E-Book, Englisch, 176 Seiten, E-Book
ISBN: 978-1-118-73398-1
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
VaR methodology for non-Gaussian finance looks at the importance ofVaR in standard international rules for banks and insurancecompanies; gives the first non-Gaussian extensions of VaR andapplies several basic statistical theories to extend classicalresults of VaR techniques such as the NP approximation, theCornish-Fisher approximation, extreme and a Pareto distribution.Several non-Gaussian models using Copula methodology, Lévyprocesses along with particular attention to models with jumps suchas the Merton model are presented; as are the consideration of timehomogeneous and non-homogeneous Markov and semi-Markov processesand for each of these models.
Contents
1. Use of Value-at-Risk (VaR) Techniques for Solvency II, BaselII and III.
2. Classical Value-at-Risk (VaR) Methods.
3. VaR Extensions from Gaussian Finance to Non-GaussianFinance.
4. New VaR Methods of Non-Gaussian Finance.
5. Non-Gaussian Finance: Semi-Markov Models.
About the Authors
Marine Habart-Corlosquet is a Qualified and Certified Actuary atBNP Paribas Cardif, Paris, France. She is co-director of EURIA(Euro-Institut d'Actuariat, University of West Brittany,Brest, France), and associate researcher at Telecom Bretagne(Brest, France) as well as a board member of the French Instituteof Actuaries. She teaches at EURIA, Telecom Bretagne and EcoleCentrale Paris (France). Her main research interests are pandemics,Solvency II internal models and ALM issues for insurancecompanies.
Jacques Janssen is now Honorary Professor at the Solvay BusinessSchool (ULB) in Brussels, Belgium, having previously taught atEURIA (Euro-Institut d'Actuariat, University of WestBrittany, Brest, France) and Telecom Bretagne (Brest, France) aswell as being a director of Jacan Insurance and Finance Services, aconsultancy and training company.
Raimondo Manca is Professor of mathematical methods applied toeconomics, finance and actuarial science at University of Roma"La Sapienza" in Italy. He is associate editor for thejournal Methodology and Computing in Applied Probability. His mainresearch interests are multidimensional linear algebra,computational probability, application of stochastic processes toeconomics, finance and insurance and simulation models.
Autoren/Hrsg.
Weitere Infos & Material
INTRODUCTION ix
CHAPTER 1. USE OF VALUE-AT-RISK (VAR) TECHNIQUES FOR SOLVENCYII, BASEL II AND III 1
1.1. Basic notions of VaR 1
1.2. The use of VaR for insurance companies 6
1.3. The use of VaR for banks 13
1.4. Conclusion 16
CHAPTER 2. CLASSICAL VALUE-AT-RISK (VAR) METHODS 17
2.1. Introduction 17
2.2. Risk measures 18
2.3. General form of the VaR 19
2.4. VaR extensions: tail VaR and conditional VaR 25
2.5. VaR of an asset portfolio 28
2.6. A simulation example: the rates of investment of assets32
CHAPTER 3. VAR EXTENSIONS FROM GAUSSIAN FINANCE TONON-GAUSSIAN FINANCE 35
3.1. Motivation 35
3.2. The normal power approximation 37
3.3. VaR computation with extreme values 40
3.4. VaR value for a risk with Pareto distribution 56
3.5. Conclusion 62
CHAPTER 4. NEW VAR METHODS OF NON-GAUSSIAN FINANCE 63
4.1. Lévy processes 63 model with jumps 76
4.2. Copula models and VaR techniques 90
4.3. VaR for insurance 109
CHAPTER 5. NON-GAUSSIAN FINANCE: SEMI-MARKOV MODELS115
5.1. Introduction 115
5.2. Homogeneous semi-Markov process 116
5.3. Semi-Markov option model 139
5.4. Semi-Markov VaR models 143
5.5. The Semi-Markov Monte Carlo Model in a homogeneousenvironment 147
CONCLUSION 159
BIBLIOGRAPHY 161
INDEX 165