Machine Learning for Zombie Hunting: Predicting Distress from Firms' Accounts and Missing Values
用企业财务与缺失信息预测困境并识别僵尸企业
In this contribution, we propose machine learning techniques to predict zombie firms. First, we derive the risk of failure by training and testing our algorithms on disclosed financial information and non-random missing values of 304,906 firms active in Italy from 2008 to 2017. Then, we spot the highest financial distress conditional on predictions that lies above a threshold for which a combination of false positive rate (false prediction of firm failure) and false negative…