Commit Graph

46 Commits

Author SHA1 Message Date
OpenSquared
f2dd859ba0 fix: PatternLab save UX — color-coded toasts + meaningful error feedback
- 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>
2026-06-22 22:30:47 +02:00
OpenSquared
33097e1812 fix: custom tickers now placed in their natural asset-class tab
- Detect yfinance quote_type (CURRENCY→forex, FUTURE→energy, INDEX→indices,
  ETF→etfs, EQUITY→equities) when adding a custom ticker and persist it in
  market_watchlist.asset_class
- get_all_quotes() merges custom tickers into their proper group (e.g. EURUSD=X
  appears under Forex) instead of always under a separate "Custom" group
- "Custom" tab only shows tickers whose type couldn't be detected
- Add market_watchlist.asset_class migration; ensure backtest_lab_runs and
  market_watchlist are always created at init_db() time

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-22 22:11:31 +02:00
OpenSquared
c3ea0b7f8c feat: dynamic market ticker watchlist (Markets page)
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>
2026-06-22 21:54:58 +02:00
OpenSquared
78c60d5254 feat: Pattern Lab Discover + fix history run display
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>
2026-06-22 21:36:00 +02:00
OpenSquared
a2315c3b78 feat: inline edit for patterns in library (name, description, category, direction, regime)
- 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>
2026-06-22 21:13:34 +02:00
OpenSquared
a435c11246 feat: regime system — Find Matching + By Regime view
- Pattern Lab: "Find Matching" button per pattern uses GPT-4o-mini to classify against library (merge_as_instance / counter_scenario / new_pattern); shows match badge + confidence + suggested #regime_tag; conditional action buttons (Merge / Save counter / Save new)
- save_pattern_from_run handles action='instance' (appends to historical_instances + updates stats), action='counter' (new pattern with counter_of link, tags parent regime_tag), action='new' (unchanged + regime_tag support)
- useApi.ts: extended useSaveLabPattern type + new useFindMatchingPattern mutation + MatchResult export type
- DB migrations: regime_tag + counter_of columns on custom_patterns
- PatternExplorer: new "By Regime" view groups saved patterns by regime_tag; RegimeCard shows historical instances, hit rate, counter-of link (orange); untagged group at bottom

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-22 20:52:11 +02:00
OpenSquared
198341b0c2 fix: trade_budget_eur + preferred_horizon saved and reloaded in Config
Backend:
- CycleConfigRequest: add trade_budget_eur, preferred_horizon_min/max fields
  (were missing — Pydantic silently dropped them, so saves never reached set_config)
- update_cycle_config: handle + persist the 3 new fields via set_config
- get_status(): read + return trade_budget_eur/preferred_horizon_min/max from DB
  (were missing — frontend always fell back to React default values on page load)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-22 20:25:31 +02:00
OpenSquared
6cca7f66b6 feat: ticker validation + SLV/USO/WEAT/CORN/TUR added to ETFs watchlist
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>
2026-06-22 20:15:26 +02:00
OpenSquared
5ff5006dec feat: add purge-all for Pattern Library + clarify Trade Ideas in Data Management
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>
2026-06-22 18:42:11 +02:00
OpenSquared
66f6607568 feat: Data Management tab — purge endpoints for all major data stores
Backend — new DELETE /purge-all endpoints:
  - /api/logs/purge-all          → truncate system_logs (immediate, no 30d wait)
  - /api/reports/purge-all       → cycle_reports + ai_reports
  - /api/portfolio/purge-all     → portfolio + trade_entry_prices
  - /api/analytics/purge-all     → pattern_score_history, regime_clusters,
                                    pattern_embeddings, cycle_runs,
                                    macro_regime_history, geo_alert_history
  - /api/var/purge-all           → var_snapshots + pnl_snapshots
  - /api/pattern-lab/purge-all   → backtest_lab_runs

Frontend — Config.tsx: new 'Data Management' tab
  - PurgeButton component with inline double-confirm (click Purge → confirm)
  - Shows table names affected + row count deleted
  - 6 purge actions: Logs, AI Reports, Portfolio, Analytics, VaR, Pattern Lab

