LEADER 01096nam--2200349---450- 001 990002168930203316 005 20091028170434.0 035 $a000216893 035 $aUSA01000216893 035 $a(ALEPH)000216893USA01 035 $a000216893 100 $a20041112d1971----km-y0itay0103----ba 101 $afre 102 $aBE 105 $a||||||||001yy 200 1 $aTendances du fédéralisme en théorie et en pratique$fCarl J. Friedrich$gtraduit de l'anglais par André et Lucie Philippart 210 $aBruxelles$cInstitut Belge de science politique$d1971 215 $a205 p.$d22 cm 410 0$12001 454 1$12001 461 1$1001-------$12001 676 $a321.02 700 1$aFRIEDRICH,$bCarl J.$0118600 801 0$aIT$bsalbc$gISBD 912 $a990002168930203316 951 $a321.02 FRI 1 (IG VIII 13 301)$b40944 G.$cIG VIII 13$d00245947 959 $aBK 969 $aECO 979 $aSIAV2$b10$c20041112$lUSA01$h1703 979 $aRSIAV3$b90$c20091028$lUSA01$h1704 996 $aTendances du fédéralisme en théorie et en pratique$91038123 997 $aUNISA LEADER 01276aam 2200373I 450 001 9910710752803321 005 20160421112349.0 024 8 $aGOVPUB-C13-a23c1ee474835c084dc5a5a671d9e9ca 035 $a(CKB)5470000002478779 035 $a(OCoLC)947049568 035 $a(EXLCZ)995470000002478779 100 $a20160421d2009 ua 0 101 0 $aeng 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aManufacturing interoperability program, a synopsis /$fSharon J. Kemmerer 210 1$aGaithersburg, MD :$cU.S. Dept. of Commerce, National Institute of Standards and Technology,$d2009. 215 $a1 online resource 225 1 $aNISTIR ;$v7533 300 $a2009. 300 $aContributed record: Metadata reviewed, not verified. Some fields updated by batch processes. 300 $aTitle from PDF title page. 320 $aIncludes bibliographical references. 700 $aKemmerer$b Sharon J$01397785 701 $aKemmerer$b Sharon J$01397785 712 02$aNational Institute of Standards and Technology (U.S.) 801 0$bNBS 801 1$bNBS 801 2$bGPO 906 $aBOOK 912 $a9910710752803321 996 $aManufacturing interoperability program, a synopsis$93466756 997 $aUNINA LEADER 05303nam 22006614a 450 001 9911019275103321 005 20200520144314.0 010 $a9786610551699 010 $a9781280551697 010 $a1280551690 010 $a9780470051313 010 $a0470051310 010 $a9780470051306 010 $a0470051302 035 $a(CKB)1000000000354827 035 $a(EBL)269139 035 $a(OCoLC)166353635 035 $a(SSID)ssj0000215350 035 $a(PQKBManifestationID)11189737 035 $a(PQKBTitleCode)TC0000215350 035 $a(PQKBWorkID)10184707 035 $a(PQKB)10634923 035 $a(MiAaPQ)EBC269139 035 $a(Perlego)2765550 035 $a(EXLCZ)991000000000354827 100 $a20060309d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aOperational risk $emodeling analytics /$fHarry H. Panjer 210 $aHoboken, N.J. $cWiley Interscience$dc2006 215 $a1 online resource (460 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 08$a9780471760894 311 08$a0471760897 320 $aIncludes bibliographical references (p. 417-425) and index. 327 $aOperational Risk; Contents; Preface; Acknowledgments; Part I Introduction to operational risk modeling; 1 Operational risk; 1.1 Introduction; 1.1.1 Basel II - General; 1.1.2 Basel II - Operational risk; 1.2 Operational risk in insurance; 1.3 The analysis of operational risk; 1.4 The model- based approach; 1.4.1 The modeling process; 1.5 Organization of this book; 2 Basic probability concepts; 2.1 Introduction; 2.2 Distribution functions and related concepts; 2.3 Moments; 2.4 Quantiles of a distribution; 2.5 Generating functions; 2.6 Exercises; 3 Measures of risk; 3.1 Introduction 327 $a3.2 Risk measures3.3 Tail- Value-at- Risk; Part II Probabilistic tools for operational risk modeling; 4 Models for the size of losses: Continuous distributions; 4.1 Introduction; 4.2 An inventory of continuous distributions; 4.2 1 One-parameter distributions; 4.2.2 Two-parameter distributions; 4.2.3 Three-parameter distributions; 4.2.4 Four-parameter distributions; 4.2.5 Distributions with finite support; 4.3 Selected distributions and their relationships; 4.3.1 Introduction; 4.3.2 Two important parametric families; 4.4 Limiting distributions; 4.5 The role of parameters 327 $a4.5.1 Parametric and scale distributions4.5.2 Finite mixture distributions; 4.5.3 Data-dependent distributions; 4.6 Tails of distributions; 4.6.1 Classification based on moments; 4.6.2 Classification based on tail behavior; 4.6.3 Classification based on hazard rate function; 4.7 Creating new distributions; 4.7.1 Introduction; 4.7.2 Multiplication by a constant; 4.7.3 Transformation by raising to a power; 4.7.4 Transformation by exponentiation; 4.7.5 Continuous mixture of distributions; 4.7.6 Frailty models; 4.7.7 Splicing pieces of distributions; 4.8 TVaR for continuous distributions 327 $a4.8.1 Continuous elliptical distributions4.8.2 Continuous exponential dispersion distributions; 4.9 Exercises; 5 Models for the number of losses: Counting distributions; 5.1 Introduction; 5.2 The Poisson distribution; 5.3 The negative binomial distribution; 5.4 The binomial distribution; 5.5 The (a, b, 0) class; 5.6 The (a, b, 1) class; 5.7 Compound frequency models; 5.8 Recursive calculation of compound probabilities; 5.9 An inventory of discrete distributions; 5.9.1 The (a, b, 0) class; 5.9.2 The (a, b, 1 ) class; 5.9.3 The zero-truncated subclass; 5.9.4 The zero-modified subclass 327 $a5.9.5 The compound class5.10 A hierarchy of discrete distributions; 5.11 Further properties of the compound Poisson class; 5.12 Mixed frequency models; 5.13 Poisson mixtures; 5.14 Effect of exposure on loss counts; 5.15 TVaR for discrete distributions; 5.15.1 TVaR for discrete exponential dispersion distributions; 5.16 Exercises; 6 Aggregate loss models; 6.1 Introduction; 6.2 Model choices; 6.3 The compound model for aggregate losses; 6.4 Some analytic results; 6.5 Evaluation of the aggregate loss distribution; 6.6 The recursive method; 6.6.1 Compound frequency models 327 $a6.6.2 Underflow/overflow problems 330 $aDiscover how to optimize business strategies from both qualitative and quantitative points of viewOperational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors.Beginning with a foundation for operational risk modeling and a focus on 410 0$aWiley series in probability and statistics. 606 $aRisk management 615 0$aRisk management. 676 $a658.15/5 700 $aPanjer$b Harry H$0437806 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019275103321 996 $aOperational risk$94418567 997 $aUNINA