The owner's DeBERTa-v3-small two-head ONNX model (golden set 72/78, ~72%
agreement with DeepSeek on unseen days) replaces DeepSeek for headline
scoring. DeepSeek keeps event direction, the summary and the dashboard
endpoint.
- news_model.py: vendored ML-NEWS runtime (lazy onnxruntime/tokenizers,
so the bot starts without them) + load-once, never-raising singleton.
- news_engine: _enrich_headline_scores mode switch (off/fallback/primary),
_apply_model_sentiment (gold head only: xau_score + XAU entry, never
USD; not-relevant shows 0.0; never touches _llm_sent_cache),
_audit_with_deepseek (archive-only labels, deepseek_audit_per_day).
- Owner decision: primary mode writes nothing to logs/newsdata.db except
audit copies — the model's output is not training data.
- app_config: news_model section (path/threads/mode/deepseek_audit_per_day)
+ NEWS_MODEL_MODE env override; validated at boot.
- news_archive: model rows carry teacher_model xau_transformer@<trained_at>.
- deploy/README-news-model.md (ops for bot + dashboard daemon), unit gets a
commented NEWS_MODEL_MODE=off line; requirements + onnxruntime, tokenizers.
- test_all.py Module 38 (15 tests, one against the real bundle). Suite 581.
- CLAUDE.md, spec status note, handoff marked implemented.
Books unaffected: news never enters signals; no signal file touched.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Owner question: can score and confidence be combined into one number that is
easier to understand and for the system to decide on?
Research (pre-registered, nothing ships to the signal path):
- signals.grading_mode: "pair" (default, the shipped two-floor rule, byte-
identical: all five reference MD5s reproduce on both scripts), "min"
(min(|score|, 0.6*conf)), "product" (|score|*conf/100); thresholds fixed from
the control's corner points, no tuning. Helpers _final_signal_and_grade /
_transitioning_boost / conviction / CONVICTION_THRESHOLDS in signal_aggregator;
mirrored in K2 (GRADING_MODE_CODES, PF_conv_* packed from the live module);
twin refuses other values; M15 OOS MD5 equal on both scripts for both modes.
- Verdict: FAILED on M5 and M15. K-MIN moves 43-54 trades for -1.2R / -2.9R
(clauses a,b,e / a,b,d); K-PROD -29R on M15 (PF 1.29, W3 DD 28.9R), neutral
on M5. H1/H4 product +11.9R / +17.0R on W3 from extra low-score trades
(H1 PF 1.98 -> 1.75, DD doubles): hypothesis only.
- Code review (high) before the runs: 6 findings fixed, 1 recorded
(engine_config_fingerprint omits the switch under "pair", so live rows keep
their fingerprint).
Delivery (books untouched): alerts lead with the grade and print the two raw
numbers in words (main.plain_words: "Direction: strong buy · Reliability: good
· timeframes agree", cut-offs = the grade table's own) on Telegram, /status,
the CLI and the dashboard card (plain_words in the snapshot); "MTF" label
replaced by "Other timeframes"; guides updated. Suite 566 passed.
Evidence: backtest/research/conviction_campaign_2026-09-27.md
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Live signals.db review (2026-09-04 → 09-25, 100 unique setups replayed on the
scans' stored candles): the stop-hunt claim is refuted (71% of stop-outs ran
≥ 1R past the stop, the same as the books' 70–72%); −25.1R of the −37.8R raw
live book were consecutive-bar re-entries the backtester's 5-bar cooldown never
takes; the cooldown view sits at the 3rd–5th percentile of the books' three-week
windows.
Delivery (book-neutral):
- telegram_bot: 5-bar alert cooldown per timeframe (_ALERT_COOLDOWN_BARS =
backtest.cooldown_bars); setup block prints the trail first as the tested
exit, TP1/TP2 as guides with their R, "Planned TP1 RR", and one validated-book
line per setup class (agent_panel_base_rates.json); the informational 100-pip
TP line is removed (owner request).
- AI block rewritten for a new trader: "AI check: the odds look better than /
worse than / about usual", the chance "in 100" against the usual odds, one
reason for and one against, no verdict word or confidence figure; rendered
whenever the verdict carries a probability. agent_panel: persona prompts ban
trading jargon (PANEL_PROMPT_VERSION v2.1-2026-09-26); the macro-source
verdict now carries its persona's p_win (every live v2 row had
panel_probability NULL). Dashboard and guides mirror the wording.
- telegram_bot: level-breach rescans skip the settlement-pause window (the
20:45 M15 bar was re-logged at 22:01/22:06/22:11 every evening).
Signal (pre-registered rule-1 campaign, CUDA twin paired with gpu_backtest.py):
- M15 grade-A SELLs blocked (sell_min_quality ["A+","B"], M15 override 6):
W2 813/+154.15R PF 1.53 vs 931/+146.14R PF 1.43, OOS +68.5 vs +60.67,
W3 max DD 20.9 vs 19.3R. PASSED a–f.
- Printed target 1 floored at 1R in every generator (signals.tp_print_floor_rr),
applied AFTER the min-RR and spread gates so no trade changes; mirrored in
cuda_signal_kernels.py K2. Label-only re-pin of all four timeframes (only
tp1/rr_planned columns move). A floor applied before the gate cost −24.6R and
was rejected.
- FAILED: M15 min_rr_ratio 1.0 (trade-identical, −2.0R). Owner's call: M5
tp_floor_rr 1.0 (+48.9R W2, max DD 10.1 → 15.9R), not shipped.
New pins: M5 W2 e599c8a8…, M15 W2 5b65ecf6…, M15 OOS 09b8a8e7…, H1 W3
a44fd19b…, H4 W3 f3587bae…; twin and reference MD5s equal on every window.
Base-rate table rebuilt from the new pins. Suite 558 passed.
Evidence: backtest/research/rr_and_sell_campaign_2026-09-26.md (plus the
2026-09-18 loss-anatomy and wrong-direction reports it builds on).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
A NEUTRAL vote (value 0) and an absent divergence/candlestick entry both
drew no bar, so RSI, Div and Cndl looked missing on the live page. The
engine computes them on every scan; divergence and candlestick only exist
when a pattern is found (by design, "no opinion"). The chart now draws a
grey dot on the zero line for a neutral vote and a faint "no pattern" tag
for an absent pattern indicator; rows hover as a whole. Display-only,
signal code and books untouched. Suite 554/554.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
One card per timeframe (M5/M15/H1/H4) in a Bootstrap column grid, above a
direction board that charts every timeframe's score as a diverging bar.
