This book provides a perspective on a number of approaches to financial modelling and risk
management. It examines both theoretical and practical issues. Theoretically financial risks
models are models of a real and a financial uncertainty based on both common and private
information and economic theories defining the rules that financial markets comply to.
Financial models are thus challenged by their definitions and by a changing financial system
fueled by globalization technology growth complexity regulation and the many factors that
contribute to rendering financial processes to be continuously questioned and re-assessed. The
underlying mathematical foundations of financial risks models provide future guidelines for
risk modeling. The book's chapters provide selective insights and developments that can
contribute to better understand the complexity of financial modelling and its ability to bridge
financial theories and their practice. Future Perspectives in Risk Models and Finance begins
with an extensive outline by Alain Bensoussan et al. of GLM estimation techniques combined with
proofs of fundamental results. Applications to static and dynamic models provide a unified
approach to the estimation of nonlinear risk models. A second section is concerned with the
definition of risks and their management. In particular Guegan and Hassani review a number of
risk models definition emphasizing the importance of bi-modal distributions for financial
regulation. An additional chapter provides a review of stress testing and their implications.
Nassim Taleb and Sandis provide an anti-fragility approach based on skin in the game. To
conclude Raphael Douady discusses the noncyclical CAR (Capital Adequacy Rule) and their
effects of aversion of systemic risks. A third section emphasizes analytic financial modelling
approaches and techniques. Tapiero and Vallois provide an overview of mathematical systems and
their use in financial modeling. These systems span the fundamental Arrow-Debreu framework
underlying financial models of complete markets and subsequently mathematical systems
departing from this framework but yet generalizing their approach to dynamic financial models.
Explicitly models based on fractional calculus on persistence (short memory) and on
entropy-based non-extensiveness. Applications of these models are used to define a modeling
approach to incomplete financial models and their potential use as a measure of incompleteness.
Subsequently Bianchi and Pianese provide an extensive overview of multi-fractional models and
their important applications to Asset price modeling. Finally Tapiero and Jinquyi consider the
binomial pricing model by discussing the effects of memory on the pricing of asset prices.
