The Role of Machine Learning in Transforming Financial Market Analytics and Algorithmic Trading
Authors:-Mohammed Omer
Abstract-:Machine learning (ML) has revolutionized financial market analytics and algorithmic trading by enabling data-driven decision-making, enhancing predictive accuracy, and automating complex processes. This review explores ML’s transformative role across key areas, including fraud detection, risk management, high-frequency trading, and sentiment analysis. By analyzing historical data and identifying non-linear patterns, ML models outperform traditional statistical methods, offering insights into market trends, asset pricing, and portfolio optimization. However, challenges such as data quality, model interpretability, and regulatory compliance persist. The integration of reinforcement learning, deep neural networks, and alternative data sources underscores ML’s potential to reshape financial ecosystems, though ethical considerations and systemic risks require vigilant oversight. This article synthesizes advancements, applications, and future directions, emphasizing ML’s capacity to balance innovation with stability in global markets.