Each card carries its own indicator-vote chart, and the newswire gets a
headline-tone bar. Bootstrap Icons and the hand-rolled CSS gauges are gone;
dashboard.css is now the token set plus the app-specific pieces only.
Chart marks use a diverging pair validated on this surface (#0d9f7a /
#e8503a: lightness band, chroma floor, colour-vision separation, contrast).
Lighter steps of the same two hues carry the colour where it has to work as
text, and direction never travels as colour alone -- an arrow icon and the
word ride with it.
Behaviour is unchanged: same snapshot.json / news.json contract, the same
coordinated refresh loop (boundary poll, 60 s fallback, 15 s retry,
in-flight guard, stale-snapshot guard), per-timeframe change detection,
modal state preservation, HTML escaping, the news_summary.php contract and
the warming / scan-failed / weekend states. Nothing on the signal path is
touched, so no book moves.
Verified headlessly against a fixture replayed through the real signal code
(wide / laptop / tablet / mobile, both dialogs, every degraded state): no
console errors, html-validate clean.
Suite 553 -- the old static-UI test splits into one that pins the CDN stack
and one that pins a card and a chart per timeframe against
dashboard_publisher.DASHBOARD_TFS.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Owner decisions: research only (live scans stay on the CPU code), gpu_backtest.py
stays the base reference, every research flag supported, the one exemption from
instructions item 6 recorded in backtest/instructions_for_backtest.txt.
- backtest/cuda_signal_kernels.py: the CUDA decision stage. K1 = engine.py + the
GPUTechnicalEngine overrides (one thread per bar), K2 = analyze_from_dataframes
end to end incl. gates 6b-6i, the four setup generators and the regime filter
(one thread per primary bar), K3 = position_sizing.build_features, K4 cooldown,
K5 prefix median, K6 recorder bar rows. Config packer with generated #defines;
leaf module; --fmad=false; Python evaluation order kept (ternary min/max,
pairwise sums, Neumaier sum(), exact round(x, 2)).
- backtest/cudaBasedBacktesting.py: same CLI, cache files and writers as the
reference; the host turns kernel codes into the exact strings; no CPU path.
- test_all.py Module 37 (16 tests): every stage pinned against the live code;
suite 552 / 552 on the GPU, without CUDA and with FB2_BACKEND=cpu.
- Proof: five reference MD5s, four 6-month acceptance books (M5/M15, $0.65/$0.30),
M15 OOS --export-features and --record --record-bars tables, ten research-flag
variants, and the owner's five-year M5 and M15 books, all byte-identical to
gpu_backtest.py. Wall time 0.8-6.6 s per book against 13-353 s.
- CLAUDE.md sections 1, 3, 6, 7, 9, 10, 11 and the instructions addendum: any
signal change is now a parity event for the twin.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
CuPy from pip had never compiled a kernel on the dev box (no CUDA_PATH for the
splayed CUDA-12 wheel layout); the probe swallowed the error and every book to
date was built on the NumPy path under a "GPU backtester" name.
- backtest/gpu_kernels.py (new): lazily probed, never-silent BACKEND state
(CUDA_PATH pointed at the nvidia-cuda-runtime-cu12 header wheel; the probe
compiles a kernel and keeps the failure reason), --backend auto|gpu|cpu and
FB2_BACKEND, and three CUDA kernels compiled with --fmad=false: ewm_batch
(the _gpu_ewm_alpha recurrence, one thread per series), roll_mean_var
(pandas 3.0.2 roll_mean/roll_var replica, Kahan + Welford + unstable
recompute), resolve_trades (trailing and static exits, one thread per trade).
- gpu_backtest.py: precompute_indicators and simulate_trades dispatch to the
GPU twins or to the untouched NumPy paths; caches are host NumPy and device
memory is released before the replay workers fork; the Backend: line names
the device or the fallback reason.
- test_all.py Module 36 (7 tests): a visible CUDA device must never fall back
silently; kernels vs their CPU references on synthetic edge cases; backend
selection; import guards (cupy banned from the live roots). Suite 536.
- CLAUDE.md, instructions_for_backtest.txt, research note with the evidence.
Verification: all five reference MD5s reproduced on the GPU and with
--backend cpu (ten runs, GPU cache fallbacks 0); precompute GPU == CPU on all
42 cached windows (2.34 M bars); suite green with GPU, with
CUDA_VISIBLE_DEVICES="" and with FB2_BACKEND=cpu; --workers 1 and --record
pairs equal. The per-bar replay stays the live Python signal code on CPU
workers by design; wall time is roughly unchanged (precompute ~3x faster).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Agent panel v2: personas return p_win anchored to the book base rates with a
code-computed decision context; verdict = equal-weight mean (verdict_source
"mean"); only the macro persona runs live (agent_panel.personas ["macro"]);
prompt version and exact payloads logged; offline replay harness
scripts/panel_replay.py; base-rate table agent_panel_base_rates.json
(scripts/build_panel_base_rates.py). Backtester `strategy` column now carries
the generator's own stamp (label-only; five reference books re-pinned, all
62 other columns identical).
News corpus (after evaluating the owner's ML-NEWS scikit model against
DeepSeek: golden set 39/78 vs 78/78, out-of-sample agreement 64% against a
90% self-agreement ceiling; verdict: fallback only, not a replacement):
- NewsSentiment.xau_score + archive column xau_score keep DeepSeek's gold
score for every headline (930 of the first 1,546 DeepSeek rows had none);
an existing newsdata.db gains the column in place on first open
- headlines naming no tracked currency are scored and archived
(currencies_json []) but never returned to the platform
- _apply_llm_sentiment sends every new headline in its cycle, 25 per call;
a failed call ends the cycle's sending
Dashboard publisher never writes a database: main() calls
app_config.set_db_writes_for_process(False), honoured by signal_log_enabled()
and news_archive_enabled() (owner decision: the bot is the single writer).
Test suite: the hermetic app config now points both writers at a
suite-private temp dir — the RSS fixture tests were writing fixture
headlines into the real logs/newsdata.db — with a Module 32 test pinning it.
529 tests.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Same facts, new shape: quick start; the scan pipeline from trigger to
delivery to logging (A to Z) with the real thresholds and gate order;
a file-by-file guide with the import graph; data providers; config;
testing; the nine change rules; the validated per-timeframe overrides;
reference books with MD5s and the kept cache windows; a traps list;
and the decision ledger condensed to one row per dated decision with a
pointer to its research report.
