From e1681edffc6e2a92ae59abf8318ecf9ccb3a5b81 Mon Sep 17 00:00:00 2001
From: OpenSquared <opensquaredgeneva@gmail.com>
Date: Wed, 1 Jul 2026 21:01:00 +0200
Subject: [PATCH] feat: causal lab

---
 backend/routers/causal_lab.py          | 203 ++++--
 backend/services/causal_graphs.py      | 946 +++++++++++++++----------
 backend/services/database.py           |  10 +
 backend/services/macro_series_log.py   |  23 +-
 frontend/src/pages/MacroSeriesPage.tsx |  37 +-
 5 files changed, 774 insertions(+), 445 deletions(-)

diff --git a/backend/routers/causal_lab.py b/backend/routers/causal_lab.py
index 1a182a8..7f0906f 100644
--- a/backend/routers/causal_lab.py
+++ b/backend/routers/causal_lab.py
@@ -1324,20 +1324,99 @@ def _run_auto_analysis(event: dict, template_id: int) -> dict:
         return {"ok": False, "error": str(e)}
 
 
-def auto_assign_template(event_id: int) -> dict:
+def _classify_to_regime(event: dict) -> dict:
     """
-    Auto-assign or auto-create a causal template for a market event.
-    Called by the eco detector when auto_template=True in desk config.
-    Returns {"template_id": int, "action": "assigned"|"created", "name": str} or {"error": ...}
+    Classify a market event to one of the 12 closed-list regime slugs using GPT-4o.
+    Never creates new templates. Falls back to UNCLASSIFIED_IMPACT if confidence < 0.4.
+    Returns {"slug": str, "confidence": float, "rationale": str}
     """
+    from services.causal_graphs import REGIME_SLUGS
     try:
-        from services.database import get_conn, get_config
-        from services.causal_graphs import get_templates, init_tables, seed_templates
+        from services.database import get_config
         import openai
-
         key = get_config("openai_api_key") or ""
         if not key:
-            return {"error": "Clé OpenAI manquante"}
+            return {"slug": "UNCLASSIFIED_IMPACT", "confidence": 0.0, "rationale": "OpenAI key not configured"}
+
+        client = openai.OpenAI(api_key=key)
+
+        regime_descriptions = {
+            "MACRO_DATA_SURPRISE":         "Scheduled economic release vs consensus (CPI, NFP, GDP, PMI, retail sales, jobless claims, etc.)",
+            "CENTRAL_BANK_DECISION":       "Any central bank rate decision, FOMC/ECB/BoJ/BoE statement, QE/QT announcement",
+            "GROWTH_CORPORATE_SIGNAL":     "Corporate earnings, guidance, M&A, layoffs, analyst revisions, sector-wide activity signals",
+            "GEOPOLITICAL_RISK_OFF":       "Military conflict, sanctions, coups, political crises, election shocks generating risk-off",
+            "COMMODITY_SUPPLY_SHOCK":      "OPEC decision, pipeline disruption, sanctions on producer, WASDE crop report changing supply",
+            "TRADE_POLICY_SHOCK":          "Tariff announcement, trade restriction, protectionist measure, export ban",
+            "CREDIT_SYSTEMIC_EVENT":       "Bank failure, sovereign debt crisis, HY spread blowout, counterparty risk / financial contagion",
+            "TECHNICAL_MOMENTUM_BREAKOUT": "MA cross, key level break, RSI/Bollinger extreme, 52-week high/low — price-driven with no macro trigger",
+            "SENTIMENT_POSITIONING_EXTREME": "VIX spike extreme, COT crowded positioning, extreme put/call skew — contrarian setup",
+            "COMMODITY_INVENTORY_REPORT":  "EIA crude / product weekly, API crude, DOE report — inventory vs consensus surprise",
+            "INSTITUTIONAL_FLOW":          "COT repositioning, FX intervention, central bank buying/selling, end-of-month rebalancing",
+            "UNCLASSIFIED_IMPACT":         "Use ONLY if none of the above clearly fits (low confidence fallback)",
+        }
+
+        regimes_text = "\n".join(
+            f"- {slug}: {desc}" for slug, desc in regime_descriptions.items()
+        )
+
+        system_prompt = (
+            "You are a macro market analyst. Classify the given market event into exactly one of the 12 regime slugs. "
+            "Choose the slug that best matches the PRIMARY causal mechanism — not just the asset class. "
+            "If genuinely uncertain, use UNCLASSIFIED_IMPACT. "
+            "Respond with a JSON object only."
+        )
+
+        user_prompt = f"""Market event:
+- Name: {event.get('name')}
+- Category: {event.get('category')}
+- Sub-type: {event.get('sub_type', '')}
+- Description: {(event.get('description') or '')[:300]}
+- Market impact: {event.get('market_impact', '')}
+- Affected assets: {event.get('affected_assets', '')}
+
+Regime slugs to choose from:
+{regimes_text}
+
+Respond with this exact JSON:
+{{
+  "slug": "<one of the 12 slugs above>",
+  "confidence": <0.0-1.0>,
+  "rationale": "<1-2 sentences explaining why this regime fits>"
+}}"""
+
+        resp = client.chat.completions.create(
+            model="gpt-4o",
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user",   "content": user_prompt},
+            ],
+            response_format={"type": "json_object"},
+            temperature=0.2,
+            max_tokens=200,
+        )
+        result = json.loads(resp.choices[0].message.content or "{}")
+        slug = result.get("slug", "UNCLASSIFIED_IMPACT")
+        if slug not in REGIME_SLUGS:
+            slug = "UNCLASSIFIED_IMPACT"
+        confidence = float(result.get("confidence") or 0.0)
+        if confidence < 0.4:
+            slug = "UNCLASSIFIED_IMPACT"
+        return {"slug": slug, "confidence": confidence, "rationale": result.get("rationale", "")}
+
+    except Exception as e:
+        logger.error(f"[classify_regime] {e}")
+        return {"slug": "UNCLASSIFIED_IMPACT", "confidence": 0.0, "rationale": f"Error: {e}"}
+
+
+def auto_assign_template(event_id: int) -> dict:
+    """
+    Classify a market event to one of 12 closed-list regime templates and assign it.
+    Never creates new templates — falls back to UNCLASSIFIED_IMPACT if confidence < 0.4.
+    Returns {"template_id": int, "action": "assigned", "name": str} or {"error": ...}
+    """
+    try:
+        from services.database import get_conn
+        from services.causal_graphs import get_templates, init_tables, seed_templates
 
         conn = get_conn()
         init_tables(conn)
@@ -1348,86 +1427,60 @@ def auto_assign_template(event_id: int) -> dict:
             conn.close()
             return {"error": f"Event {event_id} introuvable"}
 
-        event     = dict(ev_row)
+        event = dict(ev_row)
+
+        # Classify to one of the 12 regime slugs (never creates a new template)
+        classification = _classify_to_regime(event)
+        slug       = classification["slug"]
+        confidence = classification["confidence"]
+        rationale  = classification.get("rationale", "")
+
+        # Look up the template by slug field (name matches slug label)
         templates = get_templates(conn)
+        tmpl = next((t for t in templates if t.get("name") == _slug_to_name(slug)), None)
 
-        # Step 1 — recommend an existing template
-        recommendation = _gpt4o_recommend(event, templates)
-        tmpl_id    = recommendation.get("template_id")
-        confidence = float(recommendation.get("confidence") or 0.0)
+        # Fallback: try matching by category name if slug lookup fails
+        if not tmpl:
+            tmpl = next((t for t in templates if t.get("name") == "Unclassified Market Impact"), None)
 
-        if tmpl_id and confidence >= 0.6:
-            conn.execute("UPDATE market_events SET auto_template_id = ? WHERE id = ?", (tmpl_id, event_id))
-            conn.commit()
-            row = conn.execute("SELECT name FROM causal_graph_templates WHERE id = ?", (tmpl_id,)).fetchone()
+        if not tmpl:
             conn.close()
-            _run_auto_analysis(event, tmpl_id)
-            return {"template_id": tmpl_id, "action": "assigned", "name": row["name"] if row else "", "confidence": confidence}
+            return {"error": f"Template for slug {slug} not found in DB — run seed_templates first"}
 
