LEADER 00675nam0 2200229 450 001 000025534 005 20190319154836.0 100 $a20090504d1932----km-y0itay50------ba 101 0 $aeng 102 $aUS 105 $ay-------001yy 200 1 $aAmerican railroads$efour phases of their history 210 $aPrinceton$cPrinceton University Press$d1932 215 $a120 p.$d22 cm 500 10$aAmerican railroads$944285 676 $a385.09$v20 700 1$aDaniels,$bWinthrop More$0633406 801 0$aIT$bUNIPARTHENOPE$c20090504$gRICA$2UNIMARC 912 $a000025534 951 $aDEP V-0086$bs. i.$cNAVA4$d2009 996 $aAmerican railroads$944285 997 $aUNIPARTHENOPE LEADER 01090nam a22002651i 4500 001 991000420469707536 005 20040827121241.0 008 040920s1998 xxu eng 020 $a9780195108095 035 $ab13218104-39ule_inst 035 $aARCHE-116434$9ExL 040 $aSet. Economia$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a332.6015 100 1 $aLuenberger, David G$06376 245 10$aInvestment science /$cDavid G. Luenberger 260 $aNew York ;$aOxford :$bOxford University,$c1998 300 $aXIV, 494 p. ;$c24 cm 650 4$aInvestimenti$xModelli matematici 907 $a.b13218104$b30-05-18$c23-09-04 912 $a991000420469707536 945 $aLE025 ECO 332.6 LUE01.01 $g1$i2025000199385$lle025$nCatalogato 2018$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i13874147$z23-09-04 945 $aLE025 ECO 332.6 LUE01.01 $g2$i2025000199354$lle025$nCatalogato 2018$o-$pE0.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i13874159$z23-09-04 996 $aInvestment science$913838 997 $aUNISALENTO 998 $ale025$b23-09-04$cm$da $e-$feng$gxxu$h0$i2 LEADER 06181nam 2200913 a 450 001 9910139058703321 005 20200520144314.0 010 $a9781118818589 010 $a111881858X 010 $a9780470661673 010 $a0470661674 010 $a9780470661789 010 $a047066178X 010 $a9781299315891 010 $a1299315895 010 $a9780470662496 010 $a0470662492 035 $a(CKB)2560000000100449 035 $a(EBL)1144006 035 $a(SSID)ssj0000832980 035 $a(PQKBManifestationID)11440131 035 $a(PQKBTitleCode)TC0000832980 035 $a(PQKBWorkID)10918987 035 $a(PQKB)10146887 035 $a(DLC) 2013001506 035 $a(Au-PeEL)EBL1144006 035 $a(CaPaEBR)ebr10674827 035 $a(CaONFJC)MIL462839 035 $a(iGPub)WILEYB0012791 035 $a(PPN)235042463 035 $a(FINmELB)ELB177641 035 $a(MiAaPQ)EBC1144006 035 $a(OCoLC)824120034 035 $a(FR-PaCSA)88813015 035 $a(FRCYB88813015)88813015 035 $a(Perlego)1008362 035 $a(EXLCZ)992560000000100449 100 $a20150303d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCounterparty credit risk, collateral and funding $ewith pricing cases for all asset classes /$fDamiano Brigo, Massimo Morini, Andrea Pallavicini 205 $a1st ed. 210 $aChichester, England $cWiley$dc2013 215 $a1 online resource (465 p.) 225 1 $aWiley Finance 300 $aDescription based upon print version of record. 311 08$a9780470748466 311 08$a047074846X 320 $aIncludes bibliographical references and index. 327 $aCounterparty Credit Risk, Collateral and Funding; Contents; Ignition; Abbreviations and Notation; PART I COUNTERPARTY CREDIT RISK, COLLATERAL AND FUNDING; 1 Introduction; 1.1 A Dialogue on CVA; 1.2 Risk Measurement: Credit VaR; 1.3 Exposure, CE, PFE, EPE, EE, EAD; 1.4 Exposure and Credit VaR; 1.5 Interlude: P and Q; 1.6 Basel; 1.7 CVA and Model Dependence; 1.8 Input and Data Issues on CVA; 1.9 Emerging Asset Classes: Longevity Risk; 1.10 CVA and Wrong Way Risk; 1.11 Basel III: VaR of CVA and Wrong Way Risk; 1.12 Discrepancies in CVA Valuation: Model Risk and Payoff Risk 327 $a1.13 Bilateral Counterparty Risk: CVA and DVA1.14 First-to-Default in CVA and DVA; 1.15 DVA Mark-to-Market and DVA Hedging; 1.16 Impact of Close-Out