Every claim was checked against the code by a reviewer pass; the
mechanism invariants the old file carried (MACD always computed, the
_-prefixed convention, PB/CP force grade B, penalties hit confidence,
gate 6b label-hour vs close-hour, the news-archive hook position, the
ordered cooldown pass, engine_fingerprint split rule, oppose guard,
holiday blindness) are kept. The previous 58 KB version is in git
history at b0b71e1.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Discussion-first cleanup of backtest/ and scripts/. Nothing in the signal
core or the backtester changed.
Removed (last commit containing them: 931b265):
- backtest/diagnose_filters.py + its two Module 18 tests
- scripts/shadow_scan.py (Phase 4 shadow scan, never run)
- scripts/backfill_news_archive.py, scripts/migrate_signal_log_news.py
(one-time scripts; the interning test keeps its live-path half, the
prune test goes)
Kept: the replay-recording stack (replay_record.py, replay_scorecard.py,
ff_calendar_scraper.py, cache/calendar.parquet, Module 33).
Local gitignored data was moved to ~/Development/ForexBot2_trash_2026-09-15
(346 MB) for the owner to delete: all 35 pinned backtest/*.csv books, the
three research output folders, the BTC/ETH cache snapshots, the Tiingo
parquets and 13 uncited Oanda windows. The three research-folder ignore
rules are dropped with the folders.
Verification: all five gate books regenerate offline from the pruned cache
with the recorded MD5s (M5 W2 29120a1e, M15 W2 d185f099, M15 OOS 6f8f24b4,
H1 W3 3b45d12b, H4 W3 e75adae1; NumPy CPU, 0 cache fallbacks). Suite
506 passed, 0 failed, 33 modules.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Signal path
- A shipped setup always names a direction: grade C needs confidence
>= 45 (gate 6c grants B at >= 45) while BUY/SELL needs >= 50, so C/B
reports reached the alert gate as NEUTRAL with a full setup. The
backtester traded them (the replay never reads final_signal) while
Telegram rejected NEUTRAL first — 5/91 trades, +3.7R of +22.2R, in
the H1 12-month book. _attach_core_setup stamps the setup's direction
and repairs the pre-gate action text; no-setup reports stay NEUTRAL.
- analyze_pair fails the scan when ANY required frame is missing
("DATA UNAVAILABLE:", scan_kind='failed'); a lost confirmation frame
used to run with an unearned -15 MTF penalty.
Outcomes and labels
- advisory_outcome.resolve_locked_floor: a gap the database cannot fill
resolves at the locked trailing stop (GAP_LOCKED, result.floor) when
the stop had crossed the entry; the rebuild fires on both gap reasons
(rows 915/920: +1.14R / +0.84R floors; resolved sum -2.46R -> -0.48R).
- label_scan_outcomes: SCAN_LABEL_MAX_AGE_H = 72 h, stale rows never
anchor the shared bar stream, labeled_at bumped on re-examination,
_stream_since warns at its row cap (the Labor-Day pile would have
blinded scan_outcomes around 2026-09-14).
Providers and scheduling
- The daily settlement pause (Mon-Thu 17:00 New York) is a scheduled
closure for _has_latest_closed_bar (whole-span label walk-back) and
_is_data_fresh (closed seconds are not age); bot and dashboard skip
scans whose just-closed label sits in the pause (61 false stale rows
in three nights).
- fetch_range retries a failed page in place (three failures on one
window raise) and logs an ERROR for interior gaps of >3 unscheduled
bars.
- pd.Timestamp.utcnow() replaced in providers/base.py and engine.py;
requirements pin pandas<4, numpy<3.
- telegram_bot: boundary loops share one scan per bar with the breach
handler (_remember_scan keys on the analysed bar; breach defers 20 s
after an M15 boundary); the rotating file handler attaches in main()
only (the test suite used to write into logs/telegram.log).
- dashboard_publisher: catch_up_timeframes re-scans boundaries missed
while a cycle overran or the process was down.
Backtester and engine guards
- _replay_span returns the per-span GPU cache-miss count; run_backtest
sums, logs it (must be 0) and writes cache_fallbacks to the manifest.
- regime_weight_table raises on a partial regime_weights_override.
Verification: 519 tests; M5/M15 2-yr, M15 OOS, H1/H4 3-yr books
byte-identical before and after; live signals.db untouched (checked on
a copy). CLAUDE.md carries the dated entry and the blocked-hours union
semantics that every book was validated under.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0139xz1J6YccndA2be6yFnEo
backtest/research/cycle_2026-09-10.md: pre-registered rules, HEAD baseline
on the 3-year window (three pinned MD5s reproduced), cost ladder and
concentration facts, bucket screen (one cycle-2 candidate: M15 grade-A
SELLs), C1 H1 divergence->0 REJECTED, C2 M15 RSI-multiplier ladder =
stable plateau, seeding-depth measurement and the two shipped parity
fixes. CLAUDE.md: live fetch depth, backtester pad, 501 tests, the
2026-09-10 state entry; corrected the docs note (no PDF builds exist)
and recorded pyarrow as a dev-venv-only dependency.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NQDjW8rXYrJR4JDWMWKUij
The per-TF warm-up pad before --start targeted 210 bars, so a 3-year H4
book started with 372 H4 bars and ~210 D1 bars of seeding while the
live scanner now fetches at least MIN_LIVE_BARS (1000) on every
timeframe. _history_pad_days keeps the 62-day intraday pad (already
>= 1488 bars, so M5/M15/H1 cache windows are untouched) and pads H4 by
234 and D1 by 1400 calendar days; the raw-path fetch for trade
resolution reuses the primary timeframe's own start (one cache file
per TF, as before).
Verified on the 3-year books at $0.65: M5 and M15 byte-identical
(c2722f98…, b2cfa9e2…); H1 and H4 trade-for-trade identical (253 /
+70.02R, 114 / +21.68R) — the only differences are one H4
confirmation reading 15 days into the H1 window and 1e-6…1e-9 numerics
in D1 Wilder recursions during Oct–Dec 2023, i.e. the window-start
seeding zone. Evidence: backtest/research/cycle_2026-09-10.md.
Tests: Module 21 "history pad seeds slow TFs like live". Suite 501 passed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NQDjW8rXYrJR4JDWMWKUij
The engine's EMAs use ewm(adjust=False), so the first bar of a fetched
frame keeps weight (1-2/201)^n in the 200-bar trend EMA. With the 60-day
lookback the live H4 frame had 380 bars (seed weight 2.3%) and D1 300
(5%), while the backtester seeds from its whole cached history. Measured
on the deepest Oanda caches (267 H4 / 313 D1 bars sampled over two years,
raw and cleaned frames): ema_trend flipped on 2/267 H4 and 1/313 D1 bars
at those depths (composite off by up to 9.5 points) and on none from 600
bars up. MIN_LIVE_BARS = 1000 leaves a seed weight of e^-10; M5/M15
(5000) and H1 (1460) already exceed it and are unchanged. One request
either way. The backtester never calls fetch_ohlcv, so no book changes.
