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Semi-Markov Migration Models for Credit Risk


Semi-Markov Migration Models for Credit Risk


1. Aufl.

von: Guglielmo D'Amico, Giuseppe Di Biase, Jacques Janssen, Raimondo Manca

112,99 €

Verlag: Wiley-Iste
Format: EPUB
Veröffentl.: 01.06.2017
ISBN/EAN: 9781119415121
Sprache: englisch
Anzahl Seiten: 316

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

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

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