-        # Step 2 — no good match → generate a new template
+        tmpl_id = tmpl["id"]
+        conn.execute("UPDATE market_events SET auto_template_id = ? WHERE id = ?", (tmpl_id, event_id))
+        conn.commit()
         conn.close()
 
-        client = openai.OpenAI(api_key=key)
-        prompt = f"""Tu es un analyste financier spécialisé en graphes causaux macro.
-Crée un graphe causal pour l'événement suivant.
-
-Événement :
-- Nom : {event.get('name')}
-- Catégorie : {event.get('category')} / {event.get('sub_type', '')}
-- Description : {(event.get('description') or '')[:400]}
-- Réel : {event.get('actual_value')} | Attendu : {event.get('expected_value')} | Surprise % : {event.get('surprise_pct')}
-
-Retourne UNIQUEMENT ce JSON (sans commentaire ni markdown) :
-{{
-  "name": "<nom court, ex: 'CPI US — Taux/USD'>",
-  "category": "macro_us",
-  "description": "<1 phrase décrivant le mécanisme>",
-  "input_node": {{"id": "<snake_case>", "label": "<label court>", "unit": "<unité>"}},
-  "intermediate_nodes": [{{"id": "<snake_case>", "label": "<label>", "coef_name": "<coef_snake_case>", "coef_value": 0.5, "coef_desc": "<description>"}}],
-  "output_nodes": [{{"id": "<instr_lower>_pip", "label": "<INSTRUMENT>", "instrument": "<EURUSD|XAUUSD|SP500|BRENT|US10Y>", "source_intermediate": "<id>", "coef_name": "<coef_snake_case>", "coef_value": 100, "coef_desc": "<description>"}}]
-}}
-Règles : coef intermédiaire ∈ [-5,5] ; coef output en pips, |val| ∈ [30,200]."""
-
-        resp = client.chat.completions.create(
-            model="gpt-4o",
-            messages=[{"role": "user", "content": prompt}],
-            response_format={"type": "json_object"},
-            temperature=0.3,
-            max_tokens=900,
-        )
-        spec = json.loads(resp.choices[0].message.content or "{}")
-
-        graph_json  = _build_graph_json_from_spec(spec)
-        category    = spec.get("category", "macro_us")
-        instruments = graph_json.get("instruments", ["EURUSD"])
-
-        conn2 = get_conn()
-        cur = conn2.execute("""
-            INSERT INTO causal_graph_templates
-                (name, category, sub_type, description, instruments, graph_json, heuristic_ver)
-            VALUES (?, ?, ?, ?, ?, ?, 1)
-        """, (
-            spec.get("name", event.get("name", "Template IA")),
-            category,
-            event.get("sub_type", ""),
-            spec.get("description", ""),
-            json.dumps(instruments),
-            json.dumps(graph_json),
-        ))
-        new_id = cur.lastrowid
-        conn2.execute("UPDATE market_events SET auto_template_id = ? WHERE id = ?", (new_id, event_id))
-        conn2.commit()
-        conn2.close()
-
-        logger.info(f"[auto_template] Created template #{new_id} '{spec.get('name')}' for event #{event_id}")
-        _run_auto_analysis(event, new_id)
-        return {"template_id": new_id, "action": "created", "name": spec.get("name", "Template IA"), "confidence": confidence}
+        logger.info(f"[auto_template] Event #{event_id} -> {slug} (conf={confidence:.2f}) template #{tmpl_id}")
+        _run_auto_analysis(event, tmpl_id)
+        return {"template_id": tmpl_id, "action": "assigned", "name": tmpl["name"],
+                "slug": slug, "confidence": confidence, "rationale": rationale}
 
     except Exception as e:
         logger.error(f"[auto_template] event #{event_id}: {e}")
         return {"error": str(e)}
 
 
+_SLUG_TO_NAME = {
+    "MACRO_DATA_SURPRISE":          "Macro Data Surprise",
+    "CENTRAL_BANK_DECISION":        "Central Bank Decision",
+    "GROWTH_CORPORATE_SIGNAL":      "Growth & Corporate Signal",
+    "GEOPOLITICAL_RISK_OFF":        "Geopolitical Risk-Off",
+    "COMMODITY_SUPPLY_SHOCK":       "Commodity Supply Shock",
+    "TRADE_POLICY_SHOCK":           "Trade Policy Shock",
+    "CREDIT_SYSTEMIC_EVENT":        "Credit & Systemic Stress",
+    "TECHNICAL_MOMENTUM_BREAKOUT":  "Technical Momentum Breakout",
+    "SENTIMENT_POSITIONING_EXTREME":"Sentiment & Positioning Extreme",
+    "COMMODITY_INVENTORY_REPORT":   "Commodity Inventory Report",
+    "INSTITUTIONAL_FLOW":           "Institutional Flow & Repositioning",
+    "UNCLASSIFIED_IMPACT":          "Unclassified Market Impact",
+}
+
+def _slug_to_name(slug: str) -> str:
+    return _SLUG_TO_NAME.get(slug, "Unclassified Market Impact")
+
+
 @router.post("/api/causal-lab/auto-analyze/refresh")
 def refresh_auto_analyses():
     """
diff --git a/backend/services/causal_graphs.py b/backend/services/causal_graphs.py
index 83e2fa8..df6db2d 100644
--- a/backend/services/causal_graphs.py
+++ b/backend/services/causal_graphs.py
@@ -44,461 +44,678 @@ def _c(value, description=""):
     return {"value": value, "calibrated": None, "description": description}
 
 
-# ── Templates pré-peuplés ─────────────────────────────────────────────────────
+# ── Slugs régimes (12 templates exhaustifs — liste fermée pour auto-assign) ───
+REGIME_SLUGS = [
+    "MACRO_DATA_SURPRISE",
+    "CENTRAL_BANK_DECISION",
+    "GROWTH_CORPORATE_SIGNAL",
+    "GEOPOLITICAL_RISK_OFF",
+    "COMMODITY_SUPPLY_SHOCK",
+    "TRADE_POLICY_SHOCK",
+    "CREDIT_SYSTEMIC_EVENT",
+    "TECHNICAL_MOMENTUM_BREAKOUT",
+    "SENTIMENT_POSITIONING_EXTREME",
+    "COMMODITY_INVENTORY_REPORT",
+    "INSTITUTIONAL_FLOW",
+    "UNCLASSIFIED_IMPACT",
+]
 
