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 . 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.
|Number of pages||10|
|Journal||Mathematics and Computers in Simulation|
|Publication status||Published - 2010|