16:642:622 and 16:960:563, or an equivalent graduate course on regression analysis. The course will introduce discuss quantitative portfolio theory and related topics. It will begin with classical Markowitz theory and related analytics in a variety of real-world contexts - constrained optimization, benchmark/active optimization, risk-managed, etc. Following this, topics will include Bayesian mathematics, Black-Litterman, parameter estimation, and alternative risk measures. A heavy emphasis will be placed on programming and analytics; students will construct and manage their own portfolios under a variety of assumptions. Applications discussed during the course are implemented in MATLAB (see software section below).