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. 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-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. Several non-Gaussian models using Copula
methodology, Lévy 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.
Contents
1. Use of Value-at-Risk (VaR) Techniques for Solvency II, Basel II and
III.
2. Classical Value-at-Risk (VaR) Methods.
3. VaR Extensions from Gaussian Finance to Non-Gaussian Finance.
4. New VaR Methods of Non-Gaussian Finance.
5. Non-Gaussian Finance: Semi-Markov Models.
