Andrew O. Arnold
Machine Learning Research
(former Quantitative Portfolio Manager)
Ph.D., Machine Learning, Carnegie Mellon University (2009)
andrew.arnold AT gmail.com
This course introduces students to the topics of machine learning (ml) and natural language processing (nlp), in particular, as used to develop quantitative trading strategies. Students learn the mathematical fundamentals underlying many of the latest ml and nlp techniques (including deep neural networks, embeddings, and sentiment models), along with the basics of developing practical quantitative trading strategies based on these insights (such as quantifying the positive or negative sentiment of text, determining the relevance of text to particular stocks or classes of stocks, and the amount of novelty contained in textual content).