Prediction of Corporate Recovery in Malaysia

Abstract

Using data from Malaysia, we investigate prediction of recovery by distressed companies, during the period 2003-2016. We use logistic regressions to estimate versions of traditional recovery prediction models, augmented with indicators of distress severity and regularization plan type. The financial indicators are industry-adjusted. The results support our hypotheses, indicating that recovery is more likely if distress is diagnosed at early stages and if an operational versus strategic recovery plan is followed.