Artificial Intelligence and Machine Learning in Investment Strategies

Machine Learning for Investing --- This course covers quantitative approaches to using firm information to develop profitable trading strategies. Students will learn to apply a variety of machine learning techniques to multiple financial data sources in order to investigate and validate the out-of-sample performance of investment strategies. Machine learning techniques include ordinary least squares regression, penalized regression, decision trees (including random forest and gradient boosting) and neural networks. Examples of financial data include analyst earnings forecasts, prices and volume, insider ownership and sentiment scores.