AI-Driven Financial Market Dynamics and Cross-Market Spillovers: A Comparative Research Framework for Emerging and Developed Stock Markets and Sustainable Development

Financial integration has risen and shocks are increasingly transmitted to and from emerging other developed stock markets around the globe. Previous literature is also disjointed in the fields of AI-based prediction, nonlinear market dynamics, cross-market spillovers, financial contagion, sustainability issues and AI. This study proposes an AI/ML-powered research platform that integrates AI/ML with market, macroeconomic, volatility, liquidity, sentiment and sustainability variables including the ESG, green finance and carbon markets and climate related risks, to model financial market dynamics and cross market spillovers. Eight significant gaps were found in the reviewed research thriving the methodology, cross-asset analysis, sustainability, nonlinear modelling, explainability, crisis prediction, SDG integrability and overall. Seven testable hypotheses are formulated and used to direct further empirical research. This framework can be used to aid investors, portfolio managers, financial institutions, regulators and policymakers in predictivity, contagion risk identification, risk management and sustainable financial decision making.