Commit Graph

11 Commits

Author SHA1 Message Date
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
d726cf430e fix: VPS fresh-DB bootstrap — sync OPENAI_API_KEY from env to DB at startup + show countdown before first cycle
- main.py startup: if DB has no openai_api_key but OPENAI_API_KEY env var is set, auto-save it so cycle trigger returns 200 instead of 400
- Config.tsx: move NextRunCountdown outside cs?.last_cycle block so it renders even when no cycle has run yet

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 14:55:42 +02:00
OpenSquared
9fe9a15939 fix: TS2322 onClick handler — wrap handleSynthesize in arrow function
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 14:38:32 +02:00
OpenSquared
27d6b598e8 feat: next run countdown in auto-cycle config
- auto_cycle.py: next_run_at now set to future timestamp (now + interval)
  instead of current time — was always showing wrong value
- Config.tsx: NextRunCountdown component shows live countdown (updates
  every second) + absolute local time, only visible when auto-cycle enabled

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 12:02:50 +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
4bbcd7a3a6 feat: score justification on trade cards
- Add ScorePillars: compact 4-pillar mini-bars always visible under score
  bar (📰/📅/📈/⚖️ with color-coded fill — instant visual of pillar distribution)
- Add ScoreJustification: replaces old per-click BucketBreakdown with full
  text reasoning shown at once — key_catalyst highlighted in yellow callout,
  each pillar shows score + GPT-4o comment + all sub-pillars with comments
- Rename expand button to "↳ Justification du score" for clarity

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-16 22:05:51 +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