...Fábio Henrique Sousa Coelho; Carlos Enrique Carrasco-Gutierrez; Mathias Schneid Tessmann Purpose This paper explores the effectiveness of machine learning algorithms in predicting sovereign credit ratings, benchmarking their performance against traditional linear and panel regression models...

...Thuy Tu Pham Purpose This study aims to investigate the key drivers of bank stability in Vietnam's emerging economy, offering a robust, data-driven framework that integrates advanced machine learning (ML), regularization techniques and explainable artificial intelligence (XAI) to address...

... Squares (RLS), Generalized Linear Model (GLM) and quantile regression – to capture linear effects, heterogeneity and distributional nuances. Complementing these, advanced Machine Learning (ML) methods – including Gradient Boosting Machine (GBM), bagging via Random Forest and an ensemble stacking model...

... of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode Agglomerative clustering CAPM Exploratory analysis Feature engineering K-means clustering Machine learning Our study focuses on examining how S&P Top 50 stocks cluster based on their risk and expected...

... the OECD countries between 1998 and 2018. Design/methodology/approach We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from...

..., an ensemble of machine learning. Design/methodology/approach Using quarterly observations over the period 2000–2021, the present research tests the reliability of the random forest technique for forecasting the Italian public debt. Findings The results show the large predictive power of this method...

... increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN. Design/methodology/approach A new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index. Findings...

...Christian Otchia; Simplice Asongu Purpose This study uses machine machine learning techniques to assess industrial development in Africa. Design/methodology/approach This study uses nightlight time data and machine learning techniques to assess industrial development in Africa. Findings...