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This book presents a selection of papers presented to the Second Inter- national Symposium on Semi-Markov Models: Theory and Applications held in Compiegne (France) in December 1998. This international meeting had the same aim as the first one held in Brussels in 1984 : to make, fourteen years later, the state of the art in the field of semi-Markov processes and their applications, bring together researchers in this field and also to stimulate fruitful discussions. The set of the subjects of the papers presented in Compiegne has a lot of similarities with the preceding Symposium; this shows that the main fields of semi-Markov processes are now well established particularly for basic applications in Reliability and Maintenance, Biomedicine, Queue- ing, Control processes and production. A growing field is the one of insurance and finance but this is not really a surprising fact as the problem of pricing derivative products represents now a crucial problem in economics and finance. For example, stochastic models can be applied to financial and insur- ance models as we have to evaluate the uncertainty of the future market behavior in order, firstly, to propose different measures for important risks such as the interest risk, the risk of default or the risk of catas- trophe and secondly, to describe how to act in order to optimize the situation in time. Recently, the concept of VaR (Value at Risk) was "e;discovered"e; in portfolio theory enlarging so the fundamental model of Markowitz.
This book is the result of the fourth International Symposium on Data Analysis held on June 1985 at the Universite Libre de Bruxelles with the help'of the European Institute for Advanced Management. As the preceding ones, the organization of the Symposium started with a call for real life problems from which an International Com mittee selected six topics and asked for several solutions. These topics are : I) Multivariate and longitudinal data on growing children 2) Prehistoric assemblages and lithic artifacts from a small We- european area 3) A comparison of results of European elections 4) Classification of heterogeneous data related to microcomputers 5) Group technology in production management 6) Juvenile gelinquency They are covered by the S1X chapters of this book in the following systematic way : a) firstly, a presentation of the problem is given in the original context of the relevant discipline (Medicine, archaelogy, politics, marketing, production and education); b) Secondly, we present the solution found by people who presents the problem; c) thirdly, we find the other retained solutions among the most significative ones; v vi PREFACE d) finally, a short conclusion compares the different approaches. The diversity of the six selected problems clearly shows that Data Analysis can be used for solving a wide variety of problems. Moreover, the fact that each problem is approached by several dif ferent way - at least two - also shows that, in general, a "univer sal" statistical method does not exist.
The aim of this book is to promote interaction between engineering, finance and insurance, as these three domains have many models and methods of solution in common for solving real-life problems. The authors point out the strict inter-relations that exist among the diffusion models used in engineering, finance and insurance.
This book provides a detailed study of Financial Mathematics. In addition to the extraordinary depth the book provides, it offers a study of the axiomatic approach that is ideally suited for analyzing financial problems.
After a presentation of the main probabilistic tools necessary for understanding of the book, the authors show how to apply semi-Markov processes in finance, starting from the axiomatic definition and continuing eventually to the most advanced financial tools.
Aims to give to the reader the tools necessary to apply semi-Markov processes in real-life problems. This book presents homogeneous and non-homogeneous semi-Markov processes, as well as Markov and semi-Markov rewards processes. It provides the reader knowledge of semi-Markov processes.
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