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-22 18:25:01 +02:00
OpenSquared
303ecc2a3a feat: instrument picker + Pattern Lab instrument scan mode
- 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>
2026-06-22 18:20:22 +02:00
OpenSquared
cbf989502c feat: Pattern Lab — historical backtest engine for pattern discovery
- 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>
2026-06-22 17:55:48 +02:00
OpenSquared
10ffc345d6 feat: Pattern Explorer — taxonomy tree + 23 historical patterns + instrument lens
- PatternExplorer.tsx: new page with two views:
    • Tree View — 6-root taxonomy (geopolitical, monetary_policy, economic,
      commodity, risk_off, market_structure) with collapsible sub-nodes;
      pattern cards appear on node selection
    • Instrument Lens — search any ticker (e.g. GLD, FXE) to see every
      pattern + scenario that references it, with matching trades highlighted
- geo_analyzer.py: PATTERN_TAXONOMY tree constant + taxonomy_path on all
  patterns; 15 new documented patterns P009-P023 (BoJ YCC, SVB crisis,
  Taiwan semis, OPEC cuts, Fed pivot, Debt ceiling, Iran nuclear, DPRK,
  VIX backwardation, ECB surprise, Extreme Fear contrarian, S. China Sea,
  European energy, CPI hot print, Flash crash)
- patterns.py: GET /api/patterns/taxonomy, GET /api/patterns/by-instrument
- database.py: taxonomy_path migration + seed_builtin_patterns updates path
- App.tsx: /patterns → PatternExplorer, /patterns/edit → PatternEditor

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-22 16:42:45 +02:00
OpenSquared
acc8bef29d feat: 4 remaining institutional reports — Earnings, VX curve, Central Bank RSS, Sentiment
New fetchers (no API keys required):
- earnings_fetcher.py: yfinance EPS calendar + surprise tracking for 23 geo-relevant tickers
- vx_fetcher.py: VIX term structure (^VIX/^VXV/^VXMT) + CBOE delayed futures, regime detection
- central_bank_fetcher.py: Fed + ECB RSS feeds, keyword-based hawkish/dovish classification
- sentiment_fetcher.py: CNN Fear & Greed (primary) + NAAIM + AAII (optional fallbacks)

Wiring:
- institutional_scheduler.py: all 4 now scheduled daily (≥08:00 UTC), deduplicated per day
- institutional.py /refresh: all 6 types handled with _run() helper
- ai_analyzer.py build_institutional_block(): limit 6→12, generic header text
- InstitutionalReports.tsx: 6-type color map, individual refresh buttons, expanded filters

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-22 14:26:19 +02:00
OpenSquared
3edbd6b0b7 feat: institutional reports — CFTC COT + EIA petroleum weekly
- 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>
2026-06-22 13:45:07 +02:00
OpenSquared
319ac35a26 feat: weekend-aware scheduler with configurable cycle times
- 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>
2026-06-21 20:00:06 +02:00
OpenSquared
d4bc4e6624 fix: JSON serialization crash on NaN floats in cycle context snapshot
- portfolio_context.py: add _safe_float() helper (converts NaN/Inf → None);
  use .squeeze().dropna() on yfinance closes before computing moves;
  guard division by checking closes.iloc[-2] != 0
- cycle.py: add _sanitize_floats() recursive sanitizer applied to the full
  snapshot before FastAPI serializes it — catches any remaining NaN from
  iv_rank, technical indicators, or other sources

Fixes 500 on GET /api/cycle/contexts/{run_id} when yfinance returns NaN
weekend data for portfolio positions.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-21 19:48:19 +02:00
OpenSquared
4ad3a9a782 feat: portfolio context injection + AI call log viewer
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>
2026-06-21 10:36:05 +02:00
OpenSquared
a21699805b feat: Phase 4+5 — price discovery status + replay historique
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>
2026-06-20 16:58:57 +02:00
OpenSquared
9c0ebbd138 feat: Phase 2 + context log — FRED releases, cycle context snapshot, onglet Contexte IA
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>
2026-06-20 16:51:02 +02:00
OpenSquared
50ba75e468 feat: Phase 3 — indicateurs techniques calibrés par horizon option
- technical_indicators.py (nouveau) : compute_indicators() calcule RSI, MA fast/slow,
  Bollinger Bands, ATR — périodes calibrées automatiquement selon horizon_days
- config.py : endpoints GET/PUT /config/tech-indicators (activé, liste, auto-calibration)
- useApi.ts : useTechIndicatorsConfig + useSaveTechIndicatorsConfig hooks
- Config.tsx : carte "Indicateurs techniques" dans Options—Paramètres avec toggles
- auto_cycle.py : compute top-5 tickers à chaque cycle si tech_indicators_enabled=true
- ai_analyzer.py : tech_indicators_block injecté dans suggestion + scoring prompts

