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Value-at-Risk for country risk ratings

Author

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  • McAleer, Michael
  • da Veiga, Bernardo
  • Hoti, Suhejla

Abstract

The country risk literature argues that country risk ratings have a direct impact on the cost of borrowings as they reflect the probability of debt default by a country. An improvement in country risk ratings, or country creditworthiness, will lower a country's cost of borrowing and debt servicing obligations, and vice versa. In this context, it is useful to analyse country risk ratings data, much like financial data, in terms of the time series patterns, as such an analysis would provide policy makers and the industry stakeholders with a more accurate method of forecasting future changes in the risks and returns of country risk ratings. This paper considered an extension of the Value-at-Risk (VaR) framework where both the upper and lower thresholds are considered. The purpose of the paper was to forecast the conditional variance and Country Risk Bounds (CRBs) for the rate of change of risk ratings for 10 countries. The conditional variance of composite risk returns for the 10 countries were forecasted using the Single Index (SI) and Portfolio Methods (PM) of McAleer and da Veiga [10,11]. The results suggested that the country risk ratings of Switzerland, Japan and Australia are much mode likely to remain close to current levels than the country risk ratings of Argentina, Brazil and Mexico. This type of analysis would be useful to lenders/investors evaluating the attractiveness of lending/investing in alternative countries.

Suggested Citation

  • McAleer, Michael & da Veiga, Bernardo & Hoti, Suhejla, 2011. "Value-at-Risk for country risk ratings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1454-1463.
  • Handle: RePEc:eee:matcom:v:81:y:2011:i:7:p:1454-1463
    DOI: 10.1016/j.matcom.2010.06.016
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    References listed on IDEAS

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    1. Hoti, Suhejla, 2005. "Modelling country spillover effects in country risk ratings," Emerging Markets Review, Elsevier, vol. 6(4), pages 324-345, December.
    2. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    3. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    4. C. H. Furfine & Jeffery D. Amato, 2003. "Are credit ratings procyclical?," BIS Working Papers 129, Bank for International Settlements.
    5. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
    6. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
    7. Mr. Ashok Vir Bhatia, 2002. "Sovereign Credit Ratings Methodology: An Evaluation," IMF Working Papers 2002/170, International Monetary Fund.
    8. Suhejla Hoti & Michael McAleer, 2004. "An Empirical Assessment of Country Risk Ratings and Associated Models," Journal of Economic Surveys, Wiley Blackwell, vol. 18(4), pages 539-588, September.
    9. Hoti, Suhejla, 2005. "Comparative analysis of risk ratings for the East European region," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 449-462.
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    Cited by:

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    2. Ledermann, Daniel & Alexander, Carol, 2012. "Further properties of random orthogonal matrix simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 83(C), pages 56-79.
    3. Abroon Qazi & Mecit Can Emre Simsekler, 2022. "Prioritizing interdependent drivers of financial, economic, and political risks using a data-driven probabilistic approach," Risk Management, Palgrave Macmillan, vol. 24(2), pages 164-185, June.
    4. Qazi, Abroon, 2023. "Exploring Global Competitiveness Index 4.0 through the lens of country risk," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Cristina Alina Naftanaila, 2012. "Rating Based on the Country Risk," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 2(2), pages 126-135, April.
    6. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.

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