LEADER 07344nam 2200697Ia 450 001 9910784641603321 005 20191030193358.0 010 $a1-280-96281-X 010 $a9786610962815 010 $a0-08-047106-4 035 $a(CKB)1000000000364147 035 $a(EBL)287921 035 $a(OCoLC)476040684 035 $a(SSID)ssj0000266534 035 $a(PQKBManifestationID)11937616 035 $a(PQKBTitleCode)TC0000266534 035 $a(PQKBWorkID)10304466 035 $a(PQKB)10734067 035 $a(Au-PeEL)EBL287921 035 $a(CaPaEBR)ebr10166983 035 $a(CaONFJC)MIL96281 035 $a(CaSebORM)9780123694669 035 $a(MiAaPQ)EBC287921 035 $a(PPN)170244288 035 $a(EXLCZ)991000000000364147 100 $a20070410d2007 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aValue at risk and bank capital management$b[electronic resource] /$fFrancesco Saita 205 $a1st edition 210 $aAmsterdam ;$aBoston $cElsevier Academic Press$dc2007 215 $a1 online resource (276 p.) 225 1 $aAcademic Press advanced finance series 300 $aDescription based upon print version of record. 311 $a0-12-369466-3 320 $aIncludes bibliographical references and index. 327 $aFront cover; Title page; Copyright page; Table of contents; Preface; About the Book; Acknowledgments; Contributors; CHAPTER 1: Value at Risk, Capital Management, and Capital Allocation; 1.1 An Introduction to Value at Risk; 1.2 Capital Management and Capital Allocation: The Structure of the Book; CHAPTER 2: What Is "Capital" Management?; 2.1 Regulatory Capital and the Evolution toward Basel II; 2.2 Overview of the Basel II Capital Accord; 2.3 Bank Estimates of Required Capital and the Different Notions of Bank Capital; 2.4 Summary; 2.5 Further Reading; CHAPTER 3: Market Risk 327 $a3.1 The Variance-Covariance Approach 3.2 Simulation Approaches: Historical Simulation and Monte Carlo Simulation; 3.3 Value at Risk for Option Positions; 3.4 Extreme Value Theory and Copulas; 3.5 Expected Shortfall and the Problem of VaR Nonsubadditivity; 3.6 Back-Testing Market Risk Models; 3.7 Internal VaR Models and Market Risk Capital Requirements; 3.8 Stress Tests; 3.9 Summary; 3.10 Further Reading; CHAPTER 4: Credit Risk; 4.1 Defining Credit Risk: Expected and Unexpected Losses; 4.2 Agency Ratings 327 $a4.3 Quantitative Techniques for Stand-Alone Credit Risk Evaluation: Moody's/KMV EDF and External Scoring Systems 4.4 Capital Requirements for Credit Risk under Basel II; 4.5 Internal Ratings; 4.6 Estimating Loss Given Default; 4.7 Estimating Exposure at Default; 4.8 Interaction between Basel II and International Accounting Standards; 4.9 Alternative Approaches to Modeling Credit Portfolio Risk; 4.10 Comparison of Main Credit Portfolio Models; 4.11 Summary; 4.12 Further Reading; CHAPTER 5: Operational Risk and Business Risk 327 $a5.1 Capital Requirements for Operational Risk Measurement under Basel II 5.2 Objectives of Operational Risk Management; 5.3 Quantifying Operational Risk: Building the Data Sources; 5.4 Quantifying Operational Risk: From Loss Frequency and Severity to Operational Risk Capital; 5.5 Case Study: U.S. Bank Progress on Measuring Operational Risk; 5.6 The Role of Measures of Business Risk and Earnings at Risk; 5.7 Measuring Business Risk in Practice: Defining a Measure of Earnings at Risk; 5.8 From Earnings at Risk to Capital at Risk; 5.9 Summary; 5.10 Further Reading 327 $aCHAPTER 6: Risk Capital Aggregation 6.1 The Need for Harmonization: Time Horizon, Confidence Level, and the Notion of Capital; 6.2 Risk Aggregation Techniques; 6.3 Estimating Parameters for Risk Aggregation; 6.4 Case Study: Capital Aggregation within Fortis; 6.5 A Synthetic Comparison of Alternative Risk Aggregation Techniques; 6.6 Summary; 6.7 Further Reading; CHAPTER 7: Value at Risk and Risk Control for Market and Credit Risk; 7.1 Defining VaR-Based Limits for Market Risk: Identifying Risk-Taking Centers 327 $a7.2 Managing VaR Limits for Market Risk: The Links between Daily VaR and Annual Potential Losses 330 $aWhile the highly technical measurement techniques and methodologies of Value at Risk have attracted huge interest, much less attention has been focused on how Value at Risk and the risk-adjusted performance measures such as RAROC or economic profit/EVA?