A. Hussain

Predicting Financial Distress: A Comparative Analysis of Explainable Machine Learning Models for Cross‐Market Bankruptcy Prediction

An adaptability–stability–interpretability framework for selecting bankruptcy prediction models under different institutional and market conditions is proposed and provides evidence that explainable ensemble and deep tabular models can recover economically meaningful distress signals across markets while differing in t...