LEADER 05572nam 2200709 450 001 9910131284903321 005 20200520144314.0 010 $a1-118-90954-2 010 $a1-118-90956-9 035 $a(CKB)3710000000413224 035 $a(EBL)1895736 035 $a(SSID)ssj0001481273 035 $a(PQKBManifestationID)11830747 035 $a(PQKBTitleCode)TC0001481273 035 $a(PQKBWorkID)11497757 035 $a(PQKB)10263027 035 $a(Au-PeEL)EBL1895736 035 $a(CaPaEBR)ebr11053048 035 $a(OCoLC)883305082 035 $a(CaSebORM)9781118909539 035 $a(MiAaPQ)EBC1895736 035 $a(PPN)192687379 035 $a(EXLCZ)993710000000413224 100 $a20150520h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in heavy tailed risk modeling $ea handbook of operational risk /$fGareth W. Peters, Pavel V. Shevchenko 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d2015. 210 4$dİ2015 215 $a1 online resource (662 p.) 225 1 $aWiley Handbooks in Financial Engineering and Econometrics 300 $aDescription based upon print version of record. 311 $a1-118-90955-0 311 $a1-118-90953-4 320 $aIncludes bibliographical references and index. 327 $aCover; 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 327 $a2.3 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 327 $a2.4.8 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 327 $aChapter 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: ?-Stable Family; 4.1 Infinitely Divisible and Self-Decomposable Loss Random Variables 327 $a4.1.1 Basic Properties of Characteristic Functions4.1.2 Divisibility and Self-Decomposability of Loss Random Variables; 4.2 Characterizing Heavy-Tailed ?-Stable Severity Models; 4.2.1 Characterisations of ?-Stable Severity Models via the Domain of Attraction; 4.3 Deriving the Properties and Characterizations of the ?-Stable Severity Models; 4.3.1 Unimodality of ?-Stable Severity Models; 4.3.2 Relationship between L Class and ?-Stable Distributions; 4.3.3 Fundamentals of Obtaining the ?-Stable Characteristic Function 327 $a4.3.4 From Le?vy-Khinchin's Canonical Representation to the ?-Stable Characteristic Function Parameterizations 330 $a A cutting-edge guide for the theories, applications, and statistical methodologies essential to heavy tailed risk modeling Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques. Featuring a unique balance of mathematical and statistical perspectives, the handbook begins by introducing the motivation for heavy tailed risk pro 410 0$aWiley handbooks in financial engineering and econometrics. 606 $aRisk management 606 $aOperational risk 615 0$aRisk management. 615 0$aOperational risk. 676 $a658.15/5 686 $aMAT029000$aTEC009060$aBUS004000$2bisacsh 700 $aPeters$b Gareth W.$f1978-$0943026 702 $aShevchenko$b Pavel V. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910131284903321 996 $aAdvances in heavy tailed risk modeling$92128089 997 $aUNINA