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
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
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
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
Validation (llm_news_eval.py harness + 78-headline golden CSV + verdict
doc): headline scoring 78/78 vs keyword baseline 24/78 — validated;
event gold-direction calls misread close K/M numeric comparisons ~11%
of the time (both claims cases in sample, JOLTS 8.79M vs 8.84M).
Fix: event payload now carries code-computed "vs_forecast" (from
EconomicEvent.surprise) and the prompt gains an explicit inverted-
metrics rule + worked claims example — iteration 1 (field alone) fixed
the arithmetic but exposed a masked inversion error. 18/18 on live
re-verification (4 misreads fixed, 11 regression cases clean, 3 fresh
both-side probes).
/status: new "News & AI" section — per-source health for the calendar
chain (which of FF/MyFXBook served), each RSS feed, and DeepSeek
(daily count, last error kind), written passively by the existing
fetch paths under _cache_lock. Failures WARN once on transition
(repeats DEBUG, recovery INFO) so the rotating log carries outage
stories without 10-min spam.
test_all.py: +5 Module 19 tests (351 total); also carries the Module 22
fixed-RR-TP tests from the prior research session (shared file).
Replay artifacts dir gitignored like commit_ladder.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017mbXs9HRawZhD1uZ3ze7zQ
Added: backtest/research/commit_ladder.py (recreates historical configs
via --set on the fixed harness; 2026-08-03 campaign confirmed HEAD is
the best config on all timeframes). Results stay local like all pinned
trade books.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Nsd8HcrV67GbCZXxZEn1Ma
Scripts + summary CSVs for the 2026-07-24 studies (real XAU spread ~$0.65
tradable hours; Oanda vs TD bars diverge ~11% of ATR with 10% direction
flips). Large raw data files (parquet, per-boundary samples) gitignored.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Mc7XKYyPySVXiUpcN82QEK
New independent trading daemon (oanda_daemon.py) that places orders on
an Oanda v20 practice account instead of sending Telegram alerts.
Oanda-only market data (oanda_provider.py, mid candles + real bid/ask
spread) through the unchanged signal pipeline; order execution and
trade management via oanda_executor.py (raw requests, no new deps).
Book parity with the backtester: no broker-side TP (exits = SL/TRAIL/
TIMEOUT only), bar-close-only trail ratchet with each closed bar
processed exactly once, 5-bar per-TF entry cooldown, structural SL
from the setup. Accepted divergence: one position total (skipped
signals logged for book reconciliation).
Safety/ops: fail-fast boot on rejected credentials (transient outages
continue), market orders never retried (double-fill risk), entry lock
against aligned-boundary races, restart recovery + adoption via
oanda_state.json, hourly heartbeat, asyncio exception handler, every
failure path logged. Prices formatted at instrument precision.
Config: env OANDA_* -> config.json "oanda" section (validated in
app_config). Tests: Module 15 (30 tests), suite 240 green.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VUnCqjWBuvKRSjLwHeB9BJ
Parity: replay now applies the live _apply_regime_filter_live method
under the live guard (function-identity, default-off); unregistered-pair
fallback applies the config.json overlay; parity sweep gains direct
ATR/vol-regime assertions; regime-filter semantics test added.
Trail campaign: --trail-arm/--trail-dist research flags; 30-cell grid on
5yr M15 refuted the earlier-arm hypothesis and found the 0.70-0.80 arm
plateau. Shipped M15-only trail_arm_r=0.70 (factory override):
+210.7R PF 1.35 WR 57.8% vs +175.7R PF 1.30 WR 53.9% baseline; both
halves and 2024-06->2025-03 OOS better (+57.4 vs +45.4); 5yr max-DD
clause (33.9R vs 29.1R) explicitly waived by owner. M5 unchanged.
Factory replay reproduces the grid cell trade-for-trade; 201/201 tests.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VPNF37MP9Kuv62B1VBrZ1b
Track gpu_backtest.py, diagnose_filters.py, and instructions.
Data files (CSVs, parquet cache) remain gitignored.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
script.txt was superseded by requirements.txt. Python bytecode should
not be version-controlled — added .gitignore to keep cache and venv
out of the repo going forward.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Harwinder Sekhon