Published Paper Details:

This research paper explores the evolving landscape of artificial intelligence (AI) in financial trading. As technological advancements continue to reshape the financial sector, AI-based trading methods have emerged as powerful tools for market analysis, prediction, and execution. This study investigates various AI algorithms employed in trading, including machine learning, deep learning, and natural language processing. Through a comprehensive review of existing literature and analysis of real-world case studies, we examine the efficacy of AI-based trading strategies compared to traditional methods. Our findings indicate that AI-driven approaches can significantly enhance trading performance, particularly in high-frequency trading and complex market environments. However, challenges such as data quality, model interpretability, and regulatory concerns persist. This research contributes to the growing body of knowledge on AI in finance and provides insights for both researchers and practitioners in the field.