Owner decision 2026-09-15. Gone: market_outlook.py, the post-H1-scan Telegram
outlook DM, main.py --outlook, the outlooks table DDL/migration/writer in
signal_log.py, the market_outlook config block + MARKET_OUTLOOK_ENABLED, and
test Module 26. Last commit containing the feature: 2836024.
- app_config: "market_outlook" stays in _KNOWN_TOP as a TOLERATED, ignored
legacy key (oanda.account_id precedent) with one warning, so a live
config.json that still carries the block keeps booting.
- signal_log: existing DBs keep their orphan outlooks table and rows (no
DROP TABLE); fresh DBs never create it.
- tests: Module 26's 4-thread concurrent legacy-DB migration test (the
suite's only one) moved to Module 31; new test for the tolerated block.
519 -> 509 tests, 34 -> 33 modules, 0 failed.
- docs: CLAUDE.md usage/config/file-map lines and a dated state note.
Verification: W2 books (2024-09-05 -> 2026-09-05, $0.65, NumPy CPU, 0 cache
fallbacks) byte-identical before/after — M5 29120a1ee32979431d062f210d41a9d1
(781 / +146.07R / PF 1.52), M15 d185f099482a07f29502cb5a371a9bbf
(931 / +146.14R / PF 1.43).
New additive columns on every logged scan: bar_ts (primary closed-bar label, indexed with
timeframe), engine_fingerprint (hash of the scoring config incl. the regime weight table in
force - SignalAggregator.engine_config_fingerprint, twin of the gate fingerprint), code_version
(short git SHA), penalty_tags_json / penalty_total / momentum_fading / exhaustion_count, and
post-hoc watch_level / watch_kinds / watch_line written by violent_watch.attach_watch via
signal_log.update_watch. Each indicators_json entry now also carries eff_weight (base weight x
regime multiplier, the weight the composite actually used) and wscore.
engine: IndicatorSignal.effective_weight / weighted_score are stamped inside _compute_composite
(record-keeping only); regime_weight_table(config) is the single source of truth for the
multiplier table (override honoured). Composite output byte-identical (120-report hash proof).
New table scan_outcomes: model-free forward moves per scan (fwd_1h/4h/24h in $ and ATRs,
mfe/mae over 24h, burst_1h, bars_used, complete) measured on the stored candle stream with the
advisory model's continuity rule; labelled opportunistically at the end of log() (time-boxed,
throttled, idempotent) - no daemon; scripts/label_scan_outcomes.py drives the backlog
(--dry-run is read-only). analyze_signal_log --scan-outcomes: forward move + hit rate by
TF x signal/grade with a NEUTRAL baseline and burst rate by watch level. Readers dedup by the
first row per (timeframe, bar_ts).
Module 31 (10 tests). Suite: 463 passed. Backtester untouched (test-locked).
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
New violent_watch.py assesses each scan from the cached Forex Factory week events, the
UTC clock and the report's own indicator states, and stamps SignalReport.watch_line
post-hoc (telegram alerts, CLI, dashboard). A standalone heads-up goes to the owner on
the fastest scanned timeframe when the level is "hot", once per UTC hour per trigger
set, capped per day. Config block `violent_watch` (enabled False, alert_line, headsup,
max_headsup_per_day, headsup_min_level); env VIOLENT_WATCH_ENABLED.
Rule chosen from a 3-year bar-by-bar sweep (backtest/research/watch_rule_eval.py,
recorded in sizing_campaign_2026-09.md): hot = high-impact USD release within 30 min
(before or after) OR a hot clock slot (weekday 12-14 UTC, 01 UTC, Sunday 22-23 UTC)
with at least one price-extreme reading (outside Bollinger bands, RSI <30/>=70, outside
Keltner); ~8.6% of bars, next-bar odds 3-5x normal, ~4 hot hours/day. watch = clock
slot alone or two price-extreme readings (~2x). Context readings (ADX rising, extreme
volatility, transitioning, MACD acceleration) are phrases only - letting them raise the
level flagged 27% of bars at ~2x and would have sent ~13 heads-ups/day (rejected).
Direction sentence: DOWN when bearish readings dominate (70-78% on both TFs), UP on M5
only. Never a gate or exit: every open-trade protection tested lost money.
Test-locked out of analyze_from_dataframes / engine / backtester. Module 30 (18 tests).
Suite: 453 passed. Guide PDFs not rebuilt.
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
Harwinder Sekhon