Modern Innovations in Statistical Methods for Risk-Return Estimation

• Data acquisition
• Imputing missing data 
• Shrinkage procedures for expected return and risk estimates
• Bayesian procedures for incorporating forecasts
• Resolving inconsistent risk estimates

Portfolio Construction Under Uncertainty

• The effect of uncertainty on optimization
• Michaud optimization – the Resampled Efficient Frontier
• Optimization sensitivity to inputs
• Understanding the role and impact of constraints 
• Using post-optimization investability constraints
• Optimizing for different objectives: benchmark relative, long-short or liability-based objectives

Portfolio Monitoring and Rebalancing

• Deficiencies of conventional rebalancing practice
• Advantages of a statistical test for rebalancing
• The Michaud-Esch rebalance test
• Calibrating a rebalance test for expected portfolio drift
• Calculating confidence bounds on asset weights

Cost-Efficient Trading Using Optimization Techniques

• The turnover-tracking error tradeoff and quadratic programming
• Minimizing transaction costs
• Special uses – favoring one asset over others for trading