Tests: new Module 16 depth test; the Module 21 cache test's 300-bar
expectation becomes 1000. Suite 500 passed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NQDjW8rXYrJR4JDWMWKUij
Owner-approved 2026-09-09 after the pre-registered weight test
(backtest/research/weight_test_2026-09-09.md). M15-only
technical.regime_weights_override = the shipped table with rsi x 0.5
(0.5 trending family / 0.75 ranging / 0.5 transitioning), derived in the
factory and pinned literally by the Module 9 equivalence test; a Module 33
test locks that M5/H1/H4 carry no override.
Evidence, 2-year Oanda window 2024-09-05..2026-09-05 at $0.65: 793/+117.62R
PF 1.41 -> 931/+146.14R PF 1.43 (fixed halves +27.9/+0.6R vs control); OOS
2024-06-01..2025-03-30 300/+40.59R PF 1.38 -> 355/+60.67R PF 1.49; 3-year
+151.90R -> +186.61R (max DD 15.5 -> 19.3R, 2026 -4R). Parity: the factory
run with no --set flag reproduces the validated candidate books byte-for-
byte (2-yr MD5 d185f099..., OOS 6f8f24b4...). M15 canonical book re-pinned
to backtest/oanda_m15_2yr_065_20260909.csv. Docs carry a one-line note.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Nc9Ninzyi18QkWezrxeBvB
First use of the --record evidence: a drift-adjusted per-bar screen ranked
regime-multiplier candidates, the top 3 per timeframe went through the full
2-year replay against same-harness controls plus the 2024-06..2025-03 OOS
window under a rule written before any run. M5: all three MACD candidates
fail (-10..-46R). M15: ema_trend x2 and divergence->0 (trending) fail;
RSI x0.5 in every regime passes every check (2-yr +117.6 -> +146.1R PF 1.43,
OOS +40.6 -> +60.7R PF 1.49, 3-yr +151.9 -> +186.6R) with the caveats recorded
(2026 -4R, 3-yr max DD 15.5 -> 19.3R, added trades mostly B-grade BUYs).
Nothing shipped; the passing candidate is an owner decision.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Nc9Ninzyi18QkWezrxeBvB
Adds an opt-in recorder to the backtester so a replay keeps the evidence each
trade setup was decided on: every indicator's vote, value, confidence, base
weight, regime multiplier, effective weight and contribution on the primary and
both confirmation timeframes, penalties, the setup and outcome, and the Forex
Factory calendar events around the trade (4 h before entry to exit, all-day rows
on the New-York date). --record-bars adds one float32 row per analyzed bar with
the same votes plus 1 h/4 h/24 h forward moves in ATRs. Output is Parquet in a
folder per run with a manifest carrying the engine/gate fingerprints, the regime
weight table in force and the book MD5.
Nothing in the signal core changes: the trade book is byte-identical with
recording on or off (control-vs-recorded MD5 equal on both 2-year runs, M5
781 / +146.07R / PF 1.52, M15 793 / +117.62R / PF 1.41 at $0.65). Module 33
adds 12 tests (498 total): snapshot reproduces the engine's composite, absence
is no vote, calendar join edges/phases/holiday, write/load round-trip,
_replay_span parity with recording on, CLI flags, import and source guards.
Also: backtest/replay_scorecard.py (first-look scorecards, calendar buckets,
in-book and per-bar what-ifs, --check invariants), scripts/ff_calendar_scraper.py
restored from git history (the only way to regenerate the gitignored calendar
file), report in backtest/research/replay_recording_2026-09-09.md.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Nc9Ninzyi18QkWezrxeBvB
1. A backfill pass silently wiped teacher identity from live rows.
The provenance compare is `>=`, and backfill rows are llm-scored but
carry no teacher_model/teacher_prompt_sha1 (neither source DB recorded
one), so a bare assignment blanked what the live hook had stored.
Re-running the backfill — e.g. after importing the live server's
signals.db, which is the next planned step — would have erased it from
every live row. COALESCE now keeps a stored identity when the incoming
one is NULL, while a genuinely newer teacher still replaces it.
Timestamps clamp for the same reason: backfill stamps historical
values, so first_seen only moves earlier and last_seen only later.
2. A retried batch could be applied twice. executemany does not roll
itself back, so a batch that half-landed and then hit a lock was
re-applied whole by _with_lock_retry, double-counting seen_count on
the rows that already landed. Writes now run in an explicit BEGIN
IMMEDIATE with a rollback, which also takes the write lock up front so
contention fails before any row is applied.
3. The archive hook could break a news fetch. archive_headlines swallows
its own failures, but its ARGUMENTS are evaluated first, so a raising
get_llm_client() escaped that guard. Guarded at the call site too:
archiving is a side effect and must never cost us the headlines we
just fetched.
Both 1 and 2 were verified to reproduce against 301bf90 before fixing
(teacher_model -> None; seen_count 3 instead of 2 on the rows that
landed pre-failure) and are now regression tests.
Also fixed two weak tests of my own: the disabled-by-config test never
pointed NEWS_ARCHIVE_PATH at its temp dir, so its assertion passed
regardless of behaviour and the write went to the real archive; and the
neutral-headline test asserted the headline was archived without showing
it is dropped downstream, which is the entire reason the hook sits where
it does. Positional binding of the provenance rank is now asserted rather
than trusted, since a miscount would shift every parameter silently.
483 -> 486 tests.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Bzv4ETVapFNauFDQht7QtA
Headlines only ever survived as a side effect of signal logging, and
logs/signals.db was rotated around 2026-09-04 — destroying the 3-week,
4,054-headline corpus news_sentiment_value_2026-09-04.md was written on.
logs/ is gitignored, so git could not recover it and nobody noticed for
four days. There is no way to backfill a fetch window once it passes.
news_archive.py writes to its OWN database (logs/newsdata.db) so a
signal-log rotation cannot take the news with it. One row per distinct
headline (sha256 key) with the text, description, link, publisher,
publish time, the score, and — new — which scorer produced that score.
