Risk Management Framework
Effective risk management for systematic futures trading requires understanding both normal market conditions and tail events.
Key Topics
Covariance Estimation
Methods for estimating and updating covariance matrices, including exponential weighting, shrinkage, and factor models.
Tail Correlation
How asset correlations change during market stress, and techniques for modeling and managing tail dependence.
Adaptive Scaling
Real-time adjustment of risk estimates based on recent market conditions, with asymmetric response to volatility spikes.
Constraints
Handling factor-neutral and other constraints in small universes where traditional mean-variance optimization may be intractable.
Core Principles
- Dynamic estimation - Risk is not constant; models must adapt
- Tail awareness - Normal times don’t predict crises
- Parsimony - Simple models often outperform complex ones
- Robustness - Prefer methods that degrade gracefully
Common Pitfalls
- Over-reliance on recent data - Exponential weighting can be too reactive
- Ignoring regime changes - Correlation structure shifts in crises
- Underestimating tail risk - Normal distribution assumptions fail
- Overfitting - Complex models often perform worse out-of-sample