Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.14/15384
Título: Assessing default risk of a public company : an empirical analysis on the basis of Volkswagen AG
Autor: Thimm, Alexander
Orientador: Shackleton, Mark
Data de Defesa: 26-Fev-2014
Resumo: The outbreak of the financial crisis brought credit default risk back to the minds of investors. It is the most important risk for debtholders and there is no ideal way given by legislation in how to assess it. Several different approaches evolved over time like ratio analysis, structural or reduced form models. They all have in common that they try to predict at least bankruptcy probability and some further attempt to give an indication about how to price it. Besides that non-quantitative measures such as market-, peer- or economic analysis are taken into consideration. In order to evaluate performance of these models but credit default risk in general, Volkswagen AG, the German car manufacturer is chosen. It is on its way to become the world’s largest carmaker and offers a long history for examinations. By applying different models to VW’s case, results have shown that single ratios are superior to all other models evaluated. Structural models have strengths and weaknesses over time due to their assumptions and multi-ratio models’ performance is the worst. VW would have been bankrupt several times according to their predictions. Nevertheless the other models pointed out that VW’s credit worthiness recently improved and market expects it to continue. Therefore investing in VW’s credit risk seems a reasonable decision for investors. I would like to thank Martin Amann for his helpful advice regarding rating agencies and their methodology in assessing credit risk, my former colleagues Matthias Kreie and Konrad Kleinfeld for their support regarding VW’s bond time series and credit reports, and my brother for his advice and the discussions about the dissertation. Moreover I am very grateful to my supervisor Mark Shackleton for all his support.
URI: http://hdl.handle.net/10400.14/15384
Aparece nas colecções:FCEE - Dissertações de Mestrado / Master Dissertations
R - Dissertações de Mestrado / Master Dissertations

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