SniperGold_ML/ml/p3/p3_s25_external_data_validation

P3-S25 — EXTERNAL DATA BASIS VALIDATION & INDEPENDENT POPULATION RECONCILIATION

Session : P3-S25 — EXTERNAL DATA BASIS VALIDATION
Status  : RESEARCH-ONLY DATA VALIDATION (no ML, no tuning, no calibration)
Policy  : docs/CODE_VERIFICATION_AND_SILENT_BUG_POLICY_v1.md
Purpose : Determine whether the corrected SniperGold research population and
          UTC-clock M30 construction remain valid when independently checked
          against prepared external historical data.
Next    : P3-S26 = NOT STARTED (requires explicit owner authorization)

Mission (abridged)

Answer whether the current absence of a demonstrated predictive edge is genuine, or whether residual historical-data/basis differences could still explain part of the result. Do NOT recover a positive ML result; do NOT optimize AUC; do NOT modify the model. Eliminate or quantify remaining data-basis uncertainty.

External data candidates (authoritative locations)

Source	Path	Nature
Tickstory → MT5 tick CSV	MQL5\Files\XAUUSD_mt5_ticks.csv	plain-text tick CSV, NO header, ~34.5 GB, 722,941,870 rows, 2003-05-05 → 2026-08-20
Dukascopy via Tickstory	MQL5\Files\XAUUSD\	YYYY/Mon/day/NNh_ticks.bi5 compressed container (zstd/lz4), 204,152 files (~3.2 GB)

Each source is treated independently (never merged).

Phases implemented

0  Mandatory preflight (documented in docs/P3_S25_EXTERNAL_DATA_BASIS_VALIDATION.md)
1  External data inventory          -> s25_inventory.py
2  Data-quality gate                -> s25_quality.py
3  Tick -> M15 independent oracle   -> s25_oracle.py  (ticks->M15 UTC buckets)
4  M15 -> M30 independent oracle    -> s25_oracle.py  (M15->M30 UTC buckets; 2 impls 100% agree)
5  Compare with corrected basis     -> s25_parity.py
6  Data-basis classification        -> s25_classify.py
7  Candidate Setup population replay (research basis) -> s25_replay.py (PART A)
8  External population replay       -> s25_replay.py (PART B)
9  Identity-level reconciliation    -> s25_reconcile.py
10 Difference attribution           -> s25_attribution.py
11 Information-value test           -> s25_classify.py (Question set + hierarchy)
12 Silent-bug / mutation testing    -> s25_mutation.py
13 Reproducibility (run twice)      -> s25_repro.py

Hard authorization boundary

Authorized: inventory, DQ validation, independent UTC M15/M30 construction, broker vs external comparison, corrected population replay, identity reconciliation, machine-readable evidence, mutation testing, documentation. NOT authorized: ML retraining/tuning, calibration, feature engineering/removal, label/TP/SL/horizon changes, nonlinear models, deployment, trading, production MQL5 changes.

Deliverables

• docs/P3_S25_EXTERNAL_DATA_BASIS_VALIDATION.md
• docs/P3_S25_EXTERNAL_DATA_POPULATION_RECONCILIATION.md
• docs/P3_S25_EXTERNAL_DATA_DECISION.md
• docs/SESSION_HANDOVER_2026-08-26_P3_S25_EXTERNAL_DATA_BASIS_VALIDATION.md
• this namespace (ml/p3/p3_s25_external_data_validation/)

Determinism & reproducibility

Every script is deterministic; evidence is machine-readable (JSON/CSV) with a SHA-256 manifest generated by s25_manifest.py. The runner (s25_run_main.py) can be executed twice; substantive outputs are byte-identical except generated-UCT timestamps and explicit environment metadata.

Hard stop

Commit only research artifacts, push to origin/main, verify clean tree, and record the final SHA. P3-S26 = NOT STARTED.