Evolução da exposição ao risco de crédito: um estudo empírico do mercado brasileiro de debêntures entre 2014 e 2017

• Ano de defesa: 2018
• Autor(a) principal: Fontes, Jean Raphael da Silva de
• Orientador(a): Pessoa, Marcelo de Sales
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Risco de crédito; Debêntures; Spread de crédito; Crise econômica
• Palavras-chave em Inglês: Credit risk; Credit spread; Economic crisis
• Link de acesso: https://hdl.handle.net/10438/24304

The post-2008 financial crisis intensified and improved risk management around the world. From 2014 to 2017, Brazil experienced a severe period of economic crisis culminating in the largest recession in history in 2016. The objective of this work is to measure the impact of this crisis on the credit spread in the secondary market of debentures and the consequent probability of default implicit of these assets. The work analyzes the data of the private credit curve in Brazil for the AAA, AA and A Ratings published daily by ANBIMA based on Nelson and Siegel (1987) parametric model with revision proposed by Diebold and Li (2006). Based on these data, we extracted the daily probability of default implicit using the reduced form of the Duffie and Singleton model (1999) proposed by Xu and Nencioni (2000). This study seeks to identify the perception of agents of the credit market in relation to the increase of risk in the current Brazilian economic scenario. The study concluded that there was a significant increase in the credit spread to the apex in 2016, decreasing during 2017 with the more favorable economic scenario and the fall in interest rates. However, the model data showed high daily volatility. Regarding Probability of Default, there was a great evolution in the perception of credit risk by agents, but there was a certain delay in the pricing of this risk when compared to other economic indicators. In the comparison of the model data with the calculated default probability data for each individual asset, a large difference was observed between assets with the same rating level and the average of the model data. The data of this model can be used in future work to set up portfolios with a better return risk ratio, besides attesting the usefulness of this tool to the economic agents to price their operations and to fulfill their expectations.