Provenance is the load-bearing part. DeepSeek scores 78/78 on the
2026-08-06 golden set; the keyword scorer it overrides scores 24/78
(31%), and that is what silently stands on no key, disabled, daily cap,
timeout, HTTP/parse failure, or the >25-new-headlines-per-cycle batch
overflow. Until now both landed in the same column, indistinguishable,
so a model trained on the mix would inherit the keyword scorer's errors.
NewsSentiment.score_source now records it, mirrored into signals.db via
signal_log._headline_to_dict, and teacher_model/teacher_prompt_sha1 keep
labels made under a changed prompt from being pooled with older ones.
Writes are one atomic UPSERT per row, upgrade-only: an llm score always
replaces a keyword one (the batch-overflow tail gets labelled on the
next window in a long-running process — verified 13/13), a keyword score
never overwrites an llm one, and re-seeing a headline always counts. A
read-then-write pair lost increments when the bot, the dashboard
publisher and the tests first saw a headline together, and the WAL
switch itself needed _with_lock_retry; both are regression-tested with
three concurrent writers.
The hook sits at the end of _fetch_news_sentiment_raw, BEFORE
_is_neutral_headline runs in get_fundamental_context. Archiving
downstream of that ±0.1 filter is why signals.db holds almost no neutral
headlines and would have taught a trained scorer that "neutral" barely
exists.
scripts/backfill_news_archive.py seeds it from both DB shapes on disk,
read-only and idempotent, recomputing provenance by comparing each
stored score against the keyword scorer (neither source recorded it):
1,016 distinct headlines, 846 DeepSeek-labelled, growing ~1,400/week.
Nothing in the signal core changed. Both news gating flags stay False,
no gate reads any of this, and the backtester never builds a NewsEngine
so replays never archive (test-locked). 468 -> 483 tests, including a
new guard that AST-walks live code for sklearn/scipy/lightgbm imports —
that check did not exist before.
Do not train yet: ~800 labels gives a holdout too small to grade
(SE +/-0.032). Target is ~4,000 deduplicated headlines over >=3 weeks.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Bzv4ETVapFNauFDQht7QtA
Delivery-side fixes from the 2026-09-08 three-day signal-log + telegram-log
review. Nothing in the signal core changes: the 3-year H1 and M15 books at
$0.65 were regenerated before/after and are identical on every trade column
(H1 253 / +70.02R / PF 1.98, M15 1092 / +151.90R / PF 1.38); only the
exported `warnings` text differs, on 50/253 H1 and 358/1092 M15 trades.
- signal_aggregator: step 7 moves into `_attach_core_setup`; a final pass
after the PB/CP archetypes (`_drop_stale_spread_gate_vetoes`) moves a core
generator's "SPREAD GATE: ... costs would eat the edge" veto to
`cleaned_warnings` whenever a later generator shipped a setup. The
2026-09-08 07:45 UTC A-grade alert carried that line beside a $26.49 TP1;
a fifth of H1 and a third of M15 A-grade alerts had been doing the same.
The prefix is now the `_SPREAD_GATE_PREFIX` constant shared by both
emitters and both cleanups.
- telegram_bot: alerts require a trade setup (`_is_alert_candidate`, shared
by the scan and breach paths; no-setup candidates log
`alert skipped: ... (gate reason)`). The 07:50 UTC B-grade SELL with no
setup had gone out under the same warning.
- telegram_bot: every delivered alert / breach alert / violent-move heads-up
logs an `... sent:` INFO line with the signal-log row id (only failures
were logged before, so the review had to reconstruct sends from panel
rows). Send fan-out is one `_broadcast` helper for both paths.
- telegram_bot: `telegram.log` rotates daily x 30 instead of 3-hourly x 240
(old `_HH` files on the live box need one manual delete).
- signal_log / CLAUDE.md: `cleaned_warnings_json` is no longer a CP-only
marker; docs say so.
- test_all: 468 tests (+2): stale-veto cleanup incl. the PB-shaped case and
the both-vetoed case, and the alert-candidate rule with its skip line; the
rotation test asserts MIDNIGHT / interval 86400 / 30 backups.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018xY4NPPrx6NJoG6QWHzwpd
2026-09-07 signal-log inspection follow-up — three fixes that do not depend on sample size.
- providers/base.py: the signal-side 10σ outlier filter is now a bad-print filter. A >10σ
close-to-close bar is dropped only when the NEXT close snaps back ≥80% of the way
(OUTLIER_SIGMA / OUTLIER_REVERT_FRACTION); persisting moves and the newest bar are kept.
The unconditional rule deleted ~36 real M5 news bars/yr in the backtester (whole-frame σ)
and a different ~24/yr live (fetch-window σ) — e.g. the 2026-09-04 12:30 UTC NFP bar
vanished from M5+M15 and the 12:35 scan was a byte-identical repeat of 12:30. 3-yr Oanda
drops are now M5 2 / M15 1 / H1 0.
- providers/oanda.py: transient 401/5xx/network faults retry along RETRY_DELAYS_S=(2,5,10)s
under RETRY_BUDGET_S=45s. 11 boundary scans in two days had lost their primary frame at
xx:00:22–:26 UTC; one 2 s retry could not outlast the top-of-hour blip.
- signal_aggregator/_log_signal: a scan whose primary fetch failed logs scan_kind='failed'
(price 0, no signal); analyze_signal_log.parity_report skips it like 'blocked'.
- test_all.py: 466 tests (+6): retry ladder walks all delays, 5xx blip recovers on the third
attempt, retry budget stops the ladder, persisting/newest/partially-retraced 10σ bars kept,
failed-scan row kind, parity skip.
- CLAUDE.md: cleaning rule, retry ladder, failed scan kind, dated current-state note.
Book impact at $0.65 (rule 1 still passes everywhere, both halves positive):
12mo M5 557/+112.21/PF1.56 → 560/+108.81/1.54 M15 397/+73.93/1.53 → 398/+74.61/1.53 H1 identical
3yr M5 857/+161.3/1.53 → 870/+153.6/1.50 M15 1086/+148.7/1.37 → 1092/+151.9/1.38
H1 255/+70.5/1.98 → 253/+70.0/1.98 H4 113/+22.7/1.63 → 114/+21.7/1.59
Only trades on the previously-deleted event bars move; the pinned M5/M15 CSVs are no longer
byte-reproducible and should be regenerated at the next re-pin.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NDnBxJ2y8GRUM6ZNFJs1hZ
- providers: _to_oanda_instrument / _to_tiingo_ticker / _to_td_symbol no longer
guess a wire symbol for pairs that are not registered — the registries are
the only source, so an unknown symbol raises the provider's DataIntegrityError
instead of silently fetching something else. Every scanned symbol is validated
against PAIR_INFO at import, so nothing reachable changes.