 BUILT_IN_TEMPLATES = [
 
-  # ── 1. CPI US surprise ──────────────────────────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 1. MACRO_DATA_SURPRISE
+  # Covers: CPI, PCE, PPI, NFP, ADP, GDP, PMI, ISM, Retail Sales, Housing,
+  #         Jobless Claims, Consumer Confidence, JOLTS — any scheduled data release
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "CPI US — surprise inflationniste",
-    "category": "macro_us",
-    "sub_type": "CPI",
-    "instruments": ["EURUSD", "XAUUSD"],
-    "description": "Surprise inflationniste US → anticipations FED → taux longs → EUR/USD & Or",
-    "ai_rationale": (
-        "Un CPI US au-dessus du consensus renforce les anticipations de hausse FED, "
-        "remonte le 10Y américain, élargit le spread US-EU et apprécie le dollar. "
-        "L'or est pénalisé par la hausse des taux réels attendus."
-    ),
-    "graph_json": {
-        "nodes": [
-            _n("cpi_surprise",  "CPI US surprise",          "input",        200, 45,  unit="%"),
-            _n("fed_fwd",       "Signal FED anticipations",  "intermediate", 200, 155, formula="cpi_surprise / 0.1 * {{coef_cpi_fwd}}"),
-            _n("us_10y",        "Δ US 10Y",                  "intermediate", 200, 265, formula="fed_fwd * {{coef_fwd_10y}}", unit="%"),
-            _n("eurusd",        "EUR/USD",                   "output",       110, 380, formula="-us_10y * {{coef_10y_eurusd}}", unit="pips", instrument="EURUSD"),
-            _n("xauusd",        "Or (XAU/USD)",              "output",       290, 380, formula="-fed_fwd * {{coef_fwd_gold}}", unit="$/oz", instrument="XAUUSD"),
-        ],
-        "edges": [
-            _e("cpi_surprise", "fed_fwd",  "dashed", "fwd_guidance",  "anticipations hawkish"),
-            _e("fed_fwd",      "us_10y",   "dashed", "expectations"),
-            _e("us_10y",       "eurusd",   "solid",  "rate_diff"),
-            _e("fed_fwd",      "xauusd",   "dashed", "real_yield"),
-        ],
-        "coefficients": {
-            "coef_cpi_fwd":    _c(0.50,  "Impact de 0.1% de surprise CPI sur signal FED"),
-            "coef_fwd_10y":    _c(0.070, "Signal FED → Δ rendement US 10Y (%)"),
-            "coef_10y_eurusd": _c(200,   "1% de spread → EUR/USD (pips)"),
-            "coef_fwd_gold":   _c(15.0,  "Unité signal FED → Or ($/oz)"),
-        },
-        "instruments": ["EURUSD", "XAUUSD"],
-        "input_mapping": {
-            "cpi_surprise": {"source": "surprise", "unit": "%", "description": "actual − consensus (%)"}
-        },
-    },
-  },
-
-  # ── 2. NFP surprise v2 (dual-channel, spread US-DE, OIS) ────────────────────
-  {
-    "name": "NFP — surprise emploi non-agricole",
-    "category": "macro_us",
-    "sub_type": "NFP",
-    "heuristic_ver": 2,
-    "instruments": ["EURUSD", "SP500"],
-    "description": (
-        "NFP surprise → OIS repricing → US 2Y (fort) + US 10Y (faible) → "
-        "spread US-DE 2Y → EUR/USD  |  NFP → croissance attendue → S&P500 (2 canaux)"
-    ),
-    "ai_rationale": (
-        "Suite à la critique : (1) le nœud 'Signal FED anticipations' est remplacé par un "
-        "proxy OIS observable (Fed Funds Futures / OIS pricing) ; "
-        "(2) EUR/USD dépend du spread US-DE 2Y plutôt du seul 2Y US ; "
-        "(3) S&P500 reçoit deux effets opposés — croissance (positif) via canal bénéfices "
-        "et taux 10Y (négatif) via canal valorisation. Le lien NFP→10Y est plus faible "
-        "que NFP→2Y (prime de terme + croissance modèrent l'effet)."
-    ),
-    "graph_json": {
-        "nodes": [
-            _n("nfp_surprise", "NFP surprise",            "macro_event",  200,  50, unit="k"),
-            _n("ois_pricing",  "Fed OIS / probabilités",  "observable",   200, 165,
-               formula="nfp_surprise / 100 * {{coef_nfp_ois}}",
-               description="OIS ou Fed Funds Futures — probabilité implicite décision FED"),
-            _n("us_2y",        "Δ US 2Y",                "observable",    90, 295,
-               formula="ois_pricing * {{coef_ois_2y}}", unit="%"),
-            _n("us_10y",       "Δ US 10Y",               "observable",   310, 295,
-               formula="ois_pricing * {{coef_ois_10y}}", unit="%"),
-            _n("rate_diff",    "Spread US-DE 2Y",         "observable",    90, 405,
-               formula="us_2y * {{coef_diff_factor}}",
-               description="proxy: US 2Y seul, idéalement US2Y − DE2Y"),
-            _n("growth_exp",   "Croissance attendue",     "latent",       310, 405,
-               formula="nfp_surprise * {{coef_nfp_growth}}"),
-            _n("eurusd",       "EUR/USD",                "market_asset",  90, 515,
-               formula="-rate_diff * {{coef_diff_eurusd}}", unit="pips", instrument="EURUSD"),
-            _n("sp500",        "S&P 500",                "market_asset", 310, 515,
-               formula="growth_exp * {{coef_growth_sp}} - us_10y * {{coef_10y_sp}}",
-               unit="pts", instrument="SP500"),
-        ],
-        "edges": [
-            _e("nfp_surprise", "ois_pricing", "solid",  "repricing",    strength=3, sign="positive", label="repricing"),
-            _e("ois_pricing",  "us_2y",       "solid",  "rate_anchor",  strength=3, sign="positive", label="canal court"),
-            _e("ois_pricing",  "us_10y",      "dashed", "expectations", strength=1, sign="positive", label="canal terme"),
-            _e("us_2y",        "rate_diff",   "solid",  "spread",       strength=2, sign="positive"),
-            _e("nfp_surprise", "growth_exp",  "dashed", "growth",       strength=2, sign="positive", label="bénéfices"),
-            _e("rate_diff",    "eurusd",      "solid",  "fx_channel",   strength=3, sign="negative", label="USD s'apprécie"),
-            _e("growth_exp",   "sp500",       "solid",  "growth_sp",    strength=2, sign="positive", label="bénéfices +"),
-            _e("us_10y",       "sp500",       "dashed", "discount",     strength=2, sign="negative", label="discount rate"),
-        ],
-        "coefficients": {
-            "coef_nfp_ois":    _c(0.35,  "100k NFP → signal OIS (probabilité remonté taux)"),
-            "coef_ois_2y":     _c(0.030, "Signal OIS → Δ US 2Y (%) — canal court fort"),
-            "coef_ois_10y":    _c(0.012, "Signal OIS → Δ US 10Y (%) — plus faible que 2Y"),
-            "coef_diff_factor":_c(1.0,   "US 2Y → spread US-DE (proxy sans données EU)"),
-            "coef_nfp_growth": _c(0.003, "100k NFP → signal croissance attendue"),
-            "coef_diff_eurusd":_c(500,   "1% spread → EUR/USD pips (négatif pour EUR)"),
-            "coef_growth_sp":  _c(80,    "Signal croissance → S&P500 pts (positif)"),
-            "coef_10y_sp":     _c(150,   "1% hausse 10Y → S&P500 pts (négatif, valorisation)"),
-        },
-        "instruments": ["EURUSD", "SP500"],
-        "input_mapping": {
-            "nfp_surprise": {"source": "surprise", "unit": "k", "description": "actual − consensus (milliers)"}
-        },
-    },
-  },
-
-  # ── 3. FOMC décision de taux ─────────────────────────────────────────────────
-  {
-    "name": "FOMC — décision de taux + ton",
-    "category": "macro_us",
-    "sub_type": "FOMC",
+    "name": "Macro Data Surprise",
+    "slug": "MACRO_DATA_SURPRISE",
+    "category": "monetary_shock",
+    "heuristic_ver": 1,
