Rob Kaas – författare

Apart from standard actuarial theory, Modern Actuarial Risk Theory contains methods that are relevant for actuarial practice, for instance the rating of automobile insurance policies, premium principles and IBNR models, as well as generalized linear models with an eye on actuarial applications. Furthermore extensive introductions are given to credibility theory and ordering of risks. The book reflects the state of the art in actuarial risk theory. In addition to some chapters which are compatible with official material of actuarial education in North-America, Europe and other parts of the world, the book contains important material on topics that are relevant for recent insurance and actuarial developments including determining solvency measures, fair-value computations, reserving, ranking of risks, modelling dependencies and the use of generalized linear models. Basic ideas on risk measures in the framework of insurance premiums are also considered. The numerous exercises contained in Modern Actuarial Risk Theory, together with the hints for solving the more difficult ones and the numerical answers to many others, make the book useful as a textbook. Some important practical paradigms in insurance are presented in a way that is appealing to actuaries in their daily business. The mathematical background assumed is on a level such as acquired in the first stage of a bachelors program in quantitative economics or mathematical statistics.

The increasing complexity of insurance and reinsurance products has seen a growing interest amongst actuaries in the modelling of dependent risks. For efficient risk management, actuaries need to be able to answer fundamental questions such as: Is the correlation structure dangerous? And, if yes, to what extent? Therefore tools to quantify, compare, and model the strength of dependence between different risks are vital. Combining coverage of stochastic order and risk measure theories with the basics of risk management and stochastic dependence, this book provides an essential guide to managing modern financial risk.* Describes how to model risks in incomplete markets, emphasising insurance risks.* Explains how to measure and compare the danger of risks, model their interactions, and measure the strength of their association.* Examines the type of dependence induced by GLM-based credibility models, the bounds on functions of dependent risks, and probabilistic distances between actuarial models.* Detailed presentation of risk measures, stochastic orderings, copula models, dependence concepts and dependence orderings.* Includes numerous exercises allowing a cementing of the concepts by all levels of readers.* Solutions to tasks as well as further examples and exercises can be found on a supporting website. An invaluable reference for both academics and practitioners alike, Actuarial Theory for Dependent Risks will appeal to all those eager to master the up-to-date modelling tools for dependent risks. The inclusion of exercises and practical examples makes the book suitable for advanced courses on risk management in incomplete markets. Traders looking for practical advice on insurance markets will also find much of interest.

The increasing complexity of insurance and reinsurance products has seen a growing interest amongst actuaries in the modelling of dependent risks. For efficient risk management, actuaries need to be able to answer fundamental questions such as: Is the correlation structure dangerous? And, if yes, to what extent? Therefore tools to quantify, compare, and model the strength of dependence between different risks are vital. Combining coverage of stochastic order and risk measure theories with the basics of risk management and stochastic dependence, this book provides an essential guide to managing modern financial risk. * Describes how to model risks in incomplete markets, emphasising insurance risks. * Explains how to measure and compare the danger of risks, model their interactions, and measure the strength of their association. * Examines the type of dependence induced by GLM-based credibility models, the bounds on functions of dependent risks, and probabilistic distances between actuarial models. * Detailed presentation of risk measures, stochastic orderings, copula models, dependence concepts and dependence orderings. * Includes numerous exercises allowing a cementing of the concepts by all levels of readers. * Solutions to tasks as well as further examples and exercises can be found on a supporting website. An invaluable reference for both academics and practitioners alike, Actuarial Theory for Dependent Risks will appeal to all those eager to master the up-to-date modelling tools for dependent risks. The inclusion of exercises and practical examples makes the book suitable for advanced courses on risk management in incomplete markets. Traders looking for practical advice on insurance markets will also find much of interest.

Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and much expanded edition emphasizes the implementation of these techniques through the use of R. This free but incredibly powerful software is rapidly developing into the de facto standard for statistical computation, not just in academic circles but also in practice. With R, one can do simulations, find maximum likelihood estimators, compute distributions by inverting transforms, and much more.