- main / telegram_bot _fmt_price: the sub-$10 five-decimal branch could never
fire for gold.
- news_engine._parse_pair: BASE/QUOTE only; the Yahoo "=X" fallback was
unreachable (its test goes with it).
- dashboard_publisher.event_to_dict: drop minutes_until (frozen at publish
time, misleading) and is_high_impact — dashboard.js never read either.
- static/dashboard.html: unused id="cal-table".
Tried and reverted: trimming the LogRow fields nothing in analyze_signal_log
reads — the tests read them to verify the loader round-trips those DB columns,
so they stay.
Suite: 460 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
- SignalAggregator.pb_funnel / cp_funnel and the 19 _reject() ticks inside
_try_m5_pullback / _try_chart_pattern: class-level rejection counters nothing
in the repo reads. Every gate keeps its early return; only the counter bump
before it is gone.
- _TP_QUALITY_SCALE: the "B"/"C" entries and the 0.75 default could never be
selected — the XAU ATR generator is only called for A+/A. The lookup is now
a direct index so a violated invariant fails loudly instead of scaling silently.
- engine._classify_regime no longer takes the unused DataFrame argument, and the
structure S/R branch tests the 5-minute frame only (M1 is never a primary).
Parity: 12-month M5 and H1 books regenerated byte-identical
(md5 a28fed4becd056466c26d6a947e1a0e5 / d20405ef64f069770c258bb9bed1ac90).
Suite: 461 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
Owner directive 2026-09-06: Dukascopy and similar research material is irrelevant to
the running system; keep only code and files with a role in system functioning.
Deleted (all in git history before this commit):
- backtest/research/ tooling and data: book_report, book_diff, burst_map,
burst_precursors, burst_indicator_map, open_trade_bursts, calendar_impact,
watch_rule_eval, sizing_model, commit_ladder, llm_news_eval + llm_news_golden.csv,
ff_calendar_scraper, duka_spread + duka_spread_by_hour.csv (the Dukascopy spread
study), feed_divergence_oanda_vs_tiingo.csv, the panel dry-test JSONL, __init__.py
- scripts/feed_divergence_study.py, scripts/signal_parity_study.py (completed studies;
their reports keep the results)
- docs/architecture.png + architecture_diagram.py (developer illustration)
- docs/data_source_change_test_plan.md (Phase 4 shadow scan stays noted in CLAUDE.md)
Kept: the campaign .md reports in backtest/research/ as the decision ledger CLAUDE.md
cites (rule 1 evidence); scripts/shadow_scan.py (pending operational step);
backtest/diagnose_filters.py (test-locked backtester diagnostic).
Local, untracked material removed on this box: .superpowers/, walkforward/, baseline/,
the commit-ladder and LLM-eval result folders, the Dukascopy boundary CSV; the
sizing_2026-09 folder is pruned to the four 3-year baseline books CLAUDE.md names.
.gitignore no longer lists the removed research outputs; the backtest instructions
and CLAUDE.md no longer point at deleted tools.
Suite: 461 passed, 0 failed (nothing imported the removed files).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
- test count 461 / 31 modules
- main.py --timeframe accepts M5/M15/H1/H4 and takes confirmation TFs from the
pair factory's map
- point the dual-cost note at the Dukascopy study that produced the $0.65
figure (duka_spread.py is evidence, not dead code)
- current-state note listing what the cleanup removed
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
Removed (all recoverable from git history):
- llm_provider_switch_plan.txt: 2026-08-08 DeepSeek/Anthropic multi-provider plan that
was never implemented (llm_client.py is DeepSeek-only, no `anthropic` anywhere)
- docs/superpowers/specs/2026-07-21-centralized-config-design.md: spec of the
config.json migration that merged the same day; its plan sibling was already
deleted in b936d44. app_config's docstring pointer goes with it.
- scripts/compare_oanda_tiingo.py: Phase 0 recent-tail smoke test, superseded by the
Phase 1/2 study scripts (result recorded in the test plan)
- backtest/research/fetch_oanda_m15.py + oanda_td_divergence.py + its by-hour CSV:
the 2026-07-24 Oanda-vs-Twelve-Data study, superseded by the 2026-08-14 feed
divergence report (which keeps a one-line citation)
- backtest/research/burst_profile.py and hour_analysis.py: superseded by burst_map.py
and book_report.py
- backtest/research/panel_payload_drytest_2026-08-15.py: one-off live DeepSeek probe;
its .jsonl evidence stays
Added to git: the three 2026-08-14 research reports (feed divergence, re-pin
verification, signal parity), their CSV, and docs/data_source_change_test_plan.md -
CLAUDE.md cites them as standing evidence and their driver scripts were already
committed. The test plan no longer refers to auto-execution.
Hygiene:
- .gitignore: drop oanda_state.json (daemon removed 2026-09-03) and the vanished
backtest/trailgrid dirs; ignore .coverage
- docs/architecture_diagram.py only writes the PNG when run as a script (it used
to plot on import); test box refreshed to 461 tests / 31 modules; PNG regenerated
(the committed one still drew the removed daemon)
- backtest/instructions_for_backtest.txt: manual-journal head replaced by the
actual reporting checklist; the 2026-09-06 addendum is unchanged
- doc drift: README/publisher list all six published files; news_summary.php says
4 h (not 24 h) and drops the pre-id sha1 fallback whose window closed;
analyze_signal_log lists six lenses and --scan-outcomes; agent_panel cost model
says 4 requests by default; tiingo comment cites the NY-anchored weekend;
Module 21 title no longer says "execution lifecycle"
Suite: 461 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
Every live reader of a pip value goes through PAIR_INFO[...]["pip_value"]
(signal_aggregator, gpu_backtest, diagnose_filters) or TradeSetup.pip_value;
no code read the PlatformConfig field. The three PlatformConfig(...)
constructions that passed it (gpu_backtest x2, diagnose_filters) and the
inline construction in the factory-equivalence test drop the kwarg. Neither
config fingerprint hashes the field, so logged fingerprints are unchanged.
The removed-field test now also asserts pip_value stays gone.
Parity: 12-month M5 and H1 books regenerated byte-identical
(md5 a28fed4becd056466c26d6a947e1a0e5 / d20405ef64f069770c258bb9bed1ac90).
Suite: 461 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
- analyze_pair(context=...): no caller ever supplied it (main, telegram_bot,
pair_signals, tests), so the value was always None; the parameter and the
pass-through to analyze_from_dataframes go (analyze_from_dataframes keeps
its own context parameter).
