CFRM 543: Portfolio Optimization and Asset Management

The topics to be covered are listed below.  On average one lecture will be devoted to each topic. The content coverage will blend theory and methods with computing using R and R packages. 

  • Mean-variance optimization (MVO) theoretical foundations
  • Numerical MVO with box, group, turnover constraints and concentration penalties
  • Covariance matrix estimator methods:  shrinkage, robustness
  • Portfolio performance analysis and back-testing
  • Downside and tail risk measures, expected shortfall, coherent risk measures
  • Expected shortfall based portfolio optimization theory and computing
  • Expected utility and coherent risk measure portfolio optimization
  • Non-convex portfolio optimization: DE Optim and random portfolios
  • Active portfolio management and active management characterization
  • Information ratio and the fundamental law of active management
  • Time series factor model fitting, risk analysis and hedge funds applications
  • Fundamental factor model fitting, risk analysis and equity portfolio applications
  • Factor mimicking portfolios and factor investing
  • Marginal contributions to risk, risk-parity portfolios, equal weight portfolios
  • Bayes models and Bayes-Stein shrinkage estimator
  • Black-Litterman model and its calibration
  • Statistical factor models for portfolio optimization and risk analysis
  • Selected topics
R. Douglas Martin
Ang, Andrew (2014). Asset Management: A Systematic Approach to Factor Investing, Oxford University Press. / Draft chapters of Martin, Scherer and Yollin (2016). Post Modern Portfolio Optimization and Risk Analysis, to be provided by instructor.
R and PorfolioAnalytics, PerformanceAnalytics and FactorAnalytics packages
CFRM 541 Investment Science and CFRM 542 Financial Data Modeling and Analysis in R, or equivalents, or permission of instructor