We compare the ability of ordered choice models and support vector machines to model and predict international bank ratings. Although support vector machines can identify significant determinants we argue that ordered choice models are more reliable for this. Our findings suggest that ratings reflect a bank's financial position, the timing of rating assignment and a bank's country of origin. Accounting for country effects substantially improves predictive performance. We find that support vector machines can produce considerably better predictions of international bank ratings than ordered choice models due to the formers ability to estimate a large number of country dummies unrestrictedly. (C) 2010 Elsevier Ltd. All rights reserved.
|Number of pages||9|
|Journal||Expert Systems with Applications|
|Publication status||Published - Apr 2011|