- The three specific "SELL FILTER: quality|volatility|regime" stale-prefix
entries were shadowed by the general "SELL FILTER: " entry in the same
startswith() tuple; every emitter carries the general prefix.
- chart_patterns: the detectors never read the Open series, so the `o`
parameter is dropped from the three detectors, the PATTERN_DETECTORS
lambdas and the dispatcher.
- Corrected the pb_funnel/cp_funnel comment: nothing reads those counters
(the "read by backtest tooling" claim was stale); they stay as cheap
diagnostics.
Parity: 12-month M5 and H1 books regenerated byte-identical
(md5 a28fed4becd056466c26d6a947e1a0e5 / d20405ef64f069770c258bb9bed1ac90).
Suite: 461 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
result._kc_squeeze / result._kc_squeeze_released were assigned by both the live
TechnicalEngine and the backtester's GPUTechnicalEngine and read by nothing:
the only four occurrences in the repo were the assignments. The squeeze state
still feeds the Keltner signal text where it is computed. Removed from both
engines in one commit (rule 4).
Parity: 12-month M5 and H1 books regenerated byte-identical
(md5 a28fed4becd056466c26d6a947e1a0e5 / d20405ef64f069770c258bb9bed1ac90).
Suite: 461 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
main.py kept a private confirmation table and passed it into the pair factory,
which honours any non-None list. For M5 that table said [M1, M15] while the
factory, telegram_bot.TF_CONFIRMATIONS and dashboard_publisher.CONFIRMATIONS
all use the validated [M15, H1] - so `main.py --timeframe M5` scanned with an
unvalidated pairing (and an extra M1 fetch) that no other surface used.
- build_config now returns PAIR_PRODUCERS[pair](tf, None): the factory map is
the single source of truth. The unreachable bare-PlatformConfig fallback is
gone here and in telegram_bot._run_signal_sync (every symbol that reaches
either is registered).
- --timeframe offers the four validated primaries (M5, M15, H1, H4). M30 and
D1 were never validated and silently fell through to the generic [M15, H4]
map; they are removed from the CLI.
- The "all valid timeframes" test now asserts each CLI timeframe's
confirmation list equals pair_signals.xauusd._CONFIRMATIONS - the check
that would have caught this.
CLI behaviour change: M5 confirmations [M1, M15] -> [M15, H1]; M30/D1 rejected.
Bot and dashboard scans are unchanged.
Suite: 461 passed, 0 failed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
- telegram_bot._format_scan_summary: multi-pair "auto-scan summary" leftover;
production sends per-report format_signal_message. Its only caller was a test.
- telegram_bot.scan_keyboard: thin wrapper only a test called; main_menu_keyboard
already builds from _scan_button_rows directly.
- telegram_bot.AUTOSCAN_CONFIRMATIONS was byte-identical to TF_CONFIRMATIONS;
the candle loop now reads the one map (app_config comment updated).
- SignalLogger.news_for: one-line wrapper over the module-level read_news that
every real reader uses; the test now calls read_news like its neighbours.
- pair_signals.get_supported_pairs: PAIR_PRODUCERS is the registry; the test
lists it directly.
Suite: 461 passed, 0 failed (two helper-only tests removed).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
Zero callers anywhere (tests included), verified by grep/AST:
- dashboard_publisher.DashboardPublisher.publish_all (run_cycle inlines both publishes)
- signal_log.SignalLogger.advance_with_bars (the backfill script uses
backfill_seeds / resolve_from_store / reseed_unresolvable) and the never-read
SignalLogger.path property plus its write-only self._path
- llm_client.reset_llm_client (tests reset the singleton by assignment)
- market_outlook._last_run_ts, residue of the old "now - last < 3600" dedup;
_last_run_hour (the UTC hour bucket) is the live key
- news_engine FundamentalContext.event_impact_on_pairs: written once, read by
nothing; its only feeder NewsEngine._get_affected_pairs and that helper's
unit test go with it
- position_sizing.LIVE_DEPTH_BARS (referenced only by its own docstring, which
now states the depths inline), the unused Iterable import and the unused
atr_ok parameter of _fill_geometry
- analyze_signal_log: unused `field` import and the unused `rows` parameter of
persona_scorecard / news_outcome_buckets (both read the DB directly)
The two backfill/label scripts' --db help text now names the config.json
setting it actually falls back to.
Suite: 463 passed, 0 failed (one test removed with its subject).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
- backtest/diagnose_filters: unused BacktestConfig import
- pair_signals/__init__: unused PlatformConfig import
- scripts/shadow_scan: unused pandas import
- research burst_precursors / calendar_impact / duka_spread: unused sys / COST / struct
- test_all: MagicMock, StringIO, Colors and two function-local imports that
nothing in the test bodies used
- telegram_bot: ViolentWatch is only a type hint -> imported under TYPE_CHECKING
compare_oanda_tiingo.py and oanda_td_divergence.py are left alone here because
the hygiene commit deletes them.
Suite: 464 passed, 0 failed (unchanged).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL
The candle provider needs only oanda.api_token + base_url; account_id belonged to the
auto-execution daemon removed 2026-09-03 (31002cb). Removed from config.json.example and
the unused oanda_account_id() accessor deleted; the key stays in _KNOWN_OANDA so existing
config.json files keep loading. CLAUDE.md env-var list updated. Test locks all three.
Suite: 464 passed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
- test count no longer hardcoded (463 / 31 modules as of 2026-09-06)
- main.py --outlook, backtest --set / --export-features listed
- delivery surfaces include the web dashboard; SignalReport consumers include the publisher
- scikit-learn / lightgbm are research-only venv installs, never requirements
- rule 1: owner preference (2026-09-05) that backtests go back at most 3 years, with the
3-year baseline books and where they live
- "Current state notes" header un-dated; the 2026-08-14 canonical-book line marked superseded
by the 2026-09-03 book (M15 reference unchanged since 2026-08-04)
- docs: PDF builds noted as behind the HTML guides
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
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).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
Walk-forward "second opinion" stake multiplier (meta-labelling on 65 decision-time
features, 3yr Oanda books @ $0.65) FAILED the pre-registered rule on M5 (clean null)
and M15 (lift inside the label-shuffle null, explained by BUY-vs-SELL). Nothing that
changes numbers ships; the 12-month M5 book re-run is byte-identical to the pinned one.