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 16:41:42 +02:00
OpenSquared
d4a016a535 feat: P&L côte à côte (Ouvert|Réalisé) + filtres journal + suppression trades fermés
- 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>
2026-06-20 11:00:31 +02:00
OpenSquared
39da3b8945 feat: Config tab "Options — Paramètres" with IV gate controls + exit params
- New tab replaces "Journal & Sortie" — consolidates all options-specific settings
- IV Gate section: toggle on/off + 3 sliders (IVR High/Extreme/Skew threshold)
  with live color-coded summary and interdependency guards (high < extreme)
- Exit params section: target, stop-loss, reversal mode + threshold (moved from removed journal tab)
- Backend: GET/PUT /api/config/options-gate endpoint reads/writes 4 config DB keys
- useApi.ts: useOptionsGate + useSaveOptionsGate hooks

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 10:23:31 +02:00
OpenSquared
3ee39d5f08 feat: options technical agent — IV/skew/term structure validation per trade
- New options_technical_agent.py: rule engine (IVR, skew, term structure, flow)
  + GPT-4o narrative per trade; verdict OK/WARN/ALERT + fit_score
- options_trade_assessments table in DB for Journal badge persistence
- auto_cycle.py step 5.2: assess newly logged trades after log_trade_entries;
  results embedded in cycle report
- suggest_patterns_from_market_context: +iv_context param + explicit IV→strategy
  rules in prompt (IVR<30%→Long, 30-60%→Spread, >60%→no naked long, >80%→short)
- Pre-fetch iv_context at step 1.9 so suggestion step gets strategy rules
- reports.py: /api/reports/assessments/latest + /assessments/{run_id} endpoints
- RapportIA.tsx: "Validation Technique Options" section with per-trade IVBar,
  VerdictBadge, issues list, GPT-4o analysis, optimal strategy suggestion

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 09:36:35 +02:00
OpenSquared
e2d5bebef4 feat: Rapport de Cycle — auto-généré à chaque run avec contexte IA, delta, PnL/VaR snapshot
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 07:57:41 +02:00
OpenSquared
4a1dc76d26 feat: page Historique Positions + diff entre 2 snapshots PnL
Backend:
- get_pnl_snapshot(id) : détail complet d'un snapshot avec trades parsés
- diff_pnl_snapshots(a, b) : diff positions entre deux snapshots (nouvelles /
  fermées / évolution PnL par position + delta portfolio)
- GET /api/var/pnl/snapshots/{id} : détail snapshot
- GET /api/var/pnl/diff?a=&b= : calcul du diff

Frontend PositionHistory.tsx :
- Timeline scrollable des snapshots avec sparkline PnL
- Clic snapshot → détail des positions à ce moment (prix entrée, prix actuel,
  PnL %, PnL €, régime macro)
- Boutons A/B par snapshot → sélection de deux points à comparer
- Vue diff A→B : nouvelles positions, fermées, évolution PnL par trade,
  delta portfolio (capital, PnL %, PnL €)
- Route /position-history + nav sidebar

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 06:36:55 +02:00
OpenSquared
b4f3089c58 feat: VaR/PnL schedulers + snapshots DB + page sur bouton
Backend:
- Tables var_snapshots + pnl_snapshots dans SQLite (contexte macro + prix tickers)
- var_service.py : save_var_snapshot, save_pnl_snapshot + fonctions get_*
- var_scheduler.py : threads APScheduler pour VaR (défaut 6h) et PnL (défaut 1h)
- router var.py : /run-now (POST compute+save), /latest, /snapshots, /pnl/run-now,
  /pnl/latest, /scheduler/status, /scheduler/config
- main.py : démarrage des deux schedulers au startup

