Traditional structural uncertainty analysis is mainly based on probability models and
requires the establishment of accurate parametric probability distribution functions using …

Although extremely flexible and obviously useful for many risk assessment problems, Monte
Carlo methods have four significant limitations that risk analysts should keep in mind.(1) Like …

This book provides the most comprehensive treatment of the theoretical concepts and
modelling techniques of quantitative risk management. Whether you are a financial risk …

Probabilistic uncertainty and imprecision in structural parameters and in environmental
conditions and loads are challenging phenomena in engineering analyses. They require …

Copula Methods in Finance is the first book to address the mathematics of copula functions
illustrated with finance applications. It explains copulas by means of applications to major …

Modern risk management calls for an understanding of stochastic dependence going
beyond simple linear correlation. This article deals with the static (nontime-dependent) case …

The increasing complexity of insurance and reinsurance products has seen a growing
interest amongst actuaries in the modelling of dependent risks. For efficient risk …

Uncertainty in the predictions of science when applied to the environment is an issue of
great current relevance in relation to the impacts of climate change, protecting against …

Real-world information is imperfect and is usually described in natural language (NL).
Moreover, this information is often partially reliable and a degree of reliability is also …

This book gives an introduction to basic concepts and methods in mathematical risk
analysis, in particular to those parts of risk theory which are of particular relevance in finance …