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A portfolio optimisation model for credit risky bonds with Markov model credit rating dynamics

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  • Arti Singh
  • Selvamuthu Dharmaraja

Abstract

In this paper, a credit risk optimisation model for the portfolio of credit risky bonds with l&#infin;-norm risk measure is proposed. The proposed model is formulated as a linear programming problem which makes it computationally efficient for the portfolio of large size. The rates of returns of the bonds are the input parameters of the proposed model and of the other portfolio optimisation models which are considered for the comparison with the former. The complete approach of generating rate of returns of the bonds, given their initial credit ratings and transition probability matrices, is presented. The time homogeneous discrete time Markov chain model is assumed for the credit rating dynamics of bonds. With extensive numerical illustrations, the proposed approach of obtaining rate of returns of the bonds is demonstrated. Furthermore, comparison of the proposed credit risk optimisation model with other inline existing portfolio optimisation models is performed.

Suggested Citation

  • Arti Singh & Selvamuthu Dharmaraja, 2017. "A portfolio optimisation model for credit risky bonds with Markov model credit rating dynamics," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 6(2), pages 102-119.
    • Handle: RePEc:ids:ijfmkd:v:6:y:2017:i:2:p:102-119
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    Cited by:

    1. 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.
    2. Dawen Yan & Xiaohui Zhang & Mingzheng Wang, 2021. "A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations," Annals of Operations Research, Springer, vol. 299(1), pages 659-710, April.

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