Frontend:
- VaRAnalysis.tsx : plus d'auto-fetch ; charge le dernier snapshot DB au mount ;
  bouton "Calculer" → POST /run-now ; erreur backend = message clair ; historique
  de snapshots sélectionnables
- Config.tsx : section "Schedulers VaR & PnL" dans l'onglet cycle avec toggle
  enable/disable, intervalle, et boutons "Snapshot maintenant"

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 06:21:20 +02:00
OpenSquared
d64d1029bf feat: page VaR Analyse avec approche delta Black-Scholes
- Service var_service.py : calcul VaR Historique / Paramétrique / Monte Carlo
  stressé (vol ×1.5) + CVaR par méthode, deltas BS par position, fallback
  synthétique si yfinance indisponible
- Router /api/var/compute : paramètres confidence, horizon, lookback, IV défaut
- Page VaRAnalysis.tsx : cartes métriques %, montants EUR, histogramme retours,
  VaR glissante 30j, tableau positions + deltas, backtest Kupiec pass/fail
- Route /var + nav sidebar « VaR Analyse »

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-19 23:15:39 +02:00
OpenSquared
08651551db feat: cockpit command center + skipped trades journal
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>
2026-06-19 19:01:58 +02:00
OpenSquared
58c3767a9d feat: simulation portfolio surveillance + patterns grid/filter UI
Portfolio Monitor (v4.4):
- New portfolio_risk.py service: concentration by asset_class, directional
  conflict detection (same underlying, opposite directions), overweight alerts
- AI agent (Step 7b) runs GPT-4o-mini after each cycle log: assessment +
  prioritized actions + rebalance suggestion, persisted in system_logs
- GET /api/journal/portfolio-risk — full risk breakdown + latest AI monitor reco
- POST /api/journal/trade-check — pre-entry conflict & concentration check
- asset_class column added to trade_entry_prices (auto-migration + populated at INSERT)
- Journal: new "Risque Sim." tab with concentration bars, conflict alerts,
  AI recommendations; red badge on tab when danger alerts exist

PatternEditor:
- Grid view default (2-3 cols responsive), list toggle
- Asset class filter chips (energy/metals/agri/equities/indices/forex/rates)
- Sort: Date (default) / Score IA / Prob.
- Period filter: Tout / 7j / 30j
- Result count badge when filters active

Doc: v4.3 → v4.4, updated Journal/PatternEditor/cycle steps/schema/glossary

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-19 15:49:46 +02:00
OpenSquared
d34b4043fb fix: 4 cycle errors — NameError _log, WHEAT/EUR/USD ticker normalization, 429 serial scoring
- auto_cycle.py: replace _log with logger (NameError at lines 484/489)
- auto_cycle.py: normalize underlying via _normalize_ticker before _resolve_ticker
  so WHEAT→ZW=F→WEAT and EUR/USD→EURUSD=X→FXE reach the IV watchlist correctly
- iv_engine.py: _resolve_ticker now strips slash-format forex (EUR/USD→EURUSD=X)
  before _PROXY lookup, fixing yfinance 500/404 spam from get_atm_iv
- database.py: _fetch in log_trade_entries uses _normalize_ticker (not _normalize_yf_ticker)
  so commodity aliases like WHEAT→ZW=F are applied at price-fetch time
- ai_analyzer.py: max_workers=1 for batch scorer — parallel workers both slept and
  retried simultaneously after 429, causing repeated bursts; sequential fixes the pattern
- journal.py + JournalDeBord.tsx: add price_warning field (no_price_data/no_entry_price/
  no_live_price) with visible ⚠ badge and amber color on affected ticker/price cells

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-19 14:49:07 +02:00
OpenSquared
ee69f3cbd9 feat: trade lifecycle management — close, archive, target/stop alerts
- DB: 9 new columns on trade_entry_prices (status, closed_at, close_reason,
  close_note, pnl_realized, close_price, target_pct, stop_loss_pct, signal_threshold)
  via ALTER TABLE migration; close_trade(), get_closed_trades(),
  update_trade_exit_params() helpers; exit_defaults config key
- Backend: PATCH /trades/{id}/close, PATCH /trades/{id}/exit-params,
  GET/PUT /exit-defaults, GET /closed-trades with win-rate/avg-PnL stats;
  trade-mtm now computes alert_type (target_reached|stop_loss) per trade
- Journal: new "Fermés" tab with closed trades table + stats banner (win rate,
  avg PnL, total PnL, best trade); open trades show Cible/Stop progress bar +
  🎯/🛑 alert badges + 1-click close modal (price, reason, note)
- Config: new "Paramètres de sortie" panel — target_pct, stop_loss_pct,
  signal_reversal_mode, signal_reversal_threshold with live sliders

