Exploring the Nexus among Innovation, Green Finance, and Banks’ Performance Using Machine Learning Models: International Evidence | ||
| المجلة العربية للإدارة | ||
| Articles in Press, Accepted Manuscript, Available Online from 06 November 2025 PDF (961.21 K) | ||
| Document Type: بحوث باللغة الإنجلیزیة | ||
| DOI: 10.21608/aja.2025.419629.1936 | ||
| Author | ||
| Myvel Nabil Ramsis* | ||
| Lecturer at Department of Business Administration, Faculty of Business, Ain Shams University, Cairo, Egypt. | ||
| Abstract | ||
| This study explores the nexus among innovation, green finance, and banks’ performance across 14 countries over 8 years using machine learning. It examines whether innovation and green finance influence banks’ performance, explores whether innovation moderates the relation between green finance and banks’ performance, and tests for cointegration among the components of the nexus. It uses a global innovation index as a proxy for innovation. Green finance has been measured by green bonds, while banks’ performance has been measured by capital adequacy, profitability, liquidity, and asset quality. The study conducts an empirical comparison between panel regression and machine learning approaches to pinpoint the most accurate and robust predictive approach. Python-based models were applied to contrast the predictive capabilities of different machine learning algorithms in forecasting key financial indicators. Using panel data with robust standard errors, the analysis reveals that green bonds have a significantly positive impact on capital adequacy, but a negative impact on asset quality in these markets. Results suggest that innovation positively impact profitability but negatively affect asset quality. Moreover, innovation plays a moderating role, exerting a negative influence on the relation between green bonds and capital adequacy, while positively moderating the relation between green bonds and asset quality. The Kao Residual Cointegration Test indicates a long-term nexus between the components. Support Vector Regression and K-Nearest Neighbors outperformed other approaches and are recommended for future financial predictions. Future research may extend this study by focusing on the effect of innovation on the firms’ financial performance across Arab countries. | ||
| Keywords | ||
| Advanced learning algorithms; Banks’ performance; Cointegration test; Emerging and developed Markets; Green finance; innovation; Python-based models | ||
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