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Value-at-Risk for Country Risk Ratings

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  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)

  • Bernardo da Veiga

    (School of Economics and Finance, Curtin University of Technology)

  • Suhejla Hoti

    (Department of Treasury and Finance, Western Australia)

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 provides policy makers and industry stakeholders with a more accurate method of forecasting future changes in the risks and returns associated with country risk ratings.

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Bibliographic Info

Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-659.

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Length: 21 pages
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:tky:fseres:2009cf659

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  1. 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, 09.
  2. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February.
  3. 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.
  4. 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.
  5. Ashok Vir Bhatia, 2002. "Sovereign Credit Ratings Methodology," IMF Working Papers 02/170, International Monetary Fund.
  6. C. H. Furfine & Jeffery D. Amato, 2003. "Are credit ratings procyclical?," BIS Working Papers 129, Bank for International Settlements.
  7. Hoti, Suhejla, 2005. "Modelling country spillover effects in country risk ratings," Emerging Markets Review, Elsevier, vol. 6(4), pages 324-345, December.
  8. 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 841-62, November.
  9. 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.
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Cited by:
  1. San-Martín-Albizuri, Nerea & Rodríguez-Castellanos, Arturo, 2012. "Globalisation And The Unpredictability Of Crisis Episodes: An Empirical Analysis Of Country Risk Indexes / La Imprevisibilidad De Los Episodios De Crisis: Un Análisis Sobre Los Índices De Riesgo Pa�," Investigaciones Europeas de Dirección y Economía de la Empresa (IEDEE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), vol. 18(2), pages 148-155.
  2. 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.
  3. 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.
  4. 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.

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