This talk explores the transformative role of machine learning (ML) in quantitative and algorithmic trading, highlighting its applications, opportunities, and challenges. We begin by introducing core ML concepts—supervised, unsupervised learning —and their relevance to financial markets. The discussion then covers practical applications, including predictive modeling for asset price movements, volume prediction and forecasting, Algo recommendations, clustering stock characteristics and applications in high-frequency trading strategies.
