₹60L capital. ₹5L per trade. One consistent comparison.

What the fixed experiment produced

500 orderings: ₹10.75L–₹21.49L; median ₹17.99L. Only 2 of 500 reach ₹21L. This is an ordering sensitivity, not a confidence interval, forecast, or estimated probability of earning ₹21L. All three rows assume a 5% stop for missing originals and retain known entry-data defects.

Why the number kept changing

The earlier replies should not have presented unlike experiments as successive estimates of the same strategy. Capital and ₹5L sizing alone are insufficient: entry selection, position overlap, cash availability, stop assumptions, exit timing and open marks must also stay fixed.

The experiment contract

This isolates changed exits and portfolio consequences on historical entries. It is not a full reconstruction of today’s entry scanners; preserving source labels does not re-run each scanner. If buy dates/prices must also be regenerated, that is a separate experiment and needs historical scanner inputs.

Why 132 opportunities do not mean 132 funded trades

We evaluated all 132. In the reference ordering, 48 execute, 67 lack available cash, 9 encounter an existing holding in the same stock, and 8 encounter 12 occupied positions. Current code enforces one open holding per symbol and tenant. Holding winners longer keeps money occupied, so later historical buys may no longer fit.

Forcing independent ₹5L investments into all 132 produces ₹36.55L in summed hypothetical outcomes, but that is not a funded ₹60L portfolio. Allowing separate overlapping lots in the same stock yields ₹21.62L here; it relaxes the production constraint and is shown only as a sensitivity. Zero costs/slippage yields ₹22.03L, partly because it changes which trades fit, not merely because fees were added back.

Missing initial stops are not missing stocks or missing exits

We know these stocks and have historical exit records. The missing field is the stop price chosen when the position was opened. An eventual sell price does not reveal that original threshold. For example, the same ₹100 entry and ₹110 historical sale could have started with a ₹95 or ₹90 stop; under the new rules those paths may exit on different dates and free cash for different later trades.

The historical sale is the old outcome. Reusing it would prevent us from testing changed exits. No stop was recovered from the five inspected backups, so the original fields remain blank. We show assumed alternatives explicitly.

Change one assumption at a time

Each row uses the same ID entry ordering and changes the named baseline assumption. Outcomes are not monotonic because cash is recycled into different stocks. None is a recommended tuning choice selected by its profit.

Does the new exit rule beat the control?

With fixed ID ordering, new exits yield ₹12.36L versus ₹11.72L for a touch-stop / 5% breakeven control: about ₹0.64L higher. Across the 500 paired orderings, the median difference is ₹1.13L. Reference closed-trade win rate is 43.18%, versus 33.96% for that control. These compare different funded subsets, not identical completed trades. The control is a simplified old-style exit rule, not a reconstruction of every historical discretionary exit. This same-sample comparison does not establish future improvement.

Strategy sources remain visible

These are source-attributed results from one funded ordering, not independently capitalized strategy portfolios. VCP has only three recorded opportunities, so this sample cannot support a reliable VCP verdict.

What prevents a certified ₹21L answer

The best tested ordering includes RUBICON’s roughly ₹5.26L gain with an assumed original stop and WELCORP’s roughly ₹5.05L open gain on the flagged 22 May entry. That WELCORP row has a known duplicate/date-price inconsistency; it also contributes materially to the reference portfolio. These are not small rounding issues. We retained the inputs rather than inventing corrections; the data-quality report lists the eight entry-price/date anomalies.

Same-day fill order, original stops, historical defensive state and intraday stop updates are incompletely observed. Resolving them requires source evidence; choosing assumptions because they produce ₹21L would be fitting the result. Nothing here demonstrates an executable future ₹21L profit.

Inspect every trade and reproduce the calculation

All 132 opportunities and decisions · Reference executed trades · Near-median executed trades · Near-median all 132 decisions · Highest-case executed trades · Highest-case all 132 decisions · 500 paired orderings · Reference daily equity · Sensitivity summary · Strategy attribution · Frozen inputs · Replay source · Input hashes and code version · Run instructions and assumptions

The downloadable script was re-run against the frozen input CSV and the same local historical OHLC panel. It checks coverage of all 132 IDs, nonnegative cash, slot and stock limits, whole-share sizing, and reconciliation of final equity and source totals. The historical price panel is not redistributed; its SHA256 is published, so the package needs that panel and the pinned service checkout to reproduce. Open P&L uses modeled liquidation costs. All CSV amounts are rupees.

Full reference decision ledger