
13.2-4
Estimating extreme probabilities
391
13.3
Model selection
392
13.3.1
Mean excess plots
392
1Ą
Fitting
copula
models
395
1Ą.1
Introduction
395
1Ą.2
Maximum likelihood estimation
396
1Ą.3
S'emiparametric
estimation of the copula
398
144
The role of thresholds
399
14-5
Goodness-of-fit testing 4OI
I4.6 An example
402
Appendix A Gamma and related functions
407
Appendix
В
Discretization of the severity distribution
B.I The method of rounding
B.2 Mean preserving
B.3 Undiscretization of
a dis
cretized distribution
413
Appendix
С
Nelder-
Mead simplex method
415
References
4
Π
Index
426
Oßerational Rist
Modeling Analytics is organized around the principle that the analysis of operational risk consists, in
part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide
risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of
operational risk in both the banking and insurance sectors.
Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically
to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of opera¬
tional risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement
of concepts.
Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business
management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using
the tools of probability, statistics, and actuarial science.
In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features:
Ample exercises to further elucidate the concepts in the text
Definitive coverage of distribution functions and related concepts
Models for the size of losses
Models for frequency of loss
Aggregate loss modeling
Extreme value modeling
Dependency modeling using copulas
Statistical methods in model selection and calibration
Assuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for
beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also
useful as a reference for practitioners in both enterprise risk management and risk and operational management. |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Panjer, Harry H. 1946- |
| author_GND | (DE-588)1044735732 |
| author_facet | Panjer, Harry H. 1946- |
| author_role | aut |
| author_sort | Panjer, Harry H. 1946- |
| author_variant | h h p hh hhp |
| building | Verbundindex |
| bvnumber | BV021748225 |
| callnumber-first | H - Social Science |
| callnumber-label | HD61 |
| callnumber-raw | HD61 |
| callnumber-search | HD61 |
| callnumber-sort | HD 261 |
| callnumber-subject | HD - Industries, Land Use, Labor |
| classification_rvk | QK 300 |
| classification_tum | WIR 160f |
| ctrlnum | (OCoLC)64771111 (DE-599)BVBBV021748225 |
| dewey-full | 658.15/5 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.15/5 |
| dewey-search | 658.15/5 |
| dewey-sort | 3658.15 15 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV021748225 |
| illustrated | Illustrated |
| index_date | 2024-07-02T15:31:24Z |
| indexdate | 2024-07-09T20:43:08Z |
| institution | BVB |
| isbn | 0471760897 9780471760894 |
| language | English |
| lccn | 2006044261 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014961473 |
| oclc_num | 64771111 |
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| physical | XV, 431 S. graph. Darst. |
| publishDate | 2006 |
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| spelling | Panjer, Harry H. 1946- Verfasser (DE-588)1044735732 aut Operational risk modeling analytics Harry H. Panjer Operational risks Hoboken, NJ Wiley Interscience 2006 XV, 431 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Wiley series in probability and statistics Includes bibliographical references and index Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors. Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts. Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science. Gestion du risque Risk management Risikomanagement (DE-588)4121590-4 gnd rswk-swf Risikomanagement (DE-588)4121590-4 s DE-604 http://www.loc.gov/catdir/enhancements/fy0645/2006044261-d.html Publisher description Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014961473&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014961473&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Panjer, Harry H. 1946- Operational risk modeling analytics Gestion du risque Risk management Risikomanagement (DE-588)4121590-4 gnd |
| subject_GND | (DE-588)4121590-4 |
| title | Operational risk modeling analytics |
| title_alt | Operational risks |
| title_auth | Operational risk modeling analytics |
| title_exact_search | Operational risk modeling analytics |
| title_exact_search_txtP | Operational risk modeling analytics |
| title_full | Operational risk modeling analytics Harry H. Panjer |
| title_fullStr | Operational risk modeling analytics Harry H. Panjer |
| title_full_unstemmed | Operational risk modeling analytics Harry H. Panjer |
| title_short | Operational risk |
| title_sort | operational risk modeling analytics |
| title_sub | modeling analytics |
| topic | Gestion du risque Risk management Risikomanagement (DE-588)4121590-4 gnd |
| topic_facet | Gestion du risque Risk management Risikomanagement |
| url | http://www.loc.gov/catdir/enhancements/fy0645/2006044261-d.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014961473&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=014961473&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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