· can be effectively used to improve a bank¡¦s decision making processes. Academic books are typically concerned primarily with measurement techniques, and devote only a small section to describing the applications, usually without discussing the problems that changing organizational processes in banks may have on business units¡¦ behaviour. Practitioners¡¦ books are often based on a single experience, presenting the approach that has been pursued by a single bank, but often do not adequately evaluate that approach. In actual practice, the choice of how to use Value at Risk and risk-adjusted performance measures has no single optimal solution, but requires effective decision making that can identify the solution that is consistent with the bank¡¦s style of management and coordination mechanisms, and often with characteristics of individual business units as well. In this book, Francesco Saita of Bocconi University argues that even though risk measurement techniques have greatly improved in recent years for market, credit and now also operational risk, capital management and capital allocation decisions are far from becoming purely technical and mechanical. On one hand, decisions about capital management must consider handling different capital constraints (e.g. regulatory vs. economic capital ) and face remarkable difficulties in providing a measure of ¡§aggregated¡¨ Value at Risk (i.e. a measure that considers the overall value at risk of the bank after diversification across risk types). On the other hand, the aim of using capital more efficiently through capital allocation cannot be achieved only through a sort of centralized asset allocation process, but rather by designing a Value at Risk limit system and a risk-adjusted performance measurement system that are designed to provide the right incentives to individual business units. This connection between sophisticated and cutting edge risk measurement techniques and practical bank decision making about capital management and capital allocation make this book unique and provide readers with a depth of academic and theoretical expertise combined with practical and real-world understanding of bank structure, organizational constraints, and dec... 410 0$aAcademic Press advanced finance series. 517 3 $aRisk adjusted performances, capital management and capital allocation decision making 606 $aBank capital 606 $aBanks and banking$xRisk management 615 0$aBank capital. 615 0$aBanks and banking$xRisk management. 676 $a332.1 700 $aSaita$b Francesco$0140065 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784641603321 996 $aValue at risk and bank capital management$91131276 997 $aUNINA LEADER 03336nam 22007695 450 001 9910741183403321 005 20250609110041.0 010 $a9783030354572 010 $a3030354571 024 7 $a10.1007/978-3-030-35457-2 035 $a(CKB)4100000010013815 035 $a(MiAaPQ)EBC5997315 035 $a(DE-He213)978-3-030-35457-2 035 $a(PPN)24281929X 035 $a(MiAaPQ)EBC5997239 035 $a(EXLCZ)994100000010013815 100 $a20191213d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEntropy and the Tao of Counting $eA Brief Introduction to Statistical Mechanics and the Second Law of Thermodynamics /$fby Kim Sharp 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (70 pages) 225 1 $aSpringerBriefs in Physics,$x2191-5431 311 08$a9783030354596 311 08$a3030354598 311 08$a9783030354565 311 08$a3030354563 330 $aThis book provides a complete and accurate atomic level statistical mechanical explanation of entropy and the second law of thermodynamics. It assumes only a basic knowledge of mechanics and requires no knowledge of calculus. The treatment uses primarily geometric arguments and college level algebra. Quantitative examples are given at each stage to buttress physical understanding. This text is of benefit to undergraduate and graduate students, as well as educators and researchers in the physical sciences (whether or not they have taken a thermodynamics course) who want to understand or teach the atomic/molecular origins of entropy and the second law. It is particularly aimed at those who, due to insufficient mathematical background or because of their area of study, are not going to take a traditional statistical mechanics course. 410 0$aSpringerBriefs in Physics,$x2191-5431 606 $aMathematical physics 606 $aChemistry, Physical and theoretical 606 $aThermodynamics 606 $aHeat engineering 606 $aHeat$xTransmission 606 $aMass transfer 606 $aStatistics 606 $aTheoretical, Mathematical and Computational Physics 606 $aPhysical Chemistry 606 $aThermodynamics 606 $aEngineering Thermodynamics, Heat and Mass Transfer 606 $aStatistical Theory and Methods 615 0$aMathematical physics. 615 0$aChemistry, Physical and theoretical. 615 0$aThermodynamics. 615 0$aHeat engineering. 615 0$aHeat$xTransmission. 615 0$aMass transfer. 615 0$aStatistics. 615 14$aTheoretical, Mathematical and Computational Physics. 615 24$aPhysical Chemistry. 615 24$aThermodynamics. 615 24$aEngineering Thermodynamics, Heat and Mass Transfer. 615 24$aStatistical Theory and Methods. 676 $a536.73 676 $a536.73 (edition:23) 700 $aSharp$b Kim$4aut$4http://id.loc.gov/vocabulary/relators/aut$0837085 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910741183403321 996 $aEntropy and the Tao of Counting$92517325 997 $aUNINA