Dissertação (mestrado)—Universidade de Brasília, Departamento de Economia, 2011. / Submitted by Shayane Marques Zica (marquacizh@uol.com.br) on 2011-09-12T20:34:16Z No. of bitstreams: 1 2011_RodrigoCaldasGonçalves.pdf: 805939 bytes, checksum: 362aab0bea917f3c353b5ea5c9f18b29 (MD5) / Approved for entry into archive by LUCIANA SETUBAL MARQUES DA SILVA(lucianasetubal@bce.unb.br) on 2011-09-20T15:04:47Z (GMT) No. of bitstreams: 1 2011_RodrigoCaldasGonçalves.pdf: 805939 bytes, checksum: 362aab0bea917f3c353b5ea5c9f18b29 (MD5) / Made available in DSpace on 2011-09-20T15:04:47Z (GMT). No. of bitstreams: 1 2011_RodrigoCaldasGonçalves.pdf: 805939 bytes, checksum: 362aab0bea917f3c353b5ea5c9f18b29 (MD5) / Este trabalho aborda o modelo de precificação do CDS de emissões soberanas, proposto por Remolona in ‘A Ratings Based Approach to Measuring Sovereign Risk’ (International Journal of Finance and Economics, vol. 13, issue 1, 26-39) como forma de evidenciar parcelas do risco soberano não amparadas pela perda esperada, calculada de acordo com o rating soberano dos emissores, originando o que a literatura acadêmica chama de Credit Spread Puzzle. Foi avaliado o modelo para CDS com maturidades de 2, 3, 5, 7 e 10 anos, para grupos de 7 e 8 países emergentes, incluindo-se sempre o Brasil, considerando os períodos entre janeiro de 2002 e junho de 2006, e janeiro de 2002 e junho de 2010, utilizando para tal regressões em painel. Complementarmente, foram realizadas regressões lineares individuais pelo método OLS de 12 países, sendo 10 emergentes e 2 da zona do Euro que atualmente enfrentam problemas em relação à gestão de suas dívidas externas. Foi também avaliado o comportamento do indicador de Volatilidade VIX, elaborado pela Chicago Board of Options Exchange, e as implicações que possui na formação do CDS. Com base em dados de expectativas de perdas de todos os países, calculado com base no rating individual divulgado pela agência de classificação de Risco Moody’s, e nos CDS dos diversos países analisados, foi calculada individualmente a parcela de prêmio decorrente de perdas inesperadas, ou prêmio de risco, e feita análise comparativa com o prêmio de risco brasileiro. Os resultados mostraram que o modelo proposto por Remolona sofreu forte influência da crise subprime ocorrida entre 2008 e 2009, o que mudou os parâmetros dos coeficientes da regressão em painel, sem, no entanto, invalidar o modelo. Foi constatado que existem restrições para aplicação do modelo aos CDS individualmente, não sendo confiável sua utilização sem adaptações. Foi constatada a existência de autocorrelação de resíduos, demonstrando que existem fatores que não foram incluídos na modelagem. Em relação à análise de prêmios, constatou-se que o Brasil, se comparado aos demais países avaliados, vem apresentando significativas melhoras na taxa de CDS, além de ter apresentado perdas menores em razão da crise do subprime, principalmente nas maturidades de 2, 3 e 5 anos, indicando uma incompatibilidade entre as perdas esperadas, e consequentemente a classificação de risco atribuída, e a precificação feita pelo mercado, sendo que muitas vezes a última apresentou valor inferior à precificação esperada. _______________________________________________________________________________ ABSTRACT / This paper discusses the model for pricing sovereign CDS emissions proposed by Remolona in 'A Ratings Based Approach to Measuring Sovereign Risk' (International Journal of Finance and Economics, vol. 13, issue 1, 26-39) as a way of showing portions of sovereign risk is not supported by the expected loss calculated in accordance with the sovereign rating of the issuers, resulting in what the academic literature calls the Credit Spread Puzzle. We evaluated the model for CDS with maturities of 2, 3, 5, 7 and 10 years, for groups of 7 and 8 developing countries, always including Brazil, considering the periods between January 2002 and June 2006 and January 2002 and June 2010, using such panel regressions. In addition, individual linear regressions were performed by OLS from 12 countries, 10 emerging and 2 of the Eurozone which currently face problems in relation to the management of foreign debts. It was also rated the behavior of the VIX volatility indicator, developed by the Chicago Board of Options Exchange, and the implications it has on the formation of the CDS. Based on data from expected losses of all countries, calculated on the basis of individual rating issued by rating agency Moody's, and the CDS of the analyzed countries, was calculated individually to share premium arising from unexpected losses, or premium risk, and made comparison with the Brazilian risk premium. The results showed that the model proposed by Remolona was strongly influenced by the subprime crisis that occurred between 2008 and 2009, which changed the parameters of the regression coefficients in the panel, without, however, invalidate the model. It was noted that restrictions apply to individual CDS, its use is not reliable without adaptations. It has been found the existence of autocorrelation of residues, demonstrating that there are factors that were not included in the modeling. On the analysis of premiums, it was found that Brazil, as compared to other countries evaluated, has shown significant improvements in the rate of CDS, and also presented lower losses due to subprime crisis, primarily with maturities of 2, 3 and 5 years, indicating a mismatch between the expected losses, and consequently the risk ratings assigned, and pricing by the market, and often the latter showed a value below the expected pricing.

Credit spread is the extra risk-reward that an investor is bearing for investing in corporate bonds instead of government bonds. Structural models, which are simple in their framework, fail to explain the occurring credit spread and underestimate the predicted credit spread. Hence, the need for new models and exploration of systematic and idiosyncratic variables arose. The present paper aims to investigate if the predictability of lower-medium investment grade bonds and non-investment grade bonds credit spread can be improved by incorporating systematic and idiosyncratic variables into a fixed effect panel data regression model, and whether the selected variables’ significance has high influence on credit spread or not. Initial results showed that fixed effect panel data regression model underperforms the structural models and under predicts the actual credit spread. The applied model explained 13.5% of the lower-medium investment grade bonds credit spread and 8.5% of non-investment grade bonds. Further, systematic variables have higher influence on lower-medium investment grade bonds and idiosyncratic variables have higher influence on non-investment grade bonds. The predictability of credit spread can be improved by employing correct explanatory variables which are selected based on the characteristics of the sample size.