Behaviour-neutral plumbing:
- position_sizing.build_features (65 features; multiplier path returns 1.0, no artifact)
- SignalReport.penalty_tags / penalty_total / momentum_fading (record-keeping)
- TradeSetup.stake_multiplier = None (reserved)
- gpu_backtest --export-features (default export stays the pinned 63 columns; extras
forced to the tail even when the first trade lacks an indicator)
Research tools (backtest/research): book_report, burst_map, burst_precursors,
open_trade_bursts, calendar_impact, burst_indicator_map, sizing_model, watch_rule_eval.
Findings recorded in backtest/research/sizing_campaign_2026-09.md: M5 stretch measures
are positive in both halves; every open-trade protection against violent bars loses on
both TFs; high-impact USD releases cause 20-31% of violent bars but trades held through
them do better; violent bars come when price is already at an extreme, not from calm.
Module 29 tests (13). Suite: 435 passed.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
None of these touch the signal path. The 12-month M15 book
(2024-03-31..2025-03-30, $0.65, cached Oanda bars) is byte-identical
before and after (md5 c59d3e7e685c3c880b614640adfea74b, 375 trades),
and signal/indicator logging to logs/signals.db is unchanged — verified
end to end: per-TF indicators for all 3 TFs, 14 candles each, MTF and
reasons all still persisted.
agent_panel: the >=2-take quorum guards the CHAIR's synthesizer spend,
but ran BEFORE the macro branch — so the shipped default
(verdict_source="macro", which never calls the synthesizer) silently
dropped a good macro verdict whenever the other three personas were
slow. Quorum moved below the macro path.
analyze_signal_log: _forward_return clamped to the last available bar
when the horizon had not elapsed, reporting a near-zero "forward move"
for every row logged within `hours` of the end of the data — on every
run, blended into the hit-rate/mean-move aggregate. Now returns None.
analyze_signal_log: persona_scorecard iterated raw rows through an index
that maps EVERY member row of an event, so a re-logged scan appended
the same event R twice. One vote per event, matching
news_outcome_buckets. Measured inflation on the live DB: 1.03x.
signal_log: dedup required a non-negative logged_at gap, but logged_at is
stamped before the row wins the write lock (busy_timeout 5 s), so two
processes logging one setup at a boundary can invert timestamp order
against id order and seed a second event. Now abs(gap); same in
backfill_seeds. Zero occurrences in the current 366 setup rows.
advisory_outcome: the catch-all turned real evaluator faults into the
same UNRESOLVABLE used for legitimate weekend gaps, with nothing in the
log. Still fail-safe, now logged.
llm_client: only the "cap" warn-once flag was ever reset, so in a daemon
the second and every later network/http/parse outage logged at DEBUG
only. Cleared on UTC-day roll and re-armed by a recovered call.
dashboard.js: renderCards() redraws the selector for every timeframe but
was gated on the SELECTED one changing, leaving the other buttons stale
(up to 4 h on H4) while renderHero's rail already showed the new value.
news_summary.php: atomic_write treated a short write (disk full) as
success, publishing a truncated body the cache-first branch then served
forever; and the daily cap was charged before the no-key check and
before the stampede lock re-checked the cache, so a click burst could
exhaust the 150/day budget with zero LLM calls.
migrate_signal_log_news: logged_at is ISO with 'T' while SQLite's
datetime() uses a space, so string-comparing them put the whole cutoff
calendar day on the wrong side and it never pruned. NOTE: this now
deletes one day more than before — it only runs when invoked by hand.
Tests 414 -> 422 (new Module 28, one per fix). The existing
"<2 valid takes" test was retargeted at the chair — the case it actually
protects — rather than deleted, with new coverage for macro-alone.
Not fixed, recorded for the owner:
- Gate 6c's boost condition is textually identical to the C-grade
definition, so every C in a "transitioning" regime is promoted to B
before gate 6e reads it, making sell_min_quality's exclusion of "C" a
no-op on M15/H4 (H1 and M5 are immune by other means). The backtester
runs the same code, so every pinned book already includes this —
changing it is a rule-1 revalidation event.
- Safe-haven/geopolitical headlines score exactly 0.00 in the keyword
fallback and are now dropped entirely by the ±0.1 neutral filter,
contradicting the platform's own gold doctrine. Bites only when
DeepSeek is capped/disabled/failing.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ah5EB1goi5inQmSd37Ne6a
Verdict from the 3-week signal log (backtest/research/news_sentiment_value_2026-09-04.md):
news_sentiment is a trailing-24h echo of price (r +0.67 with the past day, +0.03 with
the next; most bullish 2 h after the 08-25 top, bearish 44 h later; most bearish at the
09-02 low, bullish 16 h later). Per-headline LLM labels are correct; the 12 h pool and
the averaging are what destroy the information. Both gating flags stay False.
- news_engine: _LLM_SUMMARY_SYSTEM rewritten for someone who has never traded (no
acronyms, two worked examples); summary payload newest-first with the platform's own
gold direction; reply cap 300 -> 400 chars.
- config: headline_max_age_seconds 43200 -> 14400; RSS items without a parsable
pubDate are dropped (they used to be stamped "now" and never aged out).
- news_engine.get_fundamental_context drops headlines whose every relevant score is
inside +-0.1 (_is_neutral_headline) before the per-currency mean; news_sentiment
from this date is a mean over directional <=4 h headlines (log comparisons split here).
- static: dashboard copy for the 4 h pool; news_summary.php prompt gets the same style rule.
- analyze_signal_log: --news (under --stored-candles) prints sentiment lead/lag with
split halves, sentiment at the window high/low with flip lags, and outcome buckets by
direction x news x macro stance; LogRow gains news_sentiment/event_risk; _row_index shared.
- tests: 406 -> 414 (age window, undated drop, neutral filter, summary prompt/payload/cap,
--news helpers, load_rows round-trip); RSS fixtures now carry a pubDate.
- docs: user/beginner guides, CLAUDE.md, deploy README.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0169BgFtWjp1SEAa5392Q9jH
agent_panel.verdict_source defaults to "macro": the macro take's stance is the
verdict, the synthesizer call is skipped (4 LLM calls per panel instead of 5);
"chair" restores the four-voice consensus + OPPOSE guard. Verdict source is
cached per mode and logged (panel_verdict_source). 406 tests.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FC4s6VCURFte4dub4xKxYL
Deletes oanda_daemon.py, oanda_executor.py, their 28 tests and the daemon-only
config keys (oanda.lot_size/quality_gate/max_hold_bars). The Oanda data
provider and credentials stay — it is the live candle feed. 402 tests.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FC4s6VCURFte4dub4xKxYL
Harwinder Sekhon