- InstrumentChart: remove setMarkers arrowDown (level-colored)
Add DOM overlay div with ★ HTML characters positioned via timeToCoordinate +
priceToCoordinate(candle.high) - 52px; sized by impact_score; colored by category
Label (title, 22 chars) rendered above each star; redrawn on scroll/zoom via
subscribeVisibleLogicalRangeChange; cleaned up on unmount
ChartEvent interface: add category, impact_score, end_date, description
Header legend: replace ▼ LT/MT/CT with ★ category color legend
- InstrumentDashboard: remove EventStarsStrip (now internal to chart)
Remove unused dateToMs helper
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add macro_regime (goldilocks/stagflation/recession/etc.) to every instrument snapshot via get_macro_gauges() + score_macro_scenarios()
- RegimeCard now shows global macro cycle section (emoji + label + top-3 scenarios) above technical signals
- Fix _detect_regime() confidence: capped at 85% max; add late-bull (dist_MA200 > 20%) and correction-in-bull (MA50 > MA200 but momentum < -3%) detection so regime no longer locks at 100%
- Add macro_events_bootstrap.py with 30 curated historical events (FOMC 2022-2025, CPI surprises, Ukraine/Hamas/Iran geopolitics, BOJ pivots, Bitcoin ETF, Liberation Day tariffs, SVB crisis, etc.)
- POST /api/timeline/bootstrap-macro endpoint (idempotent, deduplicates by name)
- Fix event date filter in _get_relevant_events(): overlap logic instead of start-only filter — events extending into the chart window are now included
- EventTimelineStrip: add "Signaux Techniques" fallback row for events not matched by any driver keyword (MA crossovers are now always visible)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- instruments.json: add keywords array to every driver across 20 instruments
(Fed, BCE, BOJ, OPEC, CPI, AI, EIA, etc.) for event-to-driver matching
- instrument_service.py: add update_instrument_drivers() persisting changes to JSON
and refreshing in-memory cache
- instruments.py: add PUT /api/instruments/{id}/drivers endpoint (DriverUpdate model)
- InstrumentDashboard:
* RegimeCard: replace regime score bars with 6-metric signal grid
(MA50/MA200 position, MA50 slope, MA200 slope, momentum 20j, dist MA200, ATR vol ratio)
with colour-coded values and contextual sub-labels (Golden cross, Surextension, etc.)
* EventTimelineStrip: rows now keyed by top-4 instrument drivers (by weight)
instead of LT/MT/CT; events matched via case-insensitive keyword scan against
title + description + category; fallback dashed line when no events match
* DriversPanel: inline edit panel (toggle via Drivers button in header);
edit label, weight, keywords (comma-separated) per driver; add/remove drivers;
saves via PUT /api/instruments/{id}/drivers; optimistic local state update
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- InstrumentChart: onDateHover callback via subscribeCrosshairMove (useRef pattern)
- EventTimelineStrip: 3 rows LT/MT/CT with CSS-% bars aligned to chart X axis
- Cards date-aware: crosshair drives selectedDate; dateTrend + dateSignals computed
client-side from lookup maps (priceMap/indMap/sortedDates) without extra API calls
- TrendCard: price, RSI, ATR, slopes, momentum, 52W range all at selected date
- RegimeCard: 5 signals recomputed at selected date; regime label from server
- Date badge above cards; blue tint when browsing history, grey on last date
- instrument_service.py: end_date in events; price_data built before events block
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- TimelineVertical: replace horizontal frise with Y=time vertical layout,
3 columns (Long/Medium/Short), auto-scroll to selected date, sub-columns
for overlapping events, today/selected-date horizontal lines
- ma_analyzer.py: detect MA50/MA200 crossovers + MA100 slope changes +
MA20 direction swings on EUR/USD, Brent, Gold, S&P500, US10Y (5y history)
with 5-bar confirmation, dedup, GPT-4o-mini enrichment, idempotent DB save
- POST /api/timeline/bootstrap-ma endpoint to trigger analysis
- Bootstrap MA button in Timeline page with loading state + result count
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Frise chronologique:
- Sub-lane stacking (assignSubLanes) — overlapping events se décalent verticalement
- Zone d'overlap semi-transparente sur la période commune entre 2 événements
- Hauteur dynamique selon nb de sub-lanes par niveau
