Explaining the variation in CDS spreads using market and accounting-based volatility measures

• Autor(a) principal: Martinho, Bruno Miguel Vaz
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.14/42580
• topic: Credit default swaps; Asset volatility; Credit risk; Credit spreads; Volatilidade do ativo; Risco de crédito; Spread de crédito; Domínio/Área Científica::Ciências Sociais::Economia e Gestão

The objective of this thesis is to study whether introducing fundamental measures of volatility in a model already accounting for market-based volatility can contribute to better explain the variation in credit default swap spreads. The accounting-based measures of volatility considered are (i) volatility of the return on net operating assets and (ii) volatility in the dispersion in analysts’ forecasts of earnings per share. When only the market volatilities are modelled together, it produces a r-square of around 67.5%. When considering the market-based volatilities and the volatility of the return on net operating assets in the same model, the explanatory power increases to around 73.5%. In the instance where all the market-based volatilities, the volatility of the return on net operating assets, and volatility in the dispersion in analysts’ earnings forecasts are considered, there is a slight decrease in r-square to around 73.0%. The results suggest that accounting measures help increase the explanation of the variation in credit default swap spreads, however adding the volatility in the dispersion in analysts’ forecasts of earnings, as a second accounting-based measure, does not add any explanatory power to the model. In further robustness tests, all volatilities measures are untouched except the return on net operating assets, which is replaced firstly by return on assets and secondly by return on equity. The robustness test results fall in line with the original findings. This corroborates that the analysis of credit default swaps can be increased by introducing accounting-based information into the models.