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Comparative analysis of risk ratings for the East European region

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  • Hoti, Suhejla

Abstract

Following the aftermath of the 11 September 2001 events, the risks associated with engaging in international dealings have increased substantially, and become more difficult to analyse and predict for decision makers in the economic, financial and political sectors. The importance of country risk analysis is underscored by the existence of several prominent country risk rating agencies, which combine a wide range of qualitative and quantitative information regarding alternative measures of economic, financial and political risk into associated composite risk ratings. However, the accuracy of any rating agency with regard to any or all of these measures is open to question. For this reason, the paper provides a qualitative comparison of country risk rating systems used by seven leading rating agencies. The paper also provides a novel analysis of four risk ratings using univariate and multivariate volatility models for nine East European countries. These ratings are compiled by the International Country Risk Guide, which is the only risk rating agency to provide consistent monthly data for a large number of countries since 1984. The empirical results enable a comparative assessment of the conditional means and volatilities associated with county risk returns, defined as the rate of change in country risk ratings, across the nine East European countries. Moreover, the estimated constant conditional correlation coefficients provide useful information as to whether the countries are similar in terms of shocks to the four risk returns.

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  • 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.
  • Handle: RePEc:eee:matcom:v:68:y:2005:i:5:p:449-462
    DOI: 10.1016/j.matcom.2005.02.014
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    1. 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.
    2. Hoti, Suhejla, 2005. "Modelling country spillover effects in country risk ratings," Emerging Markets Review, Elsevier, vol. 6(4), pages 324-345, December.
    3. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2022. "Time and frequency spillovers between political risk and the stock returns of China's rare earths," Resources Policy, Elsevier, vol. 75(C).
    4. Qazi, Abroon & Simsekler, Mecit Can Emre, 2023. "Nexus between drivers of COVID-19 and country risks," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    5. 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.

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