- Événements en cours avec flèche ▶ à droite, gradient de fin
- Tri par start_date pour placement greedy
Event Manager (composant EventManager.tsx):
- Tableau filtrable par niveau (Long/Moyen/Court)
- Edit modal complet : tous les champs + absorption_pct éditable
- Bouton "IA — Enrichir" par événement → POST /api/timeline/events/{id}/ai-enrich
→ GPT-4o-mini suggère absorption_pct + indicateurs pertinents par niveau temporel
- Delete avec confirmation double-clic
- Expand row pour voir description + indicateurs
- Intégré Timeline page via bouton "Gérer événements"
Backend:
- Nouvelles colonnes market_events: absorption_pct + relevant_indicators (ALTER idempotent)
- DELETE /api/timeline/events/{id}
- POST /api/timeline/events/{id}/ai-enrich
Snapshot Externe:
- AbsorptionBar par événement dans cellule Géopolitique
- MA indicators : fetch 200j history, compute MA10/MA20/MA100 per level (short/med/long)
- Affichage prix vs MA + % écart dans CellMarkets
- Si relevant_indicators configurés sur l'event → utilise ces symbols au lieu des défauts
- Calendar : horizons exclusifs (short 0-7j, medium 8-30j, long 31-90j) — bug corrigé
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Remplace le 2×2 indépendant par une matrice cohérente avec le concept E1/E2/E3 :
- 3 lignes (Long/Moyen/Court), chacune ancrée sur l'événement actif de ce niveau
- 4 colonnes (Géopolitique / Prix & Marchés / Régimes Macro / Calendrier)
- Assets affichés dans la colonne Prix filtrés selon affected_assets de l'événement
- Barres macro normalisées sur max score (overflow corrigé, overflow-hidden)
- Calendrier filtré par horizon temporel (7j / 1M / 3M) selon le niveau
- En-têtes colonnes globaux pour lecture matricielle immédiate
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Les appels fetch vers http://localhost:8000 ne fonctionnent pas en déploiement
Docker — remplacé par axios avec baseURL='/api' comme le reste de l'app.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Backend: category filter now ORs signal column so multi-category reports (category='multi') appear when filtering by Forex/Energy/Metals/Indices — fixes blank results
- Frontend: category pills expanded to match desk taxonomy (agri, crypto, bonds, indices added; equities kept for compatibility)
- Frontend: banner pointing to /specialist-desks clarifies the split between auto-fetched reports and manual desk report scheduling
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- handleSave now shows a red toast "Lancez d'abord un backtest" instead of
silently returning when activeRun is null (was completely invisible to user)
- All toasts now color-coded: green (emerald) for success, red for errors
- list_runs now includes context_snapshot so market data table shows when
loading a historical run from the right panel
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add ability to add/remove custom tickers (e.g. EURCHF=X) on the
Markets & Prices page without editing config. Tickers are validated
via yfinance, persisted in market_watchlist SQLite table, merged into
the quotes feed as a 'custom' group, and shown in a dedicated tab
with per-card remove buttons.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Fix: history runs now always show results — create synthetic selected preset
from run data when no matching preset found (was broken for custom events).
Also force mode='events' and reset matchResults on history load.
Discover tab: new "Discover" panel in left sidebar (AI knowledge search).
- GPT-4o generates 6 matching events from a free-text query (date, assets, hint)
- Confidence score + category badge per event
- Click → pre-fills experiment form exactly like a preset → ready to Run
- Backend: POST /api/pattern-lab/discover (DiscoverRequest, sorted by confidence)
- Frontend: useDiscoverEvents hook + DiscoveredEvent type + Discover UI with
Enter-to-search, spinner, empty states
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Backend: PATCH /api/patterns/custom/{id} — partial update, only provided fields changed
- useApi.ts: usePatchPattern mutation hook
- PatternCard: pencil icon (non-builtin only) → edit mode with inline inputs for name, description, direction (select), category, and #regime; ✓/✗ buttons to save or cancel; card border highlights blue while editing
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Missing class caused native selects to render with OS default white background.
