Position sizing strategies for risk-parity portfolios
How are people handling position sizing? I'm exploring risk-parity approaches where each asset contributes equally to portfolio variance.
The challenge is estimating the covariance matrix reliably. Shrinkage estimators (Ledoit-Wolf) help but the results are sensitive to the lookback window.
Anyone tried hierarchical risk parity (HRP)?
27 Replies
Thanks for sharing! This is exactly the kind of insight that helps the community grow. Bookmarking this thread.
For time-series cross-validation, I've found that 5 expanding windows with a 21-day embargo works well for daily data.
For those wondering: yes, you can use external Python packages in submissions, but they must be in the approved list. No custom C extensions.
This is a common pitfall. Make sure your features are computed before the prediction date, not on it. That's subtle look-ahead bias.
Market regimes are the elephant in the room. A strategy that works in a trending market will fail in mean-reverting conditions.