Isolate legacy range-grid features
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@@ -481,13 +481,13 @@ into production as-is.
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### Hidden-feature isolation
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The remaining hypothesis is that the deployed detector accidentally measures
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long-memory historical price traffic rather than genuine S/R. A dedicated matrix
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holds the complete gate fixed and changes one legacy component at a time:
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The deployed detector accidentally measures long-memory historical price traffic
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rather than genuine S/R. A dedicated matrix holds the complete gate fixed and
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changes one legacy component at a time:
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- `legacy_geometry_neutral`: old locations, every merged strength fixed at 50;
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- `legacy_pivots_only`: unfiltered full-history pivots, no VP grid;
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- `legacy_traffic_grid_only`: old range-volume price grid, no pivots.
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- `legacy_traffic_grid_only`: deployed HVN+LVN grid, no pivots.
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Run on macOS:
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@@ -498,29 +498,54 @@ Run on macOS:
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Do not validate any traffic arm yet. First establish whether geometry, pivots, or
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the range-occupancy grid reproduces production on pre-2024 training data.
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Initial result:
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Corrected training result:
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| arm | Sharpe | CAGR | MaxDD | net avg R | ex-top-5% |
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|---|---:|---:|---:|---:|---:|
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| production control | 1.28 | 28.8% | 21.4% | 0.230 | 0.066 |
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| pivots only | 1.38 | 32.9% | 25.2% | 0.236 | 0.076 |
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| traffic grid only | **1.72** | **41.8%** | **16.8%** | **0.271** | **0.136** |
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| arm | qualified | Sharpe | CAGR | MaxDD | net avg R | ex-top-5% |
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|---|---:|---:|---:|---:|---:|---:|
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| production control | 676 | 1.28 | 28.8% | 21.4% | 0.230 | 0.066 |
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| corrected neutral geometry | 505 | 1.48 | 33.5% | 18.2% | 0.230 | 0.087 |
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| pivots only | 717 | 1.38 | 32.9% | 25.2% | 0.236 | 0.076 |
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| traffic grid only | 504 | **1.72** | **41.8%** | **16.8%** | **0.271** | **0.136** |
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The traffic grid is the first research arm to beat control simultaneously on
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Sharpe, CAGR, drawdown, and robust expectancy. It retains 264 production setups,
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adds 240 positive-expectancy setups, and removes 412 weaker setups. This supports
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the hypothesis that the useful legacy feature is the volume-weighted range-
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occupancy grid, not pivots or visually meaningful S/R.
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Sharpe, CAGR, drawdown, and robust expectancy. It retains 264 production setups
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at +0.214R ex-top-5%, adds 240 at +0.051R, and removes 412 at only +0.010R.
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Against corrected neutral geometry, only 239 qualified setups overlap; the 265
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traffic-only setups return +0.140R ex-top-5% versus +0.073R for the 266
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neutral-only setups. This is different selection, not merely a lower trade count.
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The first geometry-neutral result is not interpretable: neutral strength was set
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before the shared zone cluster, which summed multiple 50-strength constituents
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back to 100. Neutrality is now enforced after clustering. Rerun only that arm:
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The old `volume_profile` name is misleading. Its helper returns both HVN and LVN
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bins, so their union retains almost every one of the 20 evenly spaced centers over
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the expanding historical high-low range (19.987 levels on average in the audit).
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The later strength calculation does not use volume; it counts bars whose ranges
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cross each center. The candidate feature is therefore:
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1. a normalized, expanding 20-bin price-range grid;
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2. range-touch occupancy strength;
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3. no full-history pivot ladder or pivot/grid strength saturation.
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Two final training arms isolate the first two items explicitly:
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- `legacy_range_grid_touch`: all 20 range centers, no volume calculation, legacy
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touch strength;
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- `legacy_range_grid_neutral`: identical centers, strength fixed at 50 after
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clustering.
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Run only these new arms on macOS:
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```bash
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.venv/bin/python scripts/run_sr_v2_matrix.py traffic \
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--only-arm legacy_geometry_neutral --workers 14
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--only-arm legacy_range_grid_touch --workers 14
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.venv/bin/python scripts/run_sr_v2_matrix.py traffic \
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--only-arm legacy_range_grid_neutral --workers 14
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```
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The touch arm should closely reproduce `legacy_traffic_grid_only`; that is the
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volume-removal parity check. The touch-versus-neutral comparison then attributes
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any remaining difference to occupancy strength. Freeze the winner before running
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the post-2024-06-30 validation command; do not tune the bin count on training data.
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**Next runs, if picked back up:**
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- A **per-name target model** for clear-air setups instead of a constant k×ATR. This
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