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MOCHILAB / AI SKILL
Portfolio Rebalance Draft
Draft user-targeted rebalancing trades with cash, lot sizes, fees and residual allocation drift.
What it does
Draft user-targeted rebalancing trades with cash, lot sizes, fees and residual allocation drift.
- User target weights must sum to one
- Sales fund cash-constrained purchases
- Round trades to supplied lot sizes
- Show fees and residual allocation drift
Try saying
Use my supplied records to draft user-targeted rebalancing trades with cash, lot sizes, fees and residual allocation drift.
Export a reproducible report with the assumptions, key metrics and detailed CSV. Ask me for missing facts first.
Calculation scope
Every holding needs id/quantity/price/target_weight/lot_size at a common valuation time and in the base currency. Targets come from the user. Sales occur before purchases; cash-limited buys follow input order. Fees and lot rounding leave residual drift. The output is a draft, never an order.
Deliverables and runtime
Includes executable Python 3.10+ standard-library calculations, independent numerical tests, fictional examples and an input reference. Supported flat collections accept CSV. No extra market-data key is needed. Files stay in the active assistant workspace, with input and output hashes. Analysis only; no account access or automatic trading.
References