00902nam0-2200313---450-99000908926040332120100329094627.0978-3-03719-068-5000908926FED01000908926(Aleph)000908926FED0100090892620090911d2009----km-y0itay50------baengCHa---a---001yy<<The >>formation of black holes in general relativityZurichEuropean Mathematical Societyc2009EMS Monographs in MathematicsRelativitàGravitàChristodoulou,Demetrios<1951- >48534ITUNINARICAUNIMARCBK99000908926040332123-332D.S.F. 9202FI1FI1Formation of black holes in general relativity785717UNINA05666nam 2200733 a 450 991082708810332120240313214332.0978111873398111187339839781118733691111873369X97811187339051118733908(CKB)2670000000369870(EBL)1187184(OCoLC)843331623(SSID)ssj0000904919(PQKBManifestationID)11494817(PQKBTitleCode)TC0000904919(PQKBWorkID)10926277(PQKB)10134411(MiAaPQ)EBC1187184(Au-PeEL)EBL1187184(CaPaEBR)ebr10700399(CaONFJC)MIL491919(Perlego)1000910(EXLCZ)99267000000036987020130123d2013 uy 0engurcn|||||||||txtccrVaR methodology for non-gaussian finance /Marine Habart-Corlosquet, Jacques Janssen, Raimondo Manca1st ed.Hoboken, N.J. ISTE Ltd./John Wiley and Sons Inc.20131 online resource (177 p.)Focus series in finance, business and management,2051-2481Description based upon print version of record.9781848214644 1848214642 Includes bibliographical references and index.Cover; Title Page; Contents; INTRODUCTION; CHAPTER 1. USE OF VALUE-AT-RISK (VAR) TECHNIQUES FOR SOLVENCY II, BASEL II AND III; 1.1. Basic notions of VaR; 1.1.1. Definition; 1.1.2. Calculation methods; 1.1.3. Advantages and limits; 1.2. The use of VaR for insurance companies; 1.2.1. Regulatory approach; 1.2.2. Risk profile approach; 1.3. The use of VaR for banks; 1.3.1. Basel II; 1.3.2. Basel III; 1.4. Conclusion; CHAPTER 2. CLASSICAL VALUE-AT-RISK (VAR) METHODS; 2.1. Introduction; 2.2. Risk measures; 2.3. General form of the VaR; 2.4. VaR extensions: tail VaR and conditional VaR2.5. VaR of an asset portfolio 2.5.1. VaR methodology; 2.6. A simulation example: the rates of investment of assets; CHAPTER 3. VAR EXTENSIONS FROM GAUSSIAN FINANCE TO NON-GAUSSIAN FINANCE; 3.1. Motivation; 3.2. The normal power approximation; 3.3. VaR computation with extreme values; 3.3.1. Extreme value theory; 3.3.2. VaR values; 3.3.3. Comparison of methods; 3.3.4. VaR values in extreme theory; 3.4. VaR value for a risk with Pareto distribution; 3.4.1. Forms of the Pareto distribution; 3.4.2. Explicit forms VaR and CVaR in Pareto case; 3.4.3. Example of computation by simulation3.5. Conclusion CHAPTER 4. NEW VAR METHODS OF NON-GAUSSIAN FINANCE; 4.1. Lévy processes; 4.1.1. Motivation; 4.1.2. Notion of characteristic functions; 4.1.3. Lévy processes; 4.1.4. Lévy-Khintchine formula; 4.1.5. Examples of Lévy processes; 4.1.6. Variance gamma (VG) process; 4.1.7. Risk neutral measures for Lévy models in finance; 4.1.8. Particular Lévy processes: Poisson-Brownian model with jumps; 4.1.9. Particular Lévy processes: Merton model with jumps; 4.1.10. VaR techniques for Lévy processes; 4.2. Copula models and VaR techniques; 4.2.1. Introduction; 4.2.2. Sklar theorem (1959)4.2.3. Particular case and Fréchet bounds 4.2.4. Examples of copula; 4.2.5. The normal copula; 4.2.6. Estimation of copula; 4.2.7. Dependence; 4.2.8. VaR with copula; 4.3. VaR for insurance; 4.3.1. VaR and SCR; 4.3.2. Particular cases; CHAPTER 5. NON-GAUSSIAN FINANCE: SEMI-MARKOV MODELS; 5.1. Introduction; 5.2. Homogeneous semi-Markov process; 5.2.1. Basic definitions; 5.2.2. Basic properties [JAN 09]; 5.2.3. Particular cases of MRP; 5.2.4. Asymptotic behavior of SMP; 5.2.5. Non-homogeneous semi-Markov process; 5.2.6. Discrete-time homogeneous and non-homogeneous semi-Markov processes5.2.7. Semi-Markov backward processes in discrete time 5.2.8. Semi-Markov backward processes in discrete time; 5.3. Semi-Markov option model; 5.3.1. General model; 5.3.2. Semi-Markov Black-Scholes model; 5.3.3. Numerical application for the semi-Markov Black-Scholes model; 5.4. Semi-Markov VaR models; 5.4.1. The environment semi-Markov VaR (ESMVaR) model; 5.4.2. Numerical applications for the semi-MarkovVaR model; 5.4.3. Semi-Markov extension of the Merton's model; 5.5. The Semi-Markov Monte Carlo Model in a homogeneous environment; 5.5.1. Capital at Risk; 5.5.2. A credit risk exampleCONCLUSIONWith the impact of the recent financial crises, more attention must be given to new models in finance rejecting "Black-Scholes-Samuelson" assumptions leading to what is called non-Gaussian finance. With the growing importance of Solvency II, Basel II and III regulatory rules for insurance companies and banks, value at risk (VaR) - one of the most popular risk indicator techniques plays a fundamental role in defining appropriate levels of equities. The aim of this book is to show how new VaR techniques can be built more appropriately for a crisis situation.VaR methodology for non-GaussFocus series (London, England)Financial risk managementFinancial risk management.332.0151Habart-Corlosquet Marine1654500Janssen Jacques726990Manca Raimondo327298John Wiley & Sons.MiAaPQMiAaPQMiAaPQBOOK9910827088103321VaR methodology for non-gaussian finance4006370UNINA