Commit Graph

21 Commits

Author SHA1 Message Date
OpenSquared
c7ccf237d7 feat: IV gate — block ALERT trades before logging + configurable thresholds
- auto_cycle.py: pre-fetch IV snapshots at step 1.9; _apply_iv_gate() runs
  before log_trade_entries, removes ALERT-verdict trades (not just reports)
- options_technical_agent.py: _IVR_HIGH/_IVR_EXTREME/_SKEW_THRESH as
  module-level vars; straddle/strangle penalty -60 (vs -56 naked) at extreme IVR
  so Long Straddle at IVR ≥ 80% → ALERT; thresholds respected in rule engine
- database.py: seed 4 iv_gate config keys (iv_gate_enabled, iv_gate_ivr_high=60,
  iv_gate_ivr_extreme=80, iv_gate_skew_threshold=8) — editable from Config page
- Blocked trades logged as skipped_trades with [IV_GATE] detail + optimal strategy

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-20 10:15:45 +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
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
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
fda6b6a297 fix: ticker normalization + GPT-4o 429 retry
Ticker normalization (_normalize_ticker):
- EUR/USD slash-format → EURUSD=X (was passed raw to yfinance → 500/404 spam)
- bare 6-char forex pairs EURUSD/USDJPY etc → append =X
- commodity alias table: WHEAT→ZW=F, CORN→ZC=F, WTI→CL=F, BRENT→BZ=F,
  GOLD→GC=F, SILVER→SI=F, NATGAS→NG=F, SUGAR→SB=F, + 15 others
- also normalize underlying at log_trade_entries time so stored tickers
  are already canonical before MtM lookups

GPT-4o 429 rate limit:
- _chat() retries up to 3× on rate_limit errors, respects retry-after hint
  from error message (e.g. "try again in 12.37s"), falls back to 2^n×5s
- batch scorer: parallel workers 4→2 to halve the token burst per cycle
  (2 concurrent batches × ~6K tokens vs 4 × ~6K = 24K burst at 30K limit)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-19 14:29:39 +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
18b3ae6f91 feat: IBKR ticket in Dashboard + Journal MtM (Strike, DTE, legs)
Adds full Interactive Brokers order ticket to both the Dashboard cockpit
and the Journal de Bord MtM expanded rows. Each ticket shows the
underlying, computed strike in dollars, estimated expiry date (nearest
Friday), per-leg BUY/SELL CALL/PUT breakdown, order type LIMIT, budget
and target.

Also adds Strike and DTE columns to the MtM table and persists
strike_guidance + expiry_days_at_entry in trade_entry_prices.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 13:54:29 +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
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
8446876eb0 fix: add pnl_pct and capital_invested migration for trade_entry_prices
Both columns were referenced in queries (reliability, Kelly, calibration,
backtest) but missing from the ALTER TABLE migration block, causing
sqlite3.OperationalError: no such column: pnl_pct on existing VPS DBs.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-17 21:52:50 +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
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