Predicting Bankruptcy with Robust Logistic Regression

Using financial ratio data from 2006 and 2007, this study uses a three-fold cross validation scheme to compare the classification pre diction of bankrupt firms by robust logistic regression with Bianco Yohai (BY) estimator versus maximum likelihood (ML) regression. With both 2007 data, BY improves in training set prediction testing set. In an out sample test, correctly predicts bankruptcy for Lehman Brothers; however, ML never Brothers either or data. Our analysis indicates that if significantly changes estimated coefficients regression, then method can improve firms. At worst, makes no has same results as This is strong evidence should be used robustness check on difference exists, primary classifier.