Rebalancer
Turns valid target weights into a Portfolio rebalance result.
Turns valid target weights into a Portfolio rebalance result.
When to use
Use it after universe, scoring, weights, and applicable constraint checks are complete.
Example
Compare target weights with the current portfolio and handle Completed, No Change, Empty Universe, and Constraint Violation.
Interpret a proposed change
Connect target Weights, the current Portfolio, and any Constraints to the matching Rebalancer inputs. Suppose a two-asset portfolio is currently 70%/30% and the target is 50%/50%. The difference is 20 percentage points in each asset. With an illustrative portfolio value of 10,000 units, the nominal shift is 2,000 units from the overweight asset toward the underweight one, before prices, costs and execution rules. This arithmetic describes intent, not a guaranteed order or fill.
Review Rebalance tolerance, minimum trade size, turnover and execution style before interpreting the result. A small difference inside tolerance can yield No Change. An empty selected universe has its own outcome; a violated constraint is not a successful rebalance. Handle Completed, No Change, Empty Universe, and Constraint Violation separately and inspect the Result data rather than treating every continuation as execution success.
TWAP and VWAP appear in the execution-style list but are reserved and disabled for authoring. Use the supported Immediate style; the window and slicing fields tied to the reserved styles are not a runnable workflow.
Common problems
No Change can be a valid outcome. Do not treat a rebalance result as proof of future live execution.
Next steps
Review the generated Parameters, Outcomes, and Data Ports on this page, then open the related guides for the complete workflow.
Related documentation
- Rebalance Result FieldExtracts one field from a rebalance result.
- Leverage Metrics FieldExtracts one field from portfolio leverage metrics.
- Portfolio rebalance with risk limitsUnderstand a Portfolio pattern that filters an asset universe, calculates target weights, applies constraints, and rebalances.