Data Science for Financial Engineering

Catalog description

This is an on-line quantitative course especially geared toward Master of Science in Financial Engineering students. The course covers the statistical tools needed to model and estimate the joint dynamics of markets. Included are: - topics in multivariate statistics that are relevant for risk management and portfolio management - machine learning models as generalizations of linear factor models, omnipresent across finance - the connection between the estimation/calibration of machine learning models and classical and Bayesian econometrics - backtesting and model/estimation risk in the context of decision theory - distributional stress-testing for risk management and portfolio/business construction for portfolio management. The final exam may be administered on-line or in-person. | Prerequisite: Matriculation into a master or doctoral program