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Sovereign Credit Risk in Saudi Arabia, Morocco and Egypt

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  • Amira Abid

    (Laboratory of Probability and Statistics, Faculty of Business and Economic Sciences, University of Sfax, Sfax 3029, Tunisia)

  • Fathi Abid

    (Laboratory of Probability and Statistics, Faculty of Business and Economic Sciences, University of Sfax, Sfax 3029, Tunisia)

Abstract

The purpose of this paper is to assess and predict sovereign credit risk for Egypt, Morroco and Saudi Arabia using credit default swap (CDS) spreads obtained from the DataStream database for the period from 2009 to 2022. Our approach consists of generating the implied default probability and the corresponding credit rating in order to estimate the term structure of the implied default probability using the Nelson–Siegel model. In order to validate the prediction from the probability term structure, we calculate the transition matrices based on the implied rating using the homogeneous Markov model. The main results show that, overall, the probabilities of defaulting in the long term are higher than those in the short term, which implies that the future outlook is more pessimistic given the events that occurred during the study period. Egypt seems to be the country with the most fragile economy, especially after 2009, likely because of the political events that marked the country at that time. The economies of Morocco and Saudi Arabia are more resilient in terms of both default probability and credit rating. These findings can help policymakers develop targeted strategies to mitigate economic risks and enhance stability, and they provide investors with valuable insights for managing long-term investment risks in these countries.

Suggested Citation

  • Amira Abid & Fathi Abid, 2024. "Sovereign Credit Risk in Saudi Arabia, Morocco and Egypt," JRFM, MDPI, vol. 17(7), pages 1-20, July.
  • Handle: RePEc:gam:jjrfmx:v:17:y:2024:i:7:p:283-:d:1429286
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    References listed on IDEAS

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    1. Frydman, Halina & Schuermann, Til, 2008. "Credit rating dynamics and Markov mixture models," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1062-1075, June.
    2. João F. Caldeira & Guilherme V. Moura & , Fabricio Tourrucôo, 2016. "Forecasting the yield curve with the arbitrage-free dynamic Nelson-Siegel model: Brazilian evidence," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(2), pages 221-237.
    3. Alessio Piccolo & Joel Shapiro, 2022. "Credit Ratings and Market Information," The Review of Financial Studies, Society for Financial Studies, vol. 35(10), pages 4425-4473.
    4. Hull, John & Predescu, Mirela & White, Alan, 2004. "The relationship between credit default swap spreads, bond yields, and credit rating announcements," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2789-2811, November.
    5. Jacob Muvingi & Takudzwa Kwinjo, 2014. "Estimation of Term Structures using Nelson-Siegel and Nelson-Siegel-Svensson: A Case of a Zimbabwean Bank," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 4(6), pages 1-9.
    6. Jens Hilscher & Mungo Wilson, 2017. "Credit Ratings and Credit Risk: Is One Measure Enough?," Management Science, INFORMS, vol. 63(10), pages 3414-3437, October.
    7. Francis A. Longstaff & Jun Pan & Lasse H. Pedersen & Kenneth J. Singleton, 2011. "How Sovereign Is Sovereign Credit Risk?," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 75-103, April.
    8. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
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