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-19 14:17:29 +02:00
OpenSquared
0ee9cf5707 feat: AI-enriched news scoring + directional alignment on pattern matching
Hook ai_score_news_batch() into /api/geo/news so every news fetch is enriched
by GPT-4o-mini: corrected impact_score, ai_dir_energy/metals/indices, ai_resolution
(ceasefire/peace deal flag), ai_insight (1 French sentence). Gracefully no-ops
when OpenAI is not configured.

Add _compute_ai_alignment() in geo_analyzer: for each pattern compares the news
AI directional signals against the pattern's expected_move direction and produces
a -25..+25 bonus injected into similarity/relevance scores. Contra-signals
(e.g. peace deal → oil bearish while pattern expects oil spike) are flagged.

Frontend GeoRadar: PatternRelevanceCard shows AI alignment badge (green = aligned,
red = contra-signal) + base relevance diff + AI insights. NewsCard shows ai_insight,
directional arrows per asset class (🥇↓) and resolution badge when expanded.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-19 12:57:52 +02:00
OpenSquared
05a475fb04 feat: system logs page + dynamic IV watchlist with auto-add from cycle
Backend:
- DB: add system_logs table (level/source/cycle_id/ticker/message) and
  iv_watchlist table (ticker/added_by/is_active); seed builtin 18 tickers
- DBLogHandler attached at startup — all WARNING+ logs auto-persist to DB
- log_system_event() helper for structured manual events
- New router /api/logs: GET with filters (level, source, cycle_id, ticker,
  date range), GET /sources, GET /cycles for dropdowns, DELETE /clear
- iv_watchlist now read from DB instead of hardcoded constant; options_vol
  watchlist/refresh/bootstrap endpoints all use get_watchlist_tickers()
- New endpoints: POST/DELETE /options-vol/watchlist-tickers/{ticker} to
  add/remove tickers; adding triggers background 1-year bootstrap
- auto_cycle: after log_trade_entries(), auto-detect new underlying proxies
  not yet in watchlist, add them and bootstrap their IV history

Frontend:
- New page SystemLogs (/logs): log table with level/source/cycle/ticker/date
  filters, color-coded rows, expandable JSON details, auto-refresh 30s
- Options Lab: WatchlistManager section — add ticker input, chip list with
  builtin/auto/manual color coding, remove button for non-builtins
- Sidebar: Logs Système nav link (ScrollText icon)
- useApi: useSystemLogs, useLogSources, useLogCycles, useClearLogs,
  useWatchlistTickers, useAddWatchlistTicker, useRemoveWatchlistTicker

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 13:07:35 +02:00
OpenSquared
3b4e035819 fix: IV rank fallback to history when live options fetch fails + Entrée date from cycle logs
- iv_engine/options_vol: when get_atm_iv() returns None (yfinance chain unavailable),
  fall back to most recent iv_history row so IV Rank is always computable from
  bootstrapped data; live vs history source tagged as iv_source field
- Dashboard: build mtmMap from tradeMtmData.trades (trade_entry_prices, cycle auto-log)
  keyed by pattern_id; getAddedInfo() falls back to mtmMap so Entrée/Durée columns
  populate automatically after each AI cycle without manual portfolio add
- OptionsLab: show '~' prefix and 'IV estimée' label when IV comes from history fallback;
  fix near-invisible text-slate-700 on 'Sans historique' section header

