Ratings of Sovereign Risk and the Macroeconomics Fundamentals of the countries: a Study Using Artificial Neural Networks

Bruno Frascaroli (), Luciano da Costa Silva () and Osvaldo Candido
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Luciano da Costa Silva: Universidade Federal da Paraíba

Brazilian Review of Finance, 2009, vol. 7, issue 1, 73-106

Abstract: To minimize the consequences of asymmetric information, the sovereign risk ratings are instruments that constitute a key piece in the determination of credit market conditions, essential to the growth of developing countries like Brazil. In the present work we studied based on macroeconomics foundations, a classification to sovereign risk ratings realized by the ratings agencies finding the classification using Artificial Neural Networks. We observed homogeneity degree between the attributions of agencies and macroeconomics foundations in the countries of sample which four of foundations seem to be more directly connected with these attributions. After, in a comparative static exercise, we use the model to make simulations of sceneries of the credit external conditions for the Brazilian economy, changing the macroeconomics foundations which we noted that agencies expected for more per capita income increasing and decrease of public debt.

Keywords: sovereign risk rating; macroeconomics foundations; arti cial neural networks. (search for similar items in EconPapers)
JEL-codes: C45 E44 G14 (search for similar items in EconPapers)
Date: 2009
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