Guglielmo D’Amico & Giuseppe Di Biase 
Semi-Markov Migration Models for Credit Risk 

Credit risk is one of the most important contemporary problems for banks and insurance companies. Indeed, for banks, more than forty percent of the equities are necessary to cover this risk. Though this problem is studied by large rating agencies with substantial economic, social and financial tools, building stochastic models is nevertheless necessary to complete this descriptive orientation.
This book presents a complete presentation of such a category of models using homogeneous and non-homogeneous semi-Markov processes developed by the authors in several recent papers. This approach provides a good method of evaluating the default risk and the classical Va R indicators used for Solvency II and Basel III governance rules.

This book is the first to present a complete semi-Markov treatment of credit risk while also insisting on the practical use of the models presented here, including numerical aspects, so that this book is not only useful for scientific research but also to managers working in this field for banks, insurance companies, pension funds and other financial institutions.

Tabella dei contenuti

Chapter 1. Credit risk problem
Chapter 2. Semi-Markov processes credit risk models
Chapter 3. Recurrence time HSMP and NHSMP: credit risk applications
Chapter 4. Backward and recurrence time HSMP and NHSMP credit risk models
Chapter 5. 5 Initial and Final Backward time HSMP and NHSMP credit risk models
Chapter 6. Mono-unireducible Markov and semi-Markov processes
Chapter 7. Non-homogeneous reward semi-Markov credit spread model
Chapter 8. NHSMP model for the evaluation of credit default swap
Chapter 9. Bivariate semi-Markov processes and related reward processes
Chapter 10. Semi-Markov credit risk simulation models

Circa l’autore

Guglielmo D’Amico, ‘G. d’Annunzio’ University of Chieti-Pescara, Italy.

Giuseppe Di Biase, ‘G. d’Annunzio’ University of Chieti-Pescara, Italy.

Jacques Janssen, Solvay Brussels School of Economics and Management, Belgium.

Raimondo Manca, University of Rome ‘La Sapienza’, Italy.