This book aims to give a complete and self-contained presentation of semi- Markov models with finitely many states, in view of solving real life problems of risk management in three main fields: Finance, Insurance and Reliability providing a useful complement to our first book (Janssen and Manca (2006)) which gives a theoretical presentation of semi-Markov theory. However, to help assure the book is self-contained, the first three chapters provide a summary of the basic tools on semi-Markov theory that the reader will need to understand our presentation. For more details, we refer the reader to our first book (Janssen and Manca (2006)) whose notations, definitions and results have been used in these four first chapters. Nowadays, the potential for theoretical models to be used on real-life problems is severely limited if there are no good computer programs to process the relevant data. We therefore systematically propose the basic algorithms so that effective numerical results can be obtained. Another important feature of this book is its presentation of both homogeneous and non-homogeneous models. It is well known that the fundamental structure of many real-life problems is n- homogeneous in time, and the application of homogeneous models to such problems gives, in the best case, only approximated results or, in the worst case, nonsense results.
Inhaltsverzeichnis
Probability Tools For Stochastic Modelling. - Renewal Theory and Markov Chains. - Markov Renewal Processes, Semi-Markov Processes and Markov Random Walks. - Discrete Time and Reward Smp and their Numerical Treatment. - Semi-Markov Extensions of the Black-Scholes Model. - Other Semi-Markov Models in Finance and Insurance. - Insurance Risk Models. - Reliability and Credit Risk Models. - Generalised Non-Homogeneous Models for Pension Funds and Manpower Management.
