MATH 614 Factor Models with Machine Learning
Introduction to factor models and key machine learning concepts for financial applications. Includes regression and principal-component factor models, factor analysis, neural networks, the kernel trick, and classification. All methods will be implemented in R or Python.
Prerequisite
Familiarity with multivariate calculus and some basic linear algebra will be assumed as well as some prior knowledge of undergraduate probability and statistics. The knowledge of various standard results concerning probability and statistics is assumed. If you are not familiar with these standard results, please contact the instructor as soon as possible