Clarify IPO short-exit strategy horizon

Request:
- Emphasize that the analyst model is for selling allocated IPO shares in T2 grey market or on D1, not for long-term holding.

Changes:
- Add explicit T2/D1 sell discipline to the analyst skill.
- Update ipo_score_v0 targets and holding policy so D1 sell return is primary and T2 is the intended extension when reliable grey-market data exists.
- Clarify that D5/D20/D60 are review labels only, not planned holding targets.
- Update the model report, single-ticker report generator, README, and the 06106 report language to reflect the short-exit horizon.

Verification:
- Rebuilt the model report with the same dataset timestamp and confirmed the analysis dataset did not change.
- Ran py_compile for build_analysis_dataset.py and generate_ipo_report.py.
- Generated a 06106 dry-run report showing T2/D1 exit discipline.
- Ran git diff --check.

Next useful context:
- T2 is still disabled in v0 until archivist approves a reliable grey-market data source; D1 remains the live modeled sell label.

reports/2026-06-15_06106_T0_prospectus_analysis.md

@@ -9,8 +9,9 @@
 - Model dataset as of: `2026-06-15T14:04:34Z`
 - Rule version: `ipo_score_v0`
 - Rule path: `rules/ipo_score_v0.yaml`
+- Strategy horizon: short IPO subscription trade; intended exit is T2 grey market if reliable, otherwise D1.
 - Decision: `strong_watch`
-- PM action: Strong watch at T0, still pending T1 demand confirmation.
+- PM action: Strong watch at T0, still pending T1 demand confirmation for a T2/D1 exit.
 - T0 score: `11`
 - Score bucket: `t0_gte_8`
 - Calibrated D1 positive probability: 76.4% from 72 historical D1 labels
@@ -35,12 +36,14 @@
 | Initial public offer percentage | 5.0% |
 | Over-allotment shares | 1,574,550 |
 
-## Model Inference
+## Short-Exit Model Inference
 
 - D1 positive probability: 76.4%
 - D1 >= 10% probability: 47.2%
 - Historical average D1 return for bucket: 28.6%
 - Historical median D1 return for bucket: 9.6%
+- T2 sell return is not modeled until an approved grey-market data source exists.
+- D5/D20/D60 outcomes are review labels only, not holding targets.
 
 ## Score Breakdown
 
@@ -64,8 +67,8 @@
 
 - No material negative scoring component.
 - No required report field is blank for this stage.
-- T2 grey-market signal is not used because the project has no approved reproducible source.
-- Post-listing D1/D5/D20/D60 outcomes are labels for model calibration only and are not shown as prediction inputs.
+- T2 grey-market signal is not used yet because the project has no approved reproducible source.
+- Post-listing D5/D20/D60 outcomes are labels for later review only and are not holding-period targets.
 
 ## Triggers
 
@@ -74,9 +77,10 @@
 
 ## Exit Plan
 
-- If subscribed and allocated, reassess after allotment and before first trading session using only information available at that stage.
-- For T1 reports without approved T2 data, treat first-day liquidity and position sizing conservatively.
-- Record actual D1/D5/D20/D60 outcomes later as review labels, not as retroactive prediction inputs.
+- If subscribed and allocated, plan to sell in T2 grey market when reliable executable data is available.
+- If T2 is unavailable or unreliable, use D1 as the default exit window.
+- Do not treat D5/D20/D60 as planned holding periods for this model.
+- Record D1/D5/D20/D60 outcomes later as review labels, not as retroactive prediction inputs.
 
 ## Source Paths
 

reports/2026-06-15_analysis_model_v0.md

@@ -7,9 +7,9 @@
 
 ## What This Model Does
 
-This is the first analyst model built from the downloaded archive. It creates a repeatable feature table, scores each IPO using stage-safe rules, and calibrates the score buckets against archived D1 outcomes. It is intentionally transparent: the output includes every score component and the archived source paths used for each ticker.
+This is the first analyst model built from the downloaded archive. It creates a repeatable feature table, scores each IPO using stage-safe rules, and calibrates the score buckets against archived D1 sell outcomes. It is intentionally transparent: the output includes every score component and the archived source paths used for each ticker.
 
-The model does not use grey-market data in v0 because T2 currently has no approved reproducible source. It also does not use post-listing returns as inputs; returns are labels only.
+The model is built for a short IPO allocation trade: sell in T2 grey market when reliable executable data exists, or sell on D1 otherwise. It does not use grey-market data in v0 because T2 currently has no approved reproducible source. It also does not use post-listing returns as inputs; D1 is the primary sell label, while D5/D20/D60 are review labels only.
 
 ## Data Inventory
 
@@ -58,7 +58,8 @@ The high-conviction bucket remains clearly differentiated, but the middle and lo
 1. Run `scripts/build_analysis_dataset.py` after archivist updates the database.
 2. Use `t0_score` for prospectus-stage watchlisting.
 3. Use `total_score`, `decision_band`, and `calibrated_d1_positive_rate` for T1-stage subscription cards.
-4. Treat D1/D5/D20/D60 columns as review labels only, never as prediction inputs.
+4. Frame live decisions around a T2 or D1 sell, not long-term holding.
+5. Treat D5/D20/D60 columns as review labels only, never as prediction inputs or holding targets.
 
 ## Known Gaps