Added .input to @layer components with dark bg, border, color-scheme:dark.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Backend:
- GET /api/market/validate?symbol= — validates ticker against yfinance,
returns {valid, name, price} or {valid: false, reason: 'helpful message'}
- Added SLV, USO, WEAT, CORN, TUR to ETFs WATCHLIST category
Frontend:
- validateTicker() async helper exported from useApi.ts
- InstrumentPicker (PatternLab): custom ticker field now validates before selecting
Shows spinner while checking, red error message if not found on yfinance
- InstrumentLens (PatternExplorer): same validation on Go button + Enter key
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- New 'etfs' asset class in WATCHLIST: 18 key ETFs used in Pattern Lab presets
(SPY, QQQ, IWM, TLT, IEF, HYG, GLD, EEM, FXI, EWG, EWJ, EWU, EWZ,
XLF, SMH, KWEB, UUP, BIL)
- Added 'etfs' tab between Indices and Equities in Markets page
- Extended AssetClass union type to include 'etfs'
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Backend: DELETE /api/patterns/purge-all — removes all custom + backtested patterns
(source != 'builtin'), leaves Pattern Lab run history intact.
Frontend Config > Data Management:
- New PurgeButton for Pattern Library (custom_patterns table)
- Updated note: Trade Ideas are computed live from the Pattern Library (no separate table),
so purging patterns resets trade idea generation on next cycle.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Backend (pattern_lab.py):
- Replace binary HIT/MISS with FULL / PARTIAL / MISS scoring
FULL: right direction AND ≥ 50% of expected move
PARTIAL: right direction AND ≥ 15% of expected move (was always MISS before)
MISS: wrong direction or negligible move
- Add direction_correct, direction_ratio, hit_type fields to all outcomes
- Add Black-Scholes ATM options P&L simulation (_bs_price, _ncdf, _sigma_for)
Normalised to S₀=K=100, per-asset-class vol heuristic (FX 8%, indices 16%, crypto 65%)
Supports: long call/put, straddle, strangle, call spread, put spread
- estimated_options_pnl_pct shows what the strategy would have returned
Frontend (PatternLab.tsx):
- OutcomeRow component: FULL HIT (green) / PARTIAL (amber) / MISS (red)
- Shows direction tick/cross + ratio % of target achieved
- Shows estimated options P&L with DollarSign icon
- Hit rate header shows full hits + partial count separately
- Card border: emerald = full, amber = partial, red = miss
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- instruments.ts: 90 IB-options-tradable instruments in 12 categories
(US Indices, Europe, Asia, EM, Sectors, Forex, Bonds, Metals, Energy,
Agriculture, Crypto, Volatility) — EUR/CHF, Cotton, etc. all included
- PatternExplorer: replace text input in Instrument Lens with categorised
grid picker (category pill filters + search + custom ticker fallback)
- PatternLab: add Instrument Scan tab alongside Event Presets
- Pick any instrument from the shared categorised picker
- Set period (start/end date) + horizon per pattern
- AI scans the full period: identifies 4-6 key pattern instances each with
their own entry date, expected move, strategy
- 'Evaluate outcomes' fetches actual price at T+horizon per pattern
- 'Save pattern' promotes any instance to the Pattern Library
- backend/services/pattern_lab.py: run_instrument_scan() + evaluate_instrument_outcomes()
(per-pattern analysis_date vs shared date in event mode)
- backend/routers/pattern_lab.py: POST /instrument-scan + POST /evaluate-instrument/{id}
- useApi.ts: useInstrumentScan + useEvaluateInstrumentScan hooks
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Remove all built-in patterns (no proof of legitimacy); seed_builtin_patterns is now a no-op
- DB: add backtest_lab_runs table + backtest_hits/runs_count columns on patterns
- services/pattern_lab.py: build_historical_context (yfinance + RSI/MA200),
run_ai_backtest (GPT-4o as historical analyst), evaluate_outcomes (actual moves at T+horizon)
- routers/pattern_lab.py: POST /run, POST /evaluate/{id}, GET /runs, DELETE /runs/{id},
POST /save-pattern (promotes hit pattern to library with reliability counters)
- PatternLab.tsx: 34 preset events 2015-2025 (macro/geo/credit/fx/commodities/volatility/tech),
3-panel layout — preset selector + wizard + run history, market data table,
AI pattern cards with hit/miss outcome display, Save to Library button
- useApi.ts: usePatternLabRuns, useRunPatternLab, useEvaluatePatternLab, useSaveLabPattern, useDeleteLabRun
- Sidebar + App.tsx: /pattern-lab route + FlaskConical nav link
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- database.py: add trade_budget_eur / preferred_horizon_min/max config
defaults and include them in cycle config migrations
- auto_cycle.py: read trade params from config and inject into cycle_meta
- ai_analyzer.py: inject INVESTOR TRADE MANDATE block into scoring and
suggestion prompts so GPT-4o penalises horizon mismatches and sizes
within the capital cap
- Config.tsx: Trade Parameters card with budget + horizon sliders and live
mandate summary
- TradeIdeas.tsx: horizon filter pills (< 1M / 1-3M / 3-6M / > 6M) and
budget/horizon indicator pulled from saved config
- useApi.ts: extend useUpdateCycleConfig type with new config fields
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Sort dropdown: AI Score / Probability / Expected Move / Date Added
- Category filter pills auto-populated from patterns in current node
- CategoryBadge component with colored pills (matches Trade Ideas palette)
- AI score shown top-right on each pattern card
- Changing taxonomy node resets category filter
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
enrichTree was building paths starting with 'root', but patterns store paths
like ['geopolitical', 'armed_conflict', ...] — no root prefix. Fix: start
enriching root children with parentPath=[] instead of ['root'].
