Graphical Data Representation in Bankruptcy
Analysis
W. K. Hardle1, R. A. Moro2, and D. Schafer3
1 C.A.S.E., Humboldt-Universitat zu Berlin, Spandauer Str. 1, 10178 Berlin
[email protected]
2 C.A.S.E., Humboldt-Universitat zu Berlin, Spandauer Str. 1, 10178 Berlin and
German Institute for Economic Research, Konigin-Luise-Straβe 5, 14195 Berlin
[email protected]
3 German Institute for Economic Research, Konigin-Luise-Straβe 5, 14195 Berlin
[email protected]
Graphical data representation is an important tool for model selection in
bankruptcy analysis since the problem is highly non-linear and its numeri-
cal representation is much less transparent. In classical rating models a con-
venient representation of ratings in a closed form is possible reducing the
need for graphical tools. In contrast to that non-linear non-parametric mod-
els achieving better accuracy often rely on visualisation. We demonstrate an
application of visualisation techniques at different stages of corporate default
analysis based on Support Vector Machines (SVM). These stages are the se-
lection of variables (predictors), probability of default (PD) estimation and
the representation of PDs for two and higher dimensional models with colour
coding. It is at this stage when the selection of a proper colour scheme be-
comes essential for a correct visualisation of PDs. The mapping of scores into
PDs is done as a non-parametric regression with monotonisation. The SVM
learns a non-parametric score function that is, in its turn, non-parametrically
transformed into PDs. Since PDs cannot be represented in a closed form,
some other ways of displaying them must be found. Graphical tools give this
possibility.
Keywords: company rating, default probability, support vector machines,
colour coding
JEL classification: C14, G33, C45