Aim and Scope

AI, Big Data and Quantitative Methods in Finance (ABQ) covers theoretical and empirical research in finance that applies artificial intelligence, big data analytics, and advanced quantitative methods. The journal welcomes studies within, but not limited to, the following areas:

• Artificial intelligence and machine learning applications in finance
• Big data analytics for financial decision-making
• Quantitative finance and financial modeling
• Econometrics and statistical analysis in finance
• Risk management, credit risk, and financial stability analysis
• Financial technology (FinTech), digital banking, and blockchain analytics
• Algorithmic trading, portfolio optimization, and asset pricing
• Corporate finance analytics and performance measurement
• Behavioral finance using quantitative and data-driven approaches
• Forecasting, simulation, and optimization methods in financial research
• ABQ prioritizes rigorous methodologies, innovative analytical frameworks, and practical implications that contribute to the advancement of financial theory, policy, and practice in the digital era.