Evaluating the default probabilities of the automotive industry using EBIT-based structural models

• Autor(a) principal: Elhanaoui, Azeddine
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.14/29145
• topic: Sturtural model; EBIT; Automotive industry; Default; Probability fixed cost; Domínio/Área Científica::Ciências Sociais::Economia e Gestão

This thesis implements the static EBIT-Based structural model proposed by Goldstein, Ju, & Leland (2001) to compute the default probabilities of 17 firms from the automotive industry. Following other papers (e.g. Eisdorfer, Goyal, & Zhdanov (2019)), this thesis also adapts our base model for the possibility of non-financial fixed costs, which are proxied by SG&A. The before mentioned models are calibrated using the Vassalou and Xing (2004) iterative approach, first used to calibrate the Merton (1974) model. The algorithm was adapted for the case with corporate payouts. Using a sample period of 12 years, this thesis shows how the default probabilities fluctuate across time in different geographies. The static Goldstein, Ju, & Leland (2001) leads to an average 5-year default probability of 2.38%. In contrast, the newly prosed model with fixed costs proxied by SG&A leads to an average 5-year default probability of 15.46%. Comparing these results with credit rating implied default probabilities of 3.42% shows that the later model’s estimates are high. This thesis concludes that, though widely used in the literature, the use of SG&A as a proxy for fixed costs leads to seemingly unreasonable high default probabilities. Its use as a proxy for fixed non-financial costs is thus questionable.