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 11:55:57 +02:00
OpenSquared
abee090881 feat: expandable inline rows in Journal + journal/maturity params in Config
- JournalDeBord: trade rows now expand inline (full-width) instead of
  PostmortemPanel appearing below the whole table. Click anywhere on a
  row to toggle. Period selector extended to 15/30/60/90j.
- Config: added Rétention Journal (30/60/90/180j) and Seuil Maturité
  (20/30/35/50%) controls, wired to the Appliquer button.
- Backend: journal_retention_days and maturity_threshold_pct read from
  config table; seeded at startup with defaults 90d / 35%. get_status()
  now returns both values so Config page can initialise correctly.
- cycle.py: CycleConfigRequest accepts and validates both new params.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 10:08:16 +02:00
OpenSquared
97ba36454b fix: bootstrap IV history with 1y realized vol to unblock IV Rank from 50
IV Rank was stuck at 50 for all tickers because the formula returns 50.0
when iv_max == iv_min (not enough historical snapshots). Added:
- bootstrap_iv_history(): downloads 1y of closes per ticker, computes
  30d rolling realized vol (annualized), saves each day to iv_history
- POST /api/options-vol/bootstrap-history endpoint (runs in background)
- OptionsLab: auto-detect when IV Rank needs bootstrapping and show
  an amber banner with one-click "Initialiser historique" button

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 21:33:01 +02:00
OpenSquared
246deaf631 feat: Phase 4 — Moteur Probabiliste & Apprentissage Automatique
Sprint 4.1 — Bayesian Updating
- database.py: update_bayesian_posteriors() — Beta(α,β) posteriors sur trades matures
- database.py: get_bayesian_posteriors() — posteriors + IC 95% + dérive prior GPT vs posterior
- Colonnes Bayésiennes ajoutées : bayesian_alpha, bayesian_beta, bayesian_win_rate, bayesian_sample_size
- auto_cycle.py: appel update_bayesian_posteriors() en Step 5.5 (après scoring)

Sprint 4.2 — Détection Automatique de Régimes (K-Means numpy pur)
- database.py: detect_and_save_regime_clusters() — K-Means sur 7 gauges macro (VIX, slope, DXY…)
- database.py: get_regime_cluster_history() — timeline des clusters
- database.py: get_regime_transition_matrix() — P(cluster j | cluster i) sur N transitions
- Table regime_clusters avec anomaly_flag (points > 3σ)
- auto_cycle.py: appel detect_and_save_regime_clusters() en Step 5.6

Sprint 4.3 — Embeddings Sémantiques (remplace Jaccard)
- database.py: get_or_create_pattern_embedding() — OpenAI text-embedding-3-small, stocké en DB
- database.py: max_cosine_similarity_vs_existing() — similarité cosinus vs patterns existants
- Table pattern_embeddings avec vecteur JSON + model_version
- auto_cycle.py: _is_duplicate_pattern() — cosinus seuil 0.75 avec fallback Jaccard automatique

Sprint 4.4 — Tableau de Bord Analytique Avancé
- AnalyticsAdvanced.tsx: nouvelle page /analytics-advanced
  • BayesianTable : prior GPT vs WR bayésien ± IC 95%, dérive, niveau de confiance
  • ClusterTimeline : timeline colorée des clusters + anomalies
  • TransitionMatrix : heatmap P(j|i) avec diagonale auto-transition
  • EmbeddingsSummary : liste des patterns vectorisés
  • Boutons "Bayesian update" et "Détecter régime" avec mutation React Query
- analytics.py router : 5 nouveaux endpoints (bayesian, regime-clusters, transitions, detect, embeddings)
- useApi.ts : 4 nouveaux hooks (useBayesianPosteriors, useRegimeClusters, useRegimeTransitions, usePatternEmbeddings)
- App.tsx + Sidebar.tsx : route /analytics-advanced + entrée menu

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 17:46:34 +02:00
OpenSquared
e44c8799b9 feat: Phase 3 — Portfolio Risk Engine (Exposition, Clusters, Kelly, Risk Dashboard)
Sprint 3.1 — Vue Portefeuille Consolidée
- database.py: get_portfolio_exposure() — exposition par classe d'actif + facteur de risque
- database.py: get_pnl_timeline() — courbe P&L cumulé pour equity curve
- Alertes concentration automatiques (>40% par classe, >50% par facteur)
- _RISK_FACTOR_MAP: classification géopolitique/inflation/récession/liquidité/dollar

