Var Methodology For Non-Gaussian Finance

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With 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

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About the Authors Marine Habart-Corlosquet is a Qualified and Certified Actuary at BNP Paribas Cardif, Paris, France

Classical Value-at-Risk VaR Methods

Contents 1

He is associate editor for the journal Methodology and Computing in Applied Probability

Her main research interests are pandemics, Solvency II internal models and ALM issues for insurance companies

His main research interests are multidimensional linear algebra, computational probability, application of stochastic processes to economics, finance and insurance and simulation models.

Jacques Janssen is now Honorary Professor at the Solvay Business School ULB in Brussels, Belgium, having previously taught at EURIA Euro-Institut d Actuariat, University of West Brittany, Brest, France and Telecom Bretagne Brest, France as well as being a director of Jacan Insurance and Finance Services, a consultancy and training company

New VaR Methods of Non-Gaussian Finance

Non-Gaussian Finance Semi-Markov Models

Raimondo Manca is Professor of mathematical methods applied to economics, finance and actuarial science at University of Roma La Sapienza in Italy

Several non-Gaussian models using Copula methodology, L vy processes along with particular attention to models with jumps such as the Merton model are presented as are the consideration of time homogeneous and non-homogeneous Markov and semi-Markov processes and for each of these models

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 Institute of Actuaries

She teaches at EURIA, Telecom Bretagne and Ecole Centrale Paris France

The aim of this book is to show how new VaR techniques can be built more appropriately for a crisis situation

Use of Value-at-Risk VaR Techniques for Solvency II, Basel II and III

VaR Extensions from Gaussian Finance to Non-Gaussian Finance

VaR methodology for non-Gaussian finance looks at the importance of VaR in standard international rules for banks and insurance companies gives the first non-Gaussian extensions of VaR and applies several basic statistical theories to extend classical results of VaR techniques such as the NP approximation, the Cornish-Fisher approximation, extreme and a Pareto distribution

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

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