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>
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>
- 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>
- 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>
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>
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>
- Dashboard: P&L card séparé en deux colonnes (Ouvertes/Réalisées) pour Simulé et Portfolio
- Dashboard: closed trades P&L locked from pnl_realized, ne fluctue plus après fermeture
- Journal Ouvert: filtres ticker/stratégie + classe d'actif + direction (haussier/baissier)
- Journal Fermés: mêmes filtres + filtre P&L (gagnants/perdants) + bouton supprimer par ligne
- Journal Non loggés: filtres ticker + classe d'actif + raison de skip
- Backend: DELETE /api/journal/trades/{id} + delete_trade() dans database.py
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Dashboard: insert 2 rows of 4 mini-cards between top row and trade ideas
- Row 1: PnL Simulé, Risque Simulé, Dernier Cycle, Régime Macro
- Row 2: Super Contexte, Signaux Géo, Meilleur Pattern, Patterns Actifs
- All cards link to underlying pages via react-router Link
Journal: add 'Non loggés' tab exposing trades suggested by cycle
but skipped because no risk profile was matched
- New skipped_trades table (auto-created on backend restart)
- log_trade_entries() persists each skip with score/gain/asset_class
- GET /api/journal/skipped-trades + useSkippedTrades hook
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
