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Initial and Final Backward and Forward Discrete Time Non-homogeneous Semi-Markov Credit Risk Models

Author

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  • Guglielmo D’Amico

    (Universitá “G. D’Annunzio”)

  • Jacques Janssen

    (Université de Bretagne Occidentale)

  • Raimondo Manca

    (Universitá “La Sapienza” di Roma)

Abstract

In this paper we show how it is possible to construct an efficient Migration models in the study of credit risk problems presented in Jarrow et al. (Rev Financ Stud 10:481–523, 1997) with Markov environment. Recently it was introduced the semi-Markov process in the migration models (D’Amico et al. Decis Econ Finan 28:79–93, 2005a). The introduction of semi-Markov processes permits to overtake some of the Markov constraints given by the dependence of transition probabilities on the duration into a rating category. In this paper, it is shown how it is possible to take into account simultaneously backward and forward processes at beginning and at the end of the time in which the credit risk model is observed. With such a generalization, it is possible to consider what happens inside the time after the first transition and before the last transition where the problem is studied. This paper generalizes other papers presented before. The model is presented in a discrete time environment.

Suggested Citation

  • Guglielmo D’Amico & Jacques Janssen & Raimondo Manca, 2010. "Initial and Final Backward and Forward Discrete Time Non-homogeneous Semi-Markov Credit Risk Models," Methodology and Computing in Applied Probability, Springer, vol. 12(2), pages 215-225, June.
    • Handle: RePEc:spr:metcap:v:12:y:2010:i:2:d:10.1007_s11009-009-9142-6
    DOI: 10.1007/s11009-009-9142-6
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    References listed on IDEAS

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    1. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    2. Robert A. Jarrow & David Lando & Stuart M. Turnbull, 2008. "A Markov Model for the Term Structure of Credit Risk Spreads," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 18, pages 411-453, World Scientific Publishing Co. Pte. Ltd..
    3. Guglielmo D'Amico & Jacques Janssen & Raimondo Manca, 2009. "The Dynamic Behaviour of Non-Homogeneous Single-Unireducible Markov and Semi-Markov Chains," Lecture Notes in Economics and Mathematical Systems, in: Ahmad K. Naimzada & Silvana Stefani & Anna Torriero (ed.), Networks, Topology and Dynamics, pages 195-211, Springer.
    4. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
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    Citations

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    Cited by:

    1. Guglielmo D’Amico & Jacques Janssen & Raimondo Manca, 2011. "Discrete Time Non-Homogeneous Semi-Markov Reliability Transition Credit Risk Models and the Default Distribution Functions," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 465-481, November.
    2. Guglielmo D'Amico & Raimondo Manca & Giovanni Salvi, 2011. "Bivariate Semi-Markov Process for Counterparty Credit Risk," Papers 1112.0226, arXiv.org, revised Oct 2012.
    3. Brecht Verbeken & Marie-Anne Guerry, 2021. "Discrete Time Hybrid Semi-Markov Models in Manpower Planning," Mathematics, MDPI, vol. 9(14), pages 1-13, July.
    4. Guglielmo D’Amico & Giuseppe Di Biase & Raimondo Manca, 2011. "A customer’s utility measure based on the reliability of multi-state systems," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 34(1), pages 1-20, May.
    5. Hunt, Julien & Devolder, Pierre, 2011. "Semi Markov regime switching interest rate models and minimal entropy measure," LIDAM Discussion Papers ISBA 2011010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Puneet Pasricha & Dharmaraja Selvamuthu & Guglielmo D’Amico & Raimondo Manca, 2020. "Portfolio optimization of credit risky bonds: a semi-Markov process approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-14, December.
    7. Vlad Stefan Barbu & Guglielmo D’Amico & Thomas Gkelsinis, 2021. "Sequential Interval Reliability for Discrete-Time Homogeneous Semi-Markov Repairable Systems," Mathematics, MDPI, vol. 9(16), pages 1-18, August.
    8. Guglielmo D’Amico & Montserrat Guillen & Raimondo Manca, 2012. "Discrete time Non-homogeneous Semi-Markov Processes applied to Models for Disability Insurance," Working Papers XREAP2012-05, Xarxa de Referència en Economia Aplicada (XREAP), revised Mar 2012.
    9. Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2019. "Risk Management of Pension Fund: A Model for Salary Evolution," IJFS, MDPI, vol. 7(3), pages 1-17, August.
    10. Hunt, Julien & Devolder, Pierre, 2011. "Semi-Markov regime switching interest rate models and minimal entropy measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3767-3781.
    11. P.-C.G. Vassiliou, 2020. "Non-Homogeneous Semi-Markov and Markov Renewal Processes and Change of Measure in Credit Risk," Mathematics, MDPI, vol. 9(1), pages 1-27, December.
    12. Guglielmo D’Amico, 2013. "A semi-Markov approach to the stock valuation problem," Annals of Finance, Springer, vol. 9(4), pages 589-610, November.
    13. Puneet Pasricha & Dharmaraja Selvamuthu, 2021. "A Markov regenerative process with recurrence time and its application," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-22, December.

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