in CVA and DVA; 1.17 Close-Out Contagion; 1.18 Collateral Modelling in CVA and DVA; 1.19 Re-Hypothecation; 1.20 Netting; 1.21 Funding; 1.22 Hedging Counterparty Risk: CCDS; 1.23 Restructuring Counterparty Risk: CVA-CDOs and Margin Lending; 2 Context; 2.1 Definition of Default: Six Basic Cases; 2.2 Definition of Exposures; 2.3 Definition of Credit Valuation Adjustment (CVA); 2.4 Counterparty Risk Mitigants: Netting 327 $a2.5 Counterparty Risk Mitigants: Collateral2.5.1 The Credit Support Annex (CSA); 2.5.2 The ISDA Proposal for a New Standard CSA; 2.5.3 Collateral Effectiveness as a Mitigant; 2.6 Funding; 2.6.1 A First Attack on Funding Cost Modelling; 2.6.2 The General Funding Theory and its Recursive Nature; 2.7 Value at Risk (VaR) and Expected Shortfall (ES) of CVA; 2.8 The Dilemma of Regulators and Basel III; 3 Modelling the Counterparty Default; 3.1 Firm Value (or Structural) Models; 3.1.1 The Geometric Brownian Assumption; 3.1.2 Merton's Model; 3.1.3 Black and Cox's (1976) Model 327 $a3.1.4 Credit Default Swaps and Default Probabilities3.1.5 Black and Cox (B&C) Model Calibration to CDS: Problems; 3.1.6 The AT1P Model; 3.1.7 A Case Study with AT1P: Lehman Brothers Default History; 3.1.8 Comments; 3.1.9 SBTV Model; 3.1.10 A Case Study with SBTV: Lehman Brothers Default History; 3.1.11 Comments; 3.2 Firm Value Models: Hints at the Multiname Picture; 3.3 Reduced Form (Intensity) Models; 3.3.1 CDS Calibration and Intensity Models; 3.3.2 A Simpler Formula for Calibrating Intensity to a Single CDS; 3.3.3 Stochastic Intensity: The CIR Family 327 $a3.3.4 The Cox-Ingersoll-Ross Model (CIR) Short-Rate Model for r3.3.5 Time-Inhomogeneous Case: CIR++ Model; 3.3.6 Stochastic Diffusion Intensity is Not Enough: Adding Jumps. The JCIR(++) Model; 3.3.7 The Jump-Diffusion CIR Model (JCIR); 3.3.8 Market Incompleteness and Default Unpredictability; 3.3.9 Further Models; 3.4 Intensity Models: The Multiname Picture; 3.4.1 Choice of Variables for the Dependence Structure; 3.4.2 Firm Value Models?; 3.4.3 Copula Functions; 3.4.4 Copula Calibration, CDOs and Criticism of Copula Functions; PART II PRICING COUNTERPARTY RISK: UNILATERAL CVA 327 $a4 Unilateral CVA and Netting for Interest Rate Products 330 $aThe book's content is focused on rigorous and advanced quantitative methods for the pricing and hedging of counterparty credit and funding risk. The new general theory that is required for this methodology is developed from scratch, leading to a consistent and comprehensive framework for counterparty credit and funding risk, inclusive of collateral, netting rules, possible debit valuation adjustments, re-hypothecation and closeout rules. The book however also looks at quite practical problems, linking particular models to particular 'concrete' financial situations across asset classes, incl 410 0$aWiley finance series. 606 $aFinance$xMathematical models 606 $aCredit$xMathematical models 606 $aCredit derivatives$xMathematical models 606 $aFinancial risk$xMathematical models 615 0$aFinance$xMathematical models. 615 0$aCredit$xMathematical models. 615 0$aCredit derivatives$xMathematical models. 615 0$aFinancial risk$xMathematical models. 676 $a332.701/5195 700 $aBrigo$b Damiano$0614126 701 $aPallavicini$b Andrea$0979162 701 $aMorini$b Massimo$0930112 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139058703321 996 $aCounterparty credit risk, collateral and funding$92232068 997 $aUNINA