Abstract
This paper examines credit risk in the European automotive industry. Distance to Default (DD) is calculated using the Merton structural credit model. In addition, we modify the Merton model to generate an innovative measure of credit risk at the extremes of the asset value fluctuations distribution, which we call Conditional Distance to Default (CDD). The credit risk of all listed automotive stocks on the S&P Euro Index is compared to all the other industries on this index, which comprises 180 stocks with geographic and sectoral diversity. The study spans the 10 years from 2000 to 2009 divided into pre-GFC and GFC periods. Our metrics find the automotive industry to be of high risk relative to other European industries, particularly during the GFC. We also find that our CDD metric is better able to capture the extreme credit risk prevalent in the industry during the GFC than traditional DD metrics.
| Original language | English |
|---|---|
| Pages (from-to) | 22-37 |
| Number of pages | 16 |
| Journal | International review of business research papers |
| Volume | 9 |
| Issue number | 1 |
| Publication status | Published - Jan 2013 |
| Externally published | Yes |
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Cite this
Allen, D. E., Kramadibrata, A. R., Powell, R. J., & Singh, A. (2013). Default risk in the European automotive industry. International review of business research papers, 9(1), 22-37.