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The taxonomy endpoint returns {tree, patterns} but the component was casting
the whole response as the root node. Also added enrichTree() to attach computed
path arrays to each node (backend PATTERN_TAXONOMY has no path field).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- economic_events table in DB (series_id, actual, forecast_baseline, surprise_pct, surprise_zscore, direction)
- DB helpers: save_economic_event(), get_recent_economic_surprises(), get_economic_events_for_calendar()
- fred_fetcher.py: _compute_zscore_surprise() computes 12-period MA as implied consensus + z-score deviation; save_fred_releases_to_db() persists releases per cycle; build_economic_surprise_block() formats significant surprises for AI prompt
- auto_cycle.py: saves FRED releases to economic_events each cycle, appends surprise block to fred_block for injection into both suggestion and scoring prompts
- data_fetcher.py: get_economic_calendar() now merges static upcoming events with past FRED actuals from DB (Prev/Fcst/Actual/z-score fields populated)
- CalendarPage.tsx: past events show colored z-score badge (⚡ for |z|≥1.5, bullish/bearish colors)
- EconomicEvent type: added surprise_zscore, surprise_direction, source fields
Activates automatically once fred_api_key is set in Configuration.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- New institutional_reports table (DB) with importance, signals per asset class, key points, absorption tracking
- cot_fetcher.py: CFTC Socrata API (6dca-aqww), 7 instruments (Gold/Silver/Copper/WTI/NatGas/SP500/EURUSD), net positioning + 52-week z-score
- eia_fetcher.py: EIA API v2, 4 series (crude/Cushing/gasoline/distillates), WoW surprise detection
- institutional.py router: GET /reports, GET /reports/{id}, POST /refresh, GET /stats
- institutional_scheduler.py: weekly auto-fetch (COT Saturdays, EIA Wednesday afternoons)
- ai_analyzer.py: build_institutional_block() + institutional_block param injected into AI scoring prompt
- auto_cycle.py: inject institutional block into suggestion + scoring, absorption tracking via keyword overlap after each cycle commentary
- InstitutionalReports.tsx: full page with filter bar (type/category/importance/period), cards with key point bullets, EXTREME alerts highlighted, signal badges, absorption badge, trading implications, expandable detail
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Complete French→English translation across all frontend pages and backend
services — every label, button, header, empty state, toast, and nav item
is now in English. Build verified clean (tsc + vite). No i18n library
added; direct string replacement throughout.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- auto_cycle.py: _scheduler_loop now distinguishes weekday (interval_hours)
from weekend (weekend_cycle_times UTC slots or sleep until Monday);
_parse_weekend_times() and _next_weekend_slot() helpers;
get_status() exposes weekend_cycle_enabled + weekend_cycle_times
- cycle.py: CycleConfigRequest adds weekend_cycle_enabled + weekend_cycle_times;
update_cycle_config validates HH:MM format and persists to config DB
- Config.tsx: weekend scheduling section with enable toggle + time picker
(06:00/08:00/12:00/18:00/22:00/00:00 UTC presets, multi-select);
weekendEnabled + weekendTimes state synced from cycle status
Default: enabled with 08:00 + 22:00 UTC (covers news scan + Globex open Sunday)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Portfolio context (portfolio_context.py):
- get_open_trades_with_moves(): fetches open trades + 1d/5d yfinance price moves
- get_portfolio_concentration(): counts by asset_class
- build_portfolio_context_block(): formatted prompt block with strict AI instructions
(no double positions, flag contradictions, avoid overweight classes)
AI call logging:
- ai_call_logs table in DB (run_id, call_type, system/user prompt, response, tokens, ms)
