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MOCHILAB / AI SKILL
DCA versus Lump-Sum Replay
Replay consecutive monthly total-return prices for DCA versus lump-sum investing with equal total budgets.
What it does
Replay consecutive monthly total-return prices for DCA versus lump-sum investing with equal total budgets.
- No forward execution-price lookahead
- Fixed and percentage trade fees
- Identical total investment budgets
- Units, marked values and ending differences
Try saying
Use my supplied records to replay consecutive monthly total-return prices for DCA versus lump-sum investing with equal total budgets.
Export a reproducible report with the assumptions, key metrics and detailed CSV. Ask me for missing facts first.
Calculation scope
Use exactly one supplied total-return execution price in every consecutive month. Fractional synthetic units and reinvested distributions are assumed. Lump sum requires the entire budget at the first date; uninvested DCA cash earns zero. Do not add distributions twice. Historical replay does not identify a future entry point.
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