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Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Handbuch ; Handbook |
Language: | English |
Notes: | Literaturverz. S. 597 - 621 Cover; Title Page; Copyright; Dedication; Contents in Brief; Contents; Preface; Acronyms; Symbols; List of Distributions; Chapter 1 Motivation for Heavy-Tailed Models; 1.1 Structure of the Book; 1.2 Dominance of the Heaviest Tail Risks; 1.3 Empirical Analysis Justifying Heavy-Tailed Loss Models-in OpRisk; 1.4 Motivating Parametric, Spliced and Non-Parametric Severity Models; 1.5 Creating Flexible Heavy-Tailed Models via Splicing; Chapter 2 Fundamentals of Extreme Value Theory for OpRisk; 2.1 Introduction; 2.2 Historical Perspective on EVT and Risk 2.3 Theoretical Properties of Univariate EVT-Block Maxima and the GEV Family2.4 Generalized Extreme Value Loss Distributional Approach (GEV-LDA); 2.4.1 Statistical Considerations for Applicability of the GEV Model; 2.4.2 Various Statistical Estimation Procedures for the GEV Model Parameters in OpRisk Settings; 2.4.3 GEV Sub-Family Approaches in OpRisk LDA Modeling; 2.4.4 Properties of the Frechet-Pareto Family of Severity Models; 2.4.5 Single Risk LDA Poisson-Generalized Pareto Family; 2.4.6 Single Risk LDA Poisson-Burr Family; 2.4.7 Properties of the Gumbel family of Severity Models 2.4.8 Single Risk LDA Poisson-LogNormal Family2.4.9 Single Risk LDA Poisson-Benktander II Models; 2.5 Theoretical Properties of Univariate EVT-Threshold Exceedances; 2.5.1 Understanding the Distribution of Threshold Exceedances; 2.6 Estimation Under the Peaks Over Threshold Approach via the Generalized Pareto Distribution; 2.6.1 Maximum-Likelihood Estimation Under the GPD Model; 2.6.2 Comments on Probability-Weighted Method of Moments Estimation Under the GPD Model; 2.6.3 Robust Estimators of the GPD Model Parameters; 2.6.4 EVT-Random Number of Losses Chapter 3 Heavy-Tailed Model Class Characterizations for LDA3.1 Landau Notations for OpRisk Asymptotics: Big and Little `Oh'; 3.2 Introduction to the Sub-Exponential Family of Heavy-Tailed Models; 3.3 Introduction to the Regular and Slow Variation Families-of Heavy-Tailed Models; 3.4 Alternative Classifications of Heavy-Tailed Models and Tail Variation; 3.5 Extended Regular Variation and Matuszewska Indices for Heavy-Tailed Models; Chapter 4 Flexible Heavy-Tailed Severity Models: α-Stable Family; 4.1 Infinitely Divisible and Self-Decomposable Loss Random Variables 4.1.1 Basic Properties of Characteristic Functions4.1.2 Divisibility and Self-Decomposability of Loss Random Variables; 4.2 Characterizing Heavy-Tailed α-Stable Severity Models; 4.2.1 Characterisations of α-Stable Severity Models via the Domain of Attraction; 4.3 Deriving the Properties and Characterizations of the α-Stable Severity Models; 4.3.1 Unimodality of α-Stable Severity Models; 4.3.2 Relationship between L Class and α-Stable Distributions; 4.3.3 Fundamentals of Obtaining the α-Stable Characteristic Function 4.3.4 From Lévy-Khinchin's Canonical Representation to the α-Stable Characteristic Function Parameterizations |
ISBN: | 978-1-118-90953-9 |
Classification: | Investition, Finanzierung |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013546928