- _chat() now accepts log_meta dict → saves call to DB non-blocking after each call
- suggest and score_batch calls pass run_id + call_type for full traceability
auto_cycle.py:
- Builds portfolio context before snapshot and both AI calls
- Context snapshot now includes portfolio_open_positions key
SystemLogs.tsx:
- "Contexte IA" tab gains sub-tabs: Contexte / Appels IA
- AiCallRow: expandable with 3 panes (user prompt / system prompt / response)
shows model, tokens breakdown, duration, call type badge
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- _normalize_asset_class() now accepts ticker param and infers class from
a full ticker→class lookup table (energy/metals/agri/indices/equities/forex)
- init_db() runs one-time UPDATE to backfill all NULL asset_class rows in
trade_entry_prices and skipped_trades using known ticker lists
- log_trade_entries and log_skipped_trade pass ticker to normalizer
- Frontend _normalizeAssetClass() gets same ticker lookup + pattern fallbacks
for =F futures, NSE: prefixed equities, =X currency pairs
- All 3 filter calls now pass t.underlying as second argument
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Direction (Ouvert) : t.direction n'existe pas dans trade_entry_prices → utilisait
undefined, excluait tout. Remplacé par _isBearishStr(t.strategy) comme Fermés.
Asset class (Ouvert, Fermés, Non loggés) : l'IA retournait parfois "commodities",
"currencies", "fx", "equity" au lieu des clés canoniques. Double correction :
- Frontend : _normalizeAssetClass() mappe les variantes → energy|metals|agriculture|
indices|equities|forex dans les 3 sections filtrées
- Backend database.py : _normalize_asset_class() appliqué à l'INSERT dans
trade_entry_prices et skipped_trades (nouveaux trades normalisés au stockage)
- Prompt ai_analyzer.py : suggested_trades[].asset_class contraint à l'enum explicite
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Phase 4 — Price Discovery Status (la pièce maîtresse) :
- price_discovery.py (nouveau) : capture_price_snapshots() sauve les prix des tickers
liés à chaque news scorée (energy→BZ=F/NG=F, metals→GC=F/HG=F, indices→^GSPC/IWM)
- compute_absorptions() mesure combien du mouvement attendu s'est déjà produit
(status: not_yet_priced <30% / partially_priced 30-80% / fully_priced >80%)
- build_price_discovery_block() → bloc prompt avec opportunités classées
- database.py : table news_price_snapshots + save/get/purge fonctions
- auto_cycle.py : capture après ai_score_news_batch, compute avant suggestions,
block injecté dans suggestion + scoring prompts + context snapshot
- ai_analyzer.py : param price_discovery_block dans suggest + score
Phase 5 — Replay historique :
- cycle.py : POST /api/cycle/contexts/{run_id}/replay — recharge le snapshot historique
et relance suggest_patterns_from_market_context avec le contexte original
- useApi.ts : hook useReplayCycle
- SystemLogs.tsx : bouton "Rejouer ce cycle" dans onglet Contexte IA avec champ
notes, résultats inline (liste des patterns générés), section price_discovery
ouverte par défaut en rouge
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Phase 2 — Données macro FRED :
- fred_fetcher.py (nouveau) : 7 séries FRED (CPI, NFP, UNRATE, FEDFUNDS, GDP, ICSA,
spread 10Y-2Y) avec détection direction bullish/bearish et block prompt formaté
- ai_analyzer.py : param fred_block dans suggest + score, injecté dans les deux prompts
- auto_cycle.py : fetch FRED non-bloquant avant la suggestion
Context log — Snapshot du contexte complet :
- database.py : table cycle_context_snapshots + save/get/list fonctions
- auto_cycle.py : sauvegarde le snapshot (meta, news partitionnées, FRED, tech, IV, quotes)
- cycle.py : GET /api/cycle/contexts + GET /api/cycle/contexts/{run_id}
- useApi.ts : hooks useCycleContextSnapshots + useCycleContextSnapshot
- SystemLogs.tsx : onglet "Contexte IA" avec liste de cycles et visualiseur JSON
par section (cycle_meta, macro, news, FRED, tech) avec accordéon
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