Sprint 3.2 — Risk Cluster Engine
- database.py: get_risk_clusters() — saturation par facteur + risk_prompt_context
- database.py: get_pattern_correlations() — matrice Pearson sur trades matures
- auto_cycle.py: injection du contexte risque dans le prompt de scoring (Step 3.5)
- ai_analyzer.py: paramètre risk_context dans score_patterns_with_context()
- Pénalisation automatique des patterns sur facteurs saturés dans le scoring GPT

Sprint 3.3 — Position Sizing Kelly Fractionnel
- database.py: compute_kelly_sizing() — f* = (p×G - (1-p))/G, Kelly ×33% par défaut
- Ajustement cluster: sizing ÷2 si facteur saturé
- Ajustement fiabilité: sizing ÷2 si win_rate historique <40% (≥5 trades)
- JournalDeBord.tsx: colonne "Kelly" avec KellyCell (% + €, ajustements signalés)
- routers/risk.py: GET /api/risk/kelly/{pattern_id}

Sprint 3.4 — Tableau de Bord Risque Global
- database.py: get_risk_dashboard() — HHI, score diversification, drawdown attendu, recommandation
- database.py: _build_risk_recommendation() — alerte Risk Committee automatique
- RiskDashboard.tsx: nouvelle page — jauges concentration, courbe P&L, corrélations, recommandation
- Dashboard.tsx: banner d'alerte concentration sur le Cockpit avec lien vers /risk
- routers/risk.py: GET /api/risk/exposure|timeline|clusters|correlations|dashboard
- App.tsx + Sidebar.tsx: route /risk + entrée menu Risk Dashboard

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 17:18:36 +02:00
OpenSquared
f09c5b8ee7 feat: Phase 2 — Pattern Reliability, Contre-thèses & Calibration probabiliste
Sprint 2.1 — Pattern Reliability Score
- database.py: get_pattern_reliability() — win_rate × log(n+1) sur trades matures (≥35% horizon)
- database.py: get_all_pattern_reliability_map() pour injection rapide dans les prompts
- ai_analyzer.py: inject reliability_map dans suggest_patterns (patterns fiables mis en avant)
- auto_cycle.py: charge reliability_map avant suggestion et le passe au suggéreur
- routers/analytics.py: GET /api/analytics/reliability
- PatternEditor.tsx: ReliabilityBadge sur chaque card + usePatternReliability hook
- useApi.ts: usePatternReliability, useCalibration hooks

Sprint 2.2 — Contre-thèses & Invalidation Triggers
- database.py: migration ALTER TABLE — counter_thesis, invalidation_trigger, invalidation_probability
- database.py: save_custom_pattern() persiste les 3 nouveaux champs
- ai_analyzer.py: counter_thesis + invalidation_trigger + invalidation_probability dans le JSON schema
- auto_cycle.py: détection automatique des triggers d'invalidation contre les news (keyword match)
- routers/analytics.py: GET /api/analytics/invalidation-alerts
- PatternEditor.tsx: affichage contre-thèse dans les cards + champs dans le formulaire
- PatternEditor.tsx: affichage dans AiSuggestModal (suggestions IA)
- routers/patterns.py: PatternRequest inclut les 3 nouveaux champs

Sprint 2.3 — Calibration probabiliste & Demi-vie KB
- database.py: migration — predicted_probability sur pattern_score_history
- database.py: save_pattern_scores() stocke probability du pattern à chaque scoring run
- database.py: get_calibration_data() — Brier score + buckets de calibration par décile
- database.py: expires_at + confidence_decay_days sur knowledge_base
- database.py: decay_kb_confidence() — decay automatique + archivage à 0
- auto_cycle.py: decay_kb_confidence() appelé au début de chaque cycle (non-bloquant)
- routers/analytics.py: GET /api/analytics/calibration + POST /api/analytics/kb/decay
- frontend/src/pages/Analytics.tsx: nouvelle page — tableau fiabilité + calibration Brier
- App.tsx + Sidebar.tsx: route /analytics + entrée menu

