MODULE 1
Portfolio Optimization
Mean-variance optimization with real-world constraints. Transaction costs, turnover limits, and sector bounds.
- Quadratic programming
- Constraint specification
- cvxpy implementation
MODULE 2
Black-Litterman
Combining equilibrium returns with investor views. Prior construction, confidence calibration, and posterior optimization.
- Equilibrium prior
- View specification
- Uncertainty calibration
MODULE 3
Risk Parity
Equal risk contribution portfolios. Risk budgeting, inverse volatility weighting, and HRP alternatives.
- Risk contribution
- Marginal risk
- Hierarchical clustering
MODULE 4
Factor Models
Factor-based portfolio construction and risk decomposition. Fama-French, Barra, and custom factor frameworks.
- Factor extraction
- Factor timing
- Risk decomposition
MODULE 5
VaR & Expected Shortfall
Risk measurement for regulatory and internal purposes. Parametric, historical, and Monte Carlo approaches.
- VaR methodologies
- ES and coherence
- Backtesting
MODULE 6
Stress Testing
Scenario design and portfolio impact analysis. Historical replay, hypothetical scenarios, and reverse stress testing.
- Scenario construction
- Correlation assumptions
- Reporting frameworks
MODULE 7
Brinson Attribution
Performance decomposition into allocation, selection, and interaction effects. Multi-period linking and geometric methods.
- Brinson-Fachler
- Multi-period linking
- Smoothing algorithms
MODULE 8
Factor Attribution
Factor-based performance decomposition. Separating factor timing from security selection skill.
- Factor exposure
- Factor return
- Residual alpha
MODULE 9
Risk Limits
Designing and monitoring risk limit frameworks. VaR limits, drawdown limits, concentration limits, and breach protocols.
- Limit calibration
- Breach escalation
- Limit aggregation
MODULE 10
Production Systems
Building production portfolio management systems. Data pipelines, rebalancing engines, and reporting automation.
- Data architecture
- Rebalancing logic
- Audit trails