Discriminant Analysis of Default Risk
by Aker Aragon of CARIFIN
October 21, 2004
Abstract: The present work intends to propose a way to get prediction functions on the defaults of companies, based on discriminant scores. The use of the Multivariate Discriminant Analysis (MDA), applied to the quantification of the bankruptcy and default risk, has been replaced in the last few years by other techniques such as the logistical regression, because of the necessary normality and homoskedasticity required when the MDA is applied.
However, the objective of this work is to show and suggest a way to determine reliable equations based on MDA, provided that the attainment of such equations is previously supported by non-parametric techniques in the process of variables selection, and by box-cox transformations in order to get the normality of the indicators. The use of Principal Components Analysis is also proposed, in order to avoid the multicollinearity or interrelation of the explicative variables, generally present in the financial ratios and often not taken into account.
In summary, the application of these techniques shows a very reliable way to get probabilities of default of the companies, based on ratios and other financial indicators.
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