The Machine Learning for Asset Pricing Training Course by Sterling Finance Training Institute is a specialised programme designed to equip finance professionals, analysts, and researchers with the skills to apply modern machine learning techniques to asset pricing and financial modelling. This course combines the principles of finance and data science to provide a deep understanding of how advanced algorithms can improve pricing accuracy, risk prediction, and portfolio optimization. Participants will explore how machine learning can enhance traditional financial theories such as the Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT) to generate more robust and data-driven investment insights.
Through a practical and research-based learning approach, this course focuses on integrating risk premium estimation, predictive analytics, and statistical learning into asset valuation. Participants will gain hands-on experience with supervised and unsupervised learning models, including regression, neural networks, and ensemble methods, and learn how to implement them to analyse large-scale financial datasets. By the end of the training, learners will be proficient in using machine learning tools for forecasting asset returns, identifying mispriced securities, and quantifying systematic risk in various market environments.