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 16:50:53 +02:00
OpenSquared
9a6b6f70b1 feat: Phase 1 — IV Rank, Term Structure, Skew, Options Flow (Sprint 1.1/1.2/1.3)
Backend:
- iv_engine.py: ATM IV, term structure (30/60/90/180j), put/call skew,
  options flow (P/C OI ratio, unusual strikes, gamma bias), proxy map for futures→ETFs
- database.py: iv_history table + save_iv_snapshot, get_iv_rank_percentile, get_iv_history
- routers/options_vol.py: /api/options-vol/ endpoints (snapshot, batch, watchlist, history)
- auto_cycle.py: inject IV context string into scoring prompt (step 3.5)
- ai_analyzer.py: score_patterns_with_context accepts iv_context param
- main.py: register options_vol router

Frontend:
- pages/OptionsLab.tsx: full IV dashboard (watchlist by IVR, term structure, skew, flow, sparkline)
- pages/JournalDeBord.tsx: IvRankCell component + IV Rank column per trade
- hooks/useApi.ts: useIvSnapshot, useIvWatchlist, useIvBatch, useIvHistory, useIvForTrade

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 16:29:33 +02:00
OpenSquared
dc3bc667eb fix: 3 bugs — synthesis crash, stale running cycle, invalid tickers
- knowledge.py: trade_line crash when pnl_pct is None in dict
  (t.get('pnl_pct',0) returns None if key exists with None value — use 'or 0')
- database.py: cleanup_stale_running_cycles() marks any 'running' cycle
  as 'error' on startup (uvicorn reload mid-cycle left status stuck)
- main.py: call cleanup_stale_running_cycles() at startup with warning log
- database.py: _normalize_ticker() converts GPT-4o exchange:symbol format
  (NSE:RELIANCE → RELIANCE.NS, BSE:X → X.BO, etc.) so yfinance stops
  spamming 404 errors for every MTM request

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 12:15:32 +02:00
OpenSquared
a3fb486477 feat: delete AI reports, Super Contexte versions, and KB entries
- database.py: add delete_ai_report(), delete_reasoning_state(), delete_kb_entry()
- reasoning.py: DELETE /api/reasoning/reports/{id}
- knowledge.py: DELETE /api/knowledge/history/{id} and /entries/{id}
- useApi.ts: useDeleteAiReport, useDeleteReasoningState, useDeleteKbEntry hooks
- RapportIA.tsx: trash icon on hover in archived reports sidebar
- SuperContexte.tsx: trash icon on hover for history versions and KB entries;
  both propagate onDelete through CategorySection down to KbEntry

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 00:10:41 +02:00
OpenSquared
22687dfd03 feat: time-aware Super Contexte synthesis
- knowledge.py: classify trades by maturity before building synthesis
  prompt; only mature trades (≥35% elapsed) contribute to P&L stats
  and conclusions; immature trades listed for transparency only
- Add 6h staleness gate on POST /synthesize (force=true to override)
- System prompt now includes hard timing rule: GPT-4o must not revise
  existing conclusions because of newly-added immature trades
- useApi.ts: useSynthesizeKnowledge accepts force boolean param
- SuperContexte.tsx: shows amber notice with age when skipped + offers
  "Force quand même" button; success banner uses new response shape

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-16 23:57:46 +02:00
OpenSquared
9075762dd5 feat: time-aware trade maturity classification
- Add _trade_maturity() helper: classifies trades by % of horizon elapsed
  (trop_tot <10%, debut 10-35%, mature 35-75%, fin_horizon >75%)
- Fix horizon_days fallback chain in log_trade_entries (default 30→90)
- journal.py: enrich each MTM trade with maturity dict + horizon_days
- reasoning.py: portfolio report segments trades by maturity; GPT-4o
  draws lessons only from matures (≥35% elapsed), never from trop_tot
- auto_cycle.py: 90d window, maturity-aware prompt with timing rules
- JournalDeBord.tsx: maturity badge with emoji, label, progress bar
  and day counter (Xj / Yj Z%) replacing plain days_held column

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-16 23:49:33 +02:00
OpenSquared
d256b65d30 Initial commit — GeoOptions Intelligence Cockpit v2.0
Stack: FastAPI + React/TypeScript + SQLite + GPT-4o
Features: Radar géopolitique, Marchés, Régime Macro, Journal de Bord MTM,
Rapport IA, Super Contexte (base de raisonnement évolutive), Boucle feedback IA.
Deploy: Docker + docker-compose + nginx pour openfin.open-squared.tech

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-16 20:29:59 +02:00