     "instruments": ["EURUSD", "XAUUSD", "SP500"],
-    "description": "Décision FED : surprise taux (bps) + ton du communiqué → 2 canaux → FX, Or, Actions",
-    "ai_rationale": (
-        "La décision FOMC active deux canaux distincts : le canal taux (fait accompli → ancre 2Y) "
-        "et le canal ton/forward guidance (discours → anticipe trajectoire future → 10Y). "
-        "L'or réagit principalement au canal réel (taux nominaux − inflation attendue)."
-    ),
+    "description": "Scheduled economic release vs consensus → monetary policy repricing (OIS→2Y→10Y) + growth channel → EUR/USD, Gold, S&P",
+    "ai_rationale": "Any scheduled data release that reprices the rate path. Hawkish surprises (hot CPI, strong NFP) strengthen USD via OIS repricing and weaken Gold; dovish misses do the reverse. S&P catches both the growth earnings channel (+) and the valuation discount rate channel (-).",
     "graph_json": {
         "nodes": [
-            _n("rate_surprise_bps", "Surprise taux (bps)",       "input",        110, 45,  unit="bps", description="actual − expected en points de base"),
-            _n("tone_score",        "Ton du communiqué",         "input",        290, 45,  unit="score", description="−3 très dovish … +3 très hawkish"),
-            _n("fed_rate_p",        "Pression taux directeur",   "intermediate", 110, 165, formula="rate_surprise_bps / 25 * {{coef_rate_mult}}"),
-            _n("fed_fwd",           "Signal anticipations FED",  "intermediate", 290, 165, formula="tone_score * {{coef_tone}}"),
-            _n("us_2y",             "Δ US 2Y",                   "intermediate", 110, 285, formula="fed_rate_p * 0.085 + fed_fwd * 0.030", unit="%"),
-            _n("us_10y",            "Δ US 10Y",                  "intermediate", 290, 285, formula="fed_rate_p * 0.035 + fed_fwd * {{coef_fwd_10y}}", unit="%"),
-            _n("eurusd",            "EUR/USD",                   "output",       110, 400, formula="-(us_2y * 500 + us_10y * 200)", unit="pips", instrument="EURUSD"),
-            _n("xauusd",            "Or (XAU/USD)",              "output",       290, 400, formula="-(us_10y * {{coef_10y_gold}} + fed_fwd * {{coef_tone_gold}})", unit="$/oz", instrument="XAUUSD"),
+            _n("macro_surprise",  "Macro Surprise",          "input",        300, 50,  unit="sigma", description="+sigma = beat (hawkish), -sigma = miss (dovish)"),
+            _n("ois_repricing",   "Fed OIS Repricing",       "observable",   150, 190, formula="macro_surprise * {{coef_surp_ois}}", unit="bps"),
+            _n("growth_exp",      "Growth Expectation",      "latent",       450, 190, formula="macro_surprise * {{coef_surp_growth}}"),
+            _n("inflation_risk",  "Inflation Risk",          "latent",       650, 190, formula="macro_surprise * {{coef_surp_infl}}"),
+            _n("us_2y",           "Delta US 2Y Yield",       "observable",   80,  340, formula="ois_repricing * {{coef_ois_2y}}", unit="%"),
+            _n("us_10y",          "Delta US 10Y Yield",      "observable",   300, 340, formula="ois_repricing * {{coef_ois_10y}} + inflation_risk * {{coef_infl_10y}}", unit="%"),
+            _n("fin_conditions",  "Financial Conditions",    "latent",       550, 340, formula="ois_repricing * {{coef_ois_fc}} + us_10y * {{coef_10y_fc}}"),
+            _n("usd_strength",    "USD Strength",            "observable",   80,  480, formula="us_2y * {{coef_2y_usd}}", unit="%"),
+            _n("eurusd",          "EUR/USD",                 "market_asset", 80,  620, formula="-usd_strength * {{coef_usd_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("xauusd",          "Gold XAU/USD",            "market_asset", 550, 620, formula="-us_10y * {{coef_10y_gold}} - usd_strength * {{coef_usd_gold}}", unit="$/oz", instrument="XAUUSD"),
+            _n("sp500",           "S&P 500",                 "market_asset", 300, 620, formula="growth_exp * {{coef_growth_sp}} - fin_conditions * {{coef_fc_sp}}", unit="pts", instrument="SP500"),
         ],
         "edges": [
-            _e("rate_surprise_bps", "fed_rate_p", "solid",  "rate_channel"),
-            _e("tone_score",        "fed_fwd",    "dashed", "fwd_guidance"),
-            _e("fed_rate_p", "us_2y",   "solid",  "rate_anchor",  "canal taux → 2Y"),
-            _e("fed_fwd",    "us_2y",   "dashed", "bleed"),
-            _e("fed_rate_p", "us_10y",  "solid",  "level_shift"),
-            _e("fed_fwd",    "us_10y",  "dashed", "expectations", "canal ton → 10Y"),
-            _e("us_2y",      "eurusd",  "solid",  "rate_diff"),
-            _e("us_10y",     "eurusd",  "dashed", "rate_diff"),
-            _e("us_10y",     "xauusd",  "solid",  "real_yield"),
-            _e("fed_fwd",    "xauusd",  "dashed", "expectations"),
+            _e("macro_surprise", "ois_repricing",  "solid",  "rate_repricing",   strength=3, sign="positive", label="Fed repricing"),
+            _e("macro_surprise", "growth_exp",     "dashed", "growth_channel",   strength=2, sign="positive", label="activity signal"),
+            _e("macro_surprise", "inflation_risk", "dashed", "inflation_ch",     strength=2, sign="positive", label="price pressure"),
+            _e("ois_repricing",  "us_2y",          "solid",  "short_end",        strength=3, sign="positive", label="short-end anchor"),
+            _e("ois_repricing",  "us_10y",         "dashed", "long_end",         strength=1, sign="positive", label="long-end partial"),
+            _e("inflation_risk", "us_10y",         "solid",  "term_premium",     strength=2, sign="positive", label="inflation premium"),
+            _e("ois_repricing",  "fin_conditions", "solid",  "policy_tighten",   strength=2, sign="positive"),
+            _e("us_10y",         "fin_conditions", "solid",  "discount_rate",    strength=2, sign="positive"),
+            _e("us_2y",          "usd_strength",   "solid",  "carry_diff",       strength=3, sign="positive", label="USD carry"),
+            _e("usd_strength",   "eurusd",         "solid",  "fx_channel",       strength=3, sign="negative", label="USD appreciates"),
+            _e("growth_exp",     "sp500",          "solid",  "earnings_ch",      strength=2, sign="positive", label="earnings channel"),
+            _e("fin_conditions", "sp500",          "solid",  "valuation_ch",     strength=3, sign="negative", label="valuation compression"),
+            _e("us_10y",         "xauusd",         "solid",  "real_rate_gold",   strength=2, sign="negative", label="real rates vs gold"),
+            _e("usd_strength",   "xauusd",         "dashed", "usd_gold",         strength=2, sign="negative", label="USD vs gold"),
         ],
         "coefficients": {
-            "coef_rate_mult":  _c(1.0,  "Multiplicateur surprise taux"),
-            "coef_tone":       _c(1.2,  "Ton → signal anticipations"),
-            "coef_fwd_10y":    _c(0.070,"Signal ton → Δ US 10Y (%)"),
-            "coef_10y_gold":   _c(30.0, "1% hausse US 10Y → Or ($/oz, négatif)"),
-            "coef_tone_gold":  _c(10.0, "Signal ton hawkish → Or ($/oz, négatif)"),
+            "coef_surp_ois":    _c(8.0,   "1 sigma surprise -> OIS repricing (bps)"),
+            "coef_surp_growth": _c(0.30,  "1 sigma surprise -> growth expectation"),
+            "coef_surp_infl":   _c(0.15,  "1 sigma surprise -> inflation risk"),
+            "coef_ois_2y":      _c(0.028, "OIS bps -> Delta US 2Y yield (%)"),
+            "coef_ois_10y":     _c(0.008, "OIS bps -> Delta US 10Y yield (partial)"),
+            "coef_infl_10y":    _c(0.12,  "Inflation risk -> 10Y term premium"),
+            "coef_ois_fc":      _c(0.40,  "OIS -> financial conditions index"),
+            "coef_10y_fc":      _c(0.60,  "10Y -> financial conditions index"),
+            "coef_2y_usd":      _c(0.50,  "2Y yield -> USD strength"),
+            "coef_usd_eurusd":  _c(80,    "1% USD -> EUR/USD pips fall"),
+            "coef_growth_sp":   _c(60,    "Growth expectation -> S&P pts"),
+            "coef_fc_sp":       _c(50,    "Financial conditions -> S&P pts fall"),
+            "coef_10y_gold":    _c(15,    "1% 10Y rise -> Gold fall ($/oz)"),
+            "coef_usd_gold":    _c(10,    "USD strength -> Gold fall ($/oz)"),
+        },
+        "instruments": ["EURUSD", "XAUUSD", "SP500"],
+        "input_mapping": {
+            "macro_surprise": {"source": "surprise", "unit": "sigma", "description": "(actual-consensus)/std_dev", "range": [-3, 3]}
+        },
+    },
+  },
+
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 2. CENTRAL_BANK_DECISION
+  # Covers: FOMC, ECB, BoJ, BoE, BoC, RBA, SNB, PBOC — any CB rate decision
+  # ═══════════════════════════════════════════════════════════════════════════════
+  {
+    "name": "Central Bank Decision",
+    "slug": "CENTRAL_BANK_DECISION",
+    "category": "central_bank",
+    "heuristic_ver": 1,
+    "instruments": ["EURUSD", "XAUUSD", "SP500"],
+    "description": "CB rate decision + forward guidance -> immediate full curve repricing -> FX carry, bonds, risk assets",
+    "ai_rationale": "Unlike data surprises, a CB decision directly moves the policy rate and shifts the forward curve. Two channels: the rate channel (anchors 2Y immediately) and the guidance channel (shifts long-end via expectations). Gold reacts primarily to real rate change; equities to discount rate + risk appetite.",
+    "graph_json": {
+        "nodes": [
+            _n("rate_surprise_bps", "Rate Surprise (bps)",   "input",        110, 45,  unit="bps", description="+bps = hawkish, -bps = dovish"),
+            _n("tone_score",        "Guidance Tone",         "input",        390, 45,  unit="score", description="-3 very dovish to +3 very hawkish"),
+            _n("rate_channel",      "Rate Path Revision",    "observable",   110, 185, formula="rate_surprise_bps / 25 * {{coef_rate_mult}}", unit="bps"),
+            _n("guidance_channel",  "Forward Guidance",      "latent",       390, 185, formula="tone_score * {{coef_tone}}"),
+            _n("us_2y",             "Delta 2Y Yield",        "observable",   80,  330, formula="rate_channel * {{coef_rate_2y}} + guidance_channel * {{coef_tone_2y}}", unit="%"),
+            _n("us_10y",            "Delta 10Y Yield",       "observable",   310, 330, formula="rate_channel * {{coef_rate_10y}} + guidance_channel * {{coef_tone_10y}}", unit="%"),
+            _n("risk_appetite",     "Risk Appetite",         "latent",       560, 330, formula="-rate_channel * {{coef_rate_risk}} + guidance_channel * {{coef_tone_risk}}"),
+            _n("carry_diff",        "Carry Differential",    "observable",   80,  470, formula="us_2y * {{coef_2y_carry}}", unit="%"),
+            _n("eurusd",            "EUR/USD",               "market_asset", 80,  620, formula="-carry_diff * {{coef_carry_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("xauusd",            "Gold XAU/USD",          "market_asset", 560, 620, formula="-us_10y * {{coef_10y_gold}} - carry_diff * {{coef_carry_gold}}", unit="$/oz", instrument="XAUUSD"),
+            _n("sp500",             "S&P 500",               "market_asset", 310, 620, formula="risk_appetite * {{coef_risk_sp}} - us_10y * {{coef_10y_sp}}", unit="pts", instrument="SP500"),
+        ],
+        "edges": [
+            _e("rate_surprise_bps", "rate_channel",    "solid",  "immediate_reprice", strength=3, sign="positive", label="direct rate move"),
+            _e("tone_score",        "guidance_channel","dashed", "fwd_guidance",      strength=3, sign="positive", label="communication"),
+            _e("rate_channel",      "us_2y",           "solid",  "short_anchor",      strength=3, sign="positive", label="short-end"),
+            _e("guidance_channel",  "us_2y",           "dashed", "bleed_2y",          strength=1, sign="positive"),
+            _e("rate_channel",      "us_10y",          "solid",  "level_shift",       strength=2, sign="positive"),
+            _e("guidance_channel",  "us_10y",          "dashed", "long_end_guid",     strength=2, sign="positive", label="long-end guidance"),
+            _e("rate_channel",      "risk_appetite",   "dashed", "cost_capital",      strength=2, sign="negative", label="cost of capital"),
+            _e("guidance_channel",  "risk_appetite",   "dashed", "confidence",        strength=2, sign="positive", label="confidence channel"),
+            _e("us_2y",             "carry_diff",      "solid",  "carry",             strength=3, sign="positive"),
+            _e("carry_diff",        "eurusd",          "solid",  "fx_carry",          strength=3, sign="negative", label="USD carry"),
+            _e("risk_appetite",     "sp500",           "solid",  "risk_on_sp",        strength=2, sign="positive"),
+            _e("us_10y",            "sp500",           "solid",  "discount_sp",       strength=3, sign="negative", label="discount rate"),
+            _e("us_10y",            "xauusd",          "solid",  "real_rate_gold",    strength=3, sign="negative", label="real rate vs gold"),
+            _e("carry_diff",        "xauusd",          "dashed", "opp_cost_gold",     strength=2, sign="negative", label="opportunity cost"),
+        ],
+        "coefficients": {
+            "coef_rate_mult":    _c(1.5,   "Decision surprise -> rate path revision multiplier"),
+            "coef_tone":         _c(0.8,   "Guidance tone -> signal"),
+            "coef_rate_2y":      _c(0.70,  "Rate path -> 2Y yield"),
+            "coef_tone_2y":      _c(0.03,  "Guidance -> 2Y bleed"),
+            "coef_rate_10y":     _c(0.30,  "Rate path -> 10Y yield"),
+            "coef_tone_10y":     _c(0.07,  "Guidance -> 10Y long end"),
+            "coef_rate_risk":    _c(0.30,  "Rate hike -> risk appetite negative"),
+            "coef_tone_risk":    _c(0.40,  "Positive guidance -> risk appetite"),
+            "coef_2y_carry":     _c(1.0,   "2Y -> carry differential"),
+            "coef_carry_eurusd": _c(120,   "1% carry -> EUR/USD pips fall"),
+            "coef_risk_sp":      _c(40,    "Risk appetite -> S&P pts"),
+            "coef_10y_sp":       _c(80,    "1% 10Y -> S&P pts fall (valuation)"),
+            "coef_10y_gold":     _c(20,    "1% 10Y rise -> Gold fall ($/oz)"),
+            "coef_carry_gold":   _c(15,    "Carry -> Gold fall (opportunity cost)"),
         },
         "instruments": ["EURUSD", "XAUUSD", "SP500"],
         "input_mapping": {
             "rate_surprise_bps": {"source": "surprise_bps", "unit": "bps"},
-            "tone_score":        {"source": "user_input",   "range": [-3, 3]},
+            "tone_score":        {"source": "user_input",   "unit": "score", "range": [-3, 3]},
         },
     },
   },
 
-  # ── 4. ECB décision de taux ──────────────────────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 3. GROWTH_CORPORATE_SIGNAL
+  # Covers: earnings (S&P large cap), M&A, layoffs, guidance, analyst revisions
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "ECB — décision de taux + ton",
-    "category": "macro_eu",
-    "sub_type": "ECB",
-    "instruments": ["EURUSD"],
-    "description": "Décision BCE : surprise taux + ton → taux EU → spread → EUR/USD",
-    "ai_rationale": (
-        "La BCE active le même schéma dual-canal que la FED mais dans le sens inverse pour EUR/USD. "
-        "Une BCE hawkish surprise élargit les spreads courts EU, réduit le spread US-EU et apprécie l'euro. "
-        "L'effet sur le 10Y Bund est amplifié par le canal forward guidance."
-    ),
+    "name": "Growth & Corporate Signal",
+    "slug": "GROWTH_CORPORATE_SIGNAL",
+    "category": "growth_shock",
+    "heuristic_ver": 1,
+    "instruments": ["SP500", "EURUSD", "XAUUSD"],
+    "description": "Corporate or macro growth signal -> earnings revision + risk appetite -> equities, FX, Gold",
+    "ai_rationale": "Earnings beats, M&A, or positive guidance revise earnings expectations upward and increase risk appetite -> SP500 up. Layoffs or guidance cuts do the reverse. The 10Y yield rises moderately on growth (discount rate headwind), creating the typical dual-channel for equities.",
     "graph_json": {
         "nodes": [
-            _n("ecb_rate_bps", "Surprise taux ECB (bps)",   "input",        110, 45,  unit="bps"),
-            _n("ecb_tone",     "Ton du communiqué BCE",     "input",        290, 45,  unit="score", description="−3 dovish … +3 hawkish"),
-            _n("ecb_rate_p",   "Pression taux BCE",         "intermediate", 110, 165, formula="ecb_rate_bps / 25 * {{coef_ecb_mult}}"),
-            _n("ecb_fwd",      "Signal anticipations BCE",  "intermediate", 290, 165, formula="ecb_tone * {{coef_ecb_tone}}"),
-            _n("eu_2y",        "Δ Bund 2Y",                 "intermediate", 110, 285, formula="ecb_rate_p * 0.080 + ecb_fwd * 0.025", unit="%"),
-            _n("eu_10y",       "Δ Bund 10Y",                "intermediate", 290, 285, formula="ecb_rate_p * 0.030 + ecb_fwd * {{coef_ecb_fwd_10y}}", unit="%"),
-            _n("eurusd",       "EUR/USD",                   "output",       200, 400, formula="eu_2y * 500 + eu_10y * 200", unit="pips", instrument="EURUSD"),
+            _n("growth_trigger",    "Growth Signal",          "input",        300, 50,  unit="%", description="+% = bullish beat, -% = bearish miss"),
+            _n("earnings_revision", "Earnings Revision",      "latent",       150, 200, formula="growth_trigger * {{coef_trig_earn}}"),
+            _n("econ_activity",     "Economic Activity",      "observable",   450, 200, formula="growth_trigger * {{coef_trig_activity}}"),
+            _n("risk_appetite",     "Risk Appetite",          "latent",       300, 360, formula="earnings_revision * {{coef_earn_risk}} + econ_activity * {{coef_act_risk}}"),
+            _n("us_10y",            "Delta US 10Y",           "observable",   100, 360, formula="econ_activity * {{coef_act_10y}}", unit="%"),
+            _n("sp500",             "S&P 500",                "market_asset", 150, 540, formula="earnings_revision * {{coef_earn_sp}} + risk_appetite * {{coef_risk_sp}} - us_10y * {{coef_10y_sp}}", unit="pts", instrument="SP500"),
+            _n("eurusd",            "EUR/USD",                "market_asset", 420, 540, formula="risk_appetite * {{coef_risk_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("xauusd",            "Gold XAU/USD",           "market_asset", 650, 540, formula="-risk_appetite * {{coef_risk_gold}}", unit="$/oz", instrument="XAUUSD"),
         ],
         "edges": [
-            _e("ecb_rate_bps", "ecb_rate_p", "solid",  "rate_channel"),
-            _e("ecb_tone",     "ecb_fwd",    "dashed", "fwd_guidance"),
-            _e("ecb_rate_p",   "eu_2y",      "solid",  "rate_anchor"),
-            _e("ecb_fwd",      "eu_2y",      "dashed", "bleed"),
-            _e("ecb_rate_p",   "eu_10y",     "solid",  "level_shift"),
-            _e("ecb_fwd",      "eu_10y",     "dashed", "expectations"),
-            _e("eu_2y",        "eurusd",     "solid",  "spread_narrow"),
-            _e("eu_10y",       "eurusd",     "dashed", "spread_narrow"),
+            _e("growth_trigger",    "earnings_revision","solid",  "eps_channel",   strength=3, sign="positive", label="EPS revision"),
+            _e("growth_trigger",    "econ_activity",    "dashed", "activity_proxy",strength=2, sign="positive", label="activity signal"),
+            _e("growth_trigger",    "us_10y",           "dashed", "growth_premium",strength=1, sign="positive", label="growth premium"),
+            _e("earnings_revision", "risk_appetite",    "solid",  "confidence_ch", strength=3, sign="positive"),
+            _e("econ_activity",     "risk_appetite",    "solid",  "sentiment_ch",  strength=2, sign="positive"),
+            _e("earnings_revision", "sp500",            "solid",  "eps_multiple",  strength=3, sign="positive", label="EPS x multiple"),
+            _e("risk_appetite",     "sp500",            "solid",  "sentiment_sp",  strength=2, sign="positive"),
+            _e("us_10y",            "sp500",            "dashed", "discount_drag", strength=1, sign="negative", label="discount rate"),
+            _e("risk_appetite",     "eurusd",           "solid",  "risk_on_fx",    strength=2, sign="positive", label="risk-on FX"),
+            _e("risk_appetite",     "xauusd",           "dashed", "safe_exit",     strength=2, sign="negative", label="safe haven exits"),
         ],
         "coefficients": {
-            "coef_ecb_mult":    _c(1.0,  "Multiplicateur surprise taux BCE"),
-            "coef_ecb_tone":    _c(1.2,  "Ton BCE → signal anticipations"),
-            "coef_ecb_fwd_10y": _c(0.060,"Signal ton BCE → Δ Bund 10Y (%)"),
+            "coef_trig_earn":     _c(0.50, "Growth signal -> earnings revision"),
+            "coef_trig_activity": _c(0.40, "Growth signal -> activity proxy"),
+            "coef_act_10y":       _c(0.05, "Activity -> 10Y growth premium"),
+            "coef_earn_risk":     _c(0.60, "Earnings revision -> risk appetite"),
+            "coef_act_risk":      _c(0.40, "Activity -> risk appetite"),
+            "coef_earn_sp":       _c(80,   "Earnings revision -> S&P pts"),
+            "coef_risk_sp":       _c(40,   "Risk appetite -> S&P pts"),
+            "coef_10y_sp":        _c(30,   "10Y rise -> S&P pts fall"),
+            "coef_risk_eurusd":   _c(30,   "Risk appetite -> EUR/USD pips"),
+            "coef_risk_gold":     _c(15,   "Risk appetite up -> Gold falls"),
         },
-        "instruments": ["EURUSD"],
+        "instruments": ["SP500", "EURUSD", "XAUUSD"],
         "input_mapping": {
-            "ecb_rate_bps": {"source": "surprise_bps", "unit": "bps"},
-            "ecb_tone":     {"source": "user_input",   "range": [-3, 3]},
+            "growth_trigger": {"source": "user_input", "unit": "%", "range": [-5, 5]}
         },
     },
   },
 
-  # ── 5. Escalade géopolitique Europe ──────────────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 4. GEOPOLITICAL_RISK_OFF
+  # Covers: military conflicts, sanctions, coups, election shocks, political crises
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "Escalade géopolitique — Europe",
+    "name": "Geopolitical Risk-Off",
+    "slug": "GEOPOLITICAL_RISK_OFF",
     "category": "geopolitical",
-    "sub_type": "Geopolitical",
-    "instruments": ["EURUSD", "XAUUSD", "BRENT"],
-    "description": "Conflit / escalade en Europe → risk-off + choc énergie → EUR/USD, Or, Pétrole",
-    "ai_rationale": (
-        "Un événement géopolitique européen active deux canaux simultanés : "
-        "l'aversion au risque (VIX → USD safe haven → EUR baisse) et le choc énergétique "
-        "(disruption approvisionnement → pétrole monte → or monte, coût importations EU → EUR faiblit)."
-    ),
+    "heuristic_ver": 1,
+    "instruments": ["EURUSD", "XAUUSD", "SP500", "BRENT"],
+    "description": "Geopolitical shock -> risk premium + safe-haven demand -> Gold up VIX up EUR down SP500 down (+ oil supply if Middle East)",
+    "ai_rationale": "Geopolitical events generate two simultaneous channels: a risk premium channel (VIX spike -> equities fall, USD safe haven -> EUR fall) and potentially an energy supply channel (if Middle East / energy producers). Gold is the primary safe haven. EUR is uniquely exposed given EU proximity to conflict zones.",
     "graph_json": {
         "nodes": [
-            _n("severity",       "Sévérité (1−10)",          "input",        200, 45,  unit="score", description="1=faible, 10=crise majeure"),
-            _n("risk_aversion",  "Aversion au risque",       "intermediate", 110, 155, formula="severity * {{coef_sev_risk}}"),
-            _n("energy_shock",   "Choc énergie EU",          "intermediate", 290, 155, formula="severity * {{coef_sev_energy}}"),
-            _n("vix_delta",      "Δ VIX",                    "intermediate", 110, 265, formula="risk_aversion * {{coef_risk_vix}}"),
-            _n("oil_delta",      "Δ Pétrole (%)",            "intermediate", 290, 265, formula="energy_shock * {{coef_energy_oil}}"),
-            _n("eurusd",         "EUR/USD",                  "output",       80,  390, formula="-(vix_delta * {{coef_vix_fx}} + energy_shock * {{coef_energy_fx}})", unit="pips", instrument="EURUSD"),
-            _n("xauusd",         "Or (XAU/USD)",             "output",       200, 390, formula="vix_delta * {{coef_vix_gold}} + oil_delta * {{coef_oil_gold}}", unit="$/oz", instrument="XAUUSD"),
-            _n("brent",          "Brent (USD/bbl)",          "output",       320, 390, formula="oil_delta * {{coef_oil_brent}}", unit="$/bbl", instrument="BRENT"),
+            _n("geo_shock",       "Geopolitical Shock",      "input",        300, 50,  unit="score", description="Severity 1-10 (1=minor, 10=major conflict)"),
+            _n("risk_premium",    "Risk Premium",            "latent",       150, 200, formula="geo_shock * {{coef_shock_rp}}"),
+            _n("safe_haven_dem",  "Safe Haven Demand",       "latent",       450, 200, formula="geo_shock * {{coef_shock_shd}}"),
+            _n("oil_supply_risk", "Oil Supply Risk",         "latent",       700, 200, formula="geo_shock * {{coef_shock_oil}}", description="Only if energy-producing region"),
+            _n("vix_spike",       "Delta VIX",               "observable",   150, 360, formula="risk_premium * {{coef_rp_vix}}", unit="pts"),
+            _n("usd_safe_haven",  "USD Safe Haven Flow",     "observable",   420, 360, formula="safe_haven_dem * {{coef_shd_usd}}"),
+            _n("gold_demand",     "Gold Safe Haven",         "observable",   680, 360, formula="safe_haven_dem * {{coef_shd_gold}}"),
+            _n("eurusd",          "EUR/USD",                 "market_asset", 100, 560, formula="-usd_safe_haven * {{coef_usd_eurusd}} - risk_premium * {{coef_rp_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("sp500",           "S&P 500",                 "market_asset", 380, 560, formula="-risk_premium * {{coef_rp_sp}} - vix_spike * {{coef_vix_sp}}", unit="pts", instrument="SP500"),
+            _n("xauusd",          "Gold XAU/USD",            "market_asset", 660, 560, formula="gold_demand * {{coef_gold_xau}} + safe_haven_dem * {{coef_shd_xau}}", unit="$/oz", instrument="XAUUSD"),
+            _n("brent",           "Brent Crude",             "market_asset", 880, 560, formula="oil_supply_risk * {{coef_oilrisk_brent}}", unit="$/bbl", instrument="BRENT"),
         ],
         "edges": [
-            _e("severity",      "risk_aversion",  "solid",  "transmission",   "perception risque"),
-            _e("severity",      "energy_shock",   "solid",  "supply_chain",   "disruption énergie"),
-            _e("risk_aversion", "vix_delta",      "solid",  "fear_gauge"),
-            _e("energy_shock",  "oil_delta",      "solid",  "supply_shock"),
-            _e("vix_delta",     "eurusd",         "solid",  "safe_haven",     "fuite vers USD"),
-            _e("energy_shock",  "eurusd",         "solid",  "trade_balance",  "coût imports EU"),
-            _e("vix_delta",     "xauusd",         "dashed", "safe_haven",     "fuite vers or"),
-            _e("oil_delta",     "xauusd",         "dashed", "inflation_hedge"),
-            _e("oil_delta",     "brent",          "solid",  "direct"),
+            _e("geo_shock",      "risk_premium",   "solid",  "uncertainty",    strength=3, sign="positive", label="uncertainty premium"),
+            _e("geo_shock",      "safe_haven_dem", "solid",  "flight_quality", strength=3, sign="positive", label="flight to quality"),
+            _e("geo_shock",      "oil_supply_risk","dashed", "supply_threat",  strength=2, sign="positive", label="supply threat"),
+            _e("risk_premium",   "vix_spike",      "solid",  "fear_gauge",     strength=3, sign="positive"),
+            _e("safe_haven_dem", "usd_safe_haven", "solid",  "usd_flight",     strength=2, sign="positive"),
+            _e("safe_haven_dem", "gold_demand",    "solid",  "gold_flight",    strength=3, sign="positive"),
+            _e("usd_safe_haven", "eurusd",         "solid",  "usd_apprec",     strength=3, sign="negative", label="USD appreciates"),
+            _e("risk_premium",   "eurusd",         "dashed", "eu_exposure",    strength=2, sign="negative", label="EU geo exposure"),
+            _e("risk_premium",   "sp500",          "solid",  "risk_reprice",   strength=3, sign="negative", label="risk repricing"),
+            _e("vix_spike",      "sp500",          "solid",  "vol_crush_eq",   strength=2, sign="negative", label="vol crushes equities"),
+            _e("gold_demand",    "xauusd",         "solid",  "gold_move",      strength=3, sign="positive"),
+            _e("safe_haven_dem", "xauusd",         "dashed", "shd_gold",       strength=2, sign="positive"),
+            _e("oil_supply_risk","brent",          "solid",  "supply_brent",   strength=3, sign="positive"),
         ],
         "coefficients": {
-            "coef_sev_risk":    _c(1.5,  "Sévérité → aversion au risque"),
-            "coef_sev_energy":  _c(0.8,  "Sévérité → choc énergie"),
-            "coef_risk_vix":    _c(3.0,  "Aversion risque → Δ VIX points"),
-            "coef_energy_oil":  _c(2.0,  "Choc énergie → % hausse pétrole"),
-            "coef_vix_fx":      _c(4.0,  "1 pt VIX → EUR/USD pips (négatif)"),
-            "coef_energy_fx":   _c(8.0,  "Choc énergie → EUR/USD pips (négatif)"),
-            "coef_vix_gold":    _c(5.0,  "1 pt VIX → Or $/oz (positif)"),
-            "coef_oil_gold":    _c(3.0,  "1% oil → Or $/oz"),
-            "coef_oil_brent":   _c(5.0,  "Choc énergie → Brent $/bbl"),
+            "coef_shock_rp":      _c(0.30, "Geo shock -> risk premium"),
+            "coef_shock_shd":     _c(0.40, "Geo shock -> safe haven demand"),
+            "coef_shock_oil":     _c(0.20, "Geo shock -> oil supply risk (region-weighted)"),
+            "coef_rp_vix":        _c(2.0,  "Risk premium -> Delta VIX pts"),
+            "coef_shd_usd":       _c(0.50, "Safe haven demand -> USD flow"),
+            "coef_shd_gold":      _c(0.80, "Safe haven demand -> gold demand"),
+            "coef_usd_eurusd":    _c(60,   "USD safe haven -> EUR/USD pips fall"),
+            "coef_rp_eurusd":     _c(40,   "Risk premium -> EUR/USD fall (EU exposure)"),
+            "coef_rp_sp":         _c(80,   "Risk premium -> S&P pts fall"),
+            "coef_vix_sp":        _c(30,   "VIX spike -> S&P pts fall"),
+            "coef_gold_xau":      _c(25,   "Gold demand -> XAU/USD rise"),
+            "coef_shd_xau":       _c(15,   "Safe haven -> XAU/USD additional"),
+            "coef_oilrisk_brent": _c(5.0,  "Oil supply risk -> Brent USD"),
         },
-        "instruments": ["EURUSD", "XAUUSD", "BRENT"],
+        "instruments": ["EURUSD", "XAUUSD", "SP500", "BRENT"],
         "input_mapping": {
-            "severity": {"source": "impact_score_scaled", "unit": "score", "range": [1, 10]}
+            "geo_shock": {"source": "impact_score_scaled", "unit": "score", "range": [1, 10]}
         },
     },
   },
 
-  # ── 6. Choc offre pétrole ────────────────────────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 5. COMMODITY_SUPPLY_SHOCK
+  # Covers: OPEC decisions, sanctions on producers, pipeline disruptions, WASDE
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "Choc offre pétrole — OPEC / disruption",
+    "name": "Commodity Supply Shock",
+    "slug": "COMMODITY_SUPPLY_SHOCK",
     "category": "commodity",
-    "sub_type": "Oil",
-    "instruments": ["BRENT", "EURUSD", "XAUUSD"],
-    "description": "Choc d'offre pétrolière → prix → inflation EU → trade balance → EUR",
-    "ai_rationale": (
-        "Un choc d'offre haussier sur le pétrole impacte directement le Brent. "
-        "L'Europe, importateur net, voit ses coûts d'importation augmenter (trade balance → EUR négatif), "
-        "et ses anticipations d'inflation croître (BCE contrainte entre lutte anti-inflation et croissance)."
-    ),
+    "heuristic_ver": 1,
+    "instruments": ["BRENT", "XAUUSD", "EURUSD", "SP500"],
+    "description": "Supply disruption/glut in energy or commodities -> Brent move -> energy inflation -> EU trade deficit -> EUR/USD, Gold, S&P",
+    "ai_rationale": "OPEC cuts or supply disruptions hit Brent first, then transmit through energy inflation (cost-push), EU trade balance deterioration (energy importer), and real income squeeze. Gold benefits from inflation expectations. S&P suffers from margin pressure.",
     "graph_json": {
         "nodes": [
-            _n("oil_change_pct",   "Choc prix pétrole (%)",   "input",        200, 45,  unit="%"),
-            _n("brent_move",       "Δ Brent ($/bbl)",         "intermediate", 110, 155, formula="oil_change_pct * {{coef_oil_brent}}"),
-            _n("eu_import_cost",   "Coût imports EU",         "intermediate", 290, 155, formula="oil_change_pct * {{coef_oil_import}}"),
-            _n("eu_inflation",     "Anticipations inflation EU","intermediate",290, 265, formula="eu_import_cost * {{coef_import_inf}}"),
-            _n("eurusd",           "EUR/USD",                 "output",       110, 380, formula="-(eu_import_cost * {{coef_import_fx}} + eu_inflation * {{coef_inf_fx}})", unit="pips", instrument="EURUSD"),
-            _n("xauusd",           "Or (XAU/USD)",            "output",       290, 380, formula="brent_move * {{coef_oil_gold}}", unit="$/oz", instrument="XAUUSD"),
+            _n("supply_shock",    "Supply Shock",            "input",        300, 50,  unit="mbpd", description="+mbpd = cut/disruption (bullish oil), -mbpd = increase"),
+            _n("supply_deficit",  "Supply Deficit",          "observable",   150, 200, formula="supply_shock * {{coef_shock_deficit}}"),
+            _n("energy_inflation","Energy Inflation",        "latent",       550, 200, formula="supply_shock * {{coef_shock_einfl}}"),
+            _n("brent",           "Brent Crude",             "market_asset", 150, 380, formula="supply_deficit * {{coef_deficit_brent}}", unit="$/bbl", instrument="BRENT"),
+            _n("eu_import_cost",  "EU Import Cost",          "latent",       420, 380, formula="energy_inflation * {{coef_einfl_import}}"),
+            _n("infl_breakeven",  "Inflation Expectations",  "latent",       700, 380, formula="energy_inflation * {{coef_einfl_breakeven}}"),
+            _n("eurusd",          "EUR/USD",                 "market_asset", 200, 560, formula="-eu_import_cost * {{coef_import_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("sp500",           "S&P 500",                 "market_asset", 480, 560, formula="-eu_import_cost * {{coef_import_sp}} - infl_breakeven * {{coef_infl_sp}}", unit="pts", instrument="SP500"),
+            _n("xauusd",          "Gold XAU/USD",            "market_asset", 750, 560, formula="infl_breakeven * {{coef_infl_gold}}", unit="$/oz", instrument="XAUUSD"),
         ],
         "edges": [
-            _e("oil_change_pct", "brent_move",    "solid",  "direct"),
-            _e("oil_change_pct", "eu_import_cost","solid",  "trade_balance"),
-            _e("eu_import_cost", "eu_inflation",  "dashed", "cost_push"),
-            _e("eu_import_cost", "eurusd",        "solid",  "trade_balance",  "déficit commercial EU"),
-            _e("eu_inflation",   "eurusd",        "dashed", "policy_ambiguity","BCE coincé"),
-            _e("brent_move",     "xauusd",        "dashed", "inflation_hedge"),
+            _e("supply_shock",    "supply_deficit",  "solid",  "production_gap",    strength=3, sign="positive", label="production gap"),
+            _e("supply_shock",    "energy_inflation","dashed", "cost_push",         strength=2, sign="positive", label="cost-push inflation"),
+            _e("supply_deficit",  "brent",           "solid",  "spot_premium",      strength=3, sign="positive", label="spot premium"),
+            _e("energy_inflation","eu_import_cost",  "solid",  "trade_balance",     strength=2, sign="positive"),
+            _e("energy_inflation","infl_breakeven",  "solid",  "breakeven_reprice", strength=2, sign="positive"),
+            _e("eu_import_cost",  "eurusd",          "solid",  "terms_of_trade",    strength=2, sign="negative", label="EU trade deficit"),
+            _e("eu_import_cost",  "sp500",           "dashed", "margin_squeeze",    strength=2, sign="negative", label="margin squeeze"),
+            _e("infl_breakeven",  "sp500",           "solid",  "multiple_compress", strength=2, sign="negative", label="multiple compression"),
+            _e("infl_breakeven",  "xauusd",          "solid",  "infl_hedge",        strength=3, sign="positive", label="inflation hedge"),
         ],
         "coefficients": {
-            "coef_oil_brent":  _c(1.0,  "% hausse oil → Δ Brent $/bbl (linéaire à calibrer)"),
-            "coef_oil_import": _c(0.5,  "% hausse oil → pression imports EU (score)"),
-            "coef_import_inf": _c(0.3,  "Pression imports → anticipations inflation EU"),
-            "coef_import_fx":  _c(10.0, "Pression imports → EUR/USD pips (négatif)"),
-            "coef_inf_fx":     _c(5.0,  "Inflation EU → EUR/USD (ambiguë, négatif net)"),
-            "coef_oil_gold":   _c(0.8,  "1$/bbl Brent → Or $/oz"),
+            "coef_shock_deficit":   _c(1.0,  "Supply shock mb/d -> deficit mb/d"),
+            "coef_shock_einfl":     _c(0.10, "Supply shock -> energy inflation (%)"),
+            "coef_deficit_brent":   _c(3.0,  "1mb/d deficit -> Brent $/bbl"),
+            "coef_einfl_import":    _c(0.60, "Energy inflation -> EU import cost pressure"),
+            "coef_einfl_breakeven": _c(0.40, "Energy inflation -> breakeven repricing"),
+            "coef_import_eurusd":   _c(50,   "EU import cost -> EUR/USD pips fall"),
+            "coef_import_sp":       _c(40,   "Import cost -> S&P pts fall (margin)"),
+            "coef_infl_sp":         _c(30,   "Inflation exp -> S&P pts fall (multiples)"),
+            "coef_infl_gold":       _c(20,   "Inflation exp -> Gold $/oz rise"),
         },
-        "instruments": ["BRENT", "EURUSD", "XAUUSD"],
+        "instruments": ["BRENT", "XAUUSD", "EURUSD", "SP500"],
         "input_mapping": {
-            "oil_change_pct": {"source": "impact_score_pct", "unit": "%"}
+            "supply_shock": {"source": "user_input", "unit": "mbpd", "range": [-3, 3]}
         },
     },
   },
 
-  # ── 7. COT repositionnement institutionnel ───────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 6. TRADE_POLICY_SHOCK
+  # Covers: tariff announcements, trade restrictions, protectionism, export bans
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "COT — repositionnement institutionnel EUR",
-    "category": "report",
-    "sub_type": "COT",
-    "instruments": ["EURUSD"],
-    "description": "Variation nette des positions institutionnelles EUR → signal momentum → EUR/USD",
-    "ai_rationale": (
-        "Le rapport COT (Commitment of Traders) révèle les positions nettes des fonds spéculatifs sur EUR. "
-        "Un changement significatif des positions nettes agit comme signal de momentum, "
-        "les marchés interprétant un repositionnement institutionnel comme un signal directionnel."
-    ),
+    "name": "Trade Policy Shock",
+    "slug": "TRADE_POLICY_SHOCK",
+    "category": "trade_policy",
+    "heuristic_ver": 1,
+    "instruments": ["EURUSD", "SP500", "XAUUSD"],
+    "description": "Tariff / trade restriction announcement -> stagflationary shock (growth down + inflation up) -> EUR down SP500 down Gold up",
+    "ai_rationale": "Trade restrictions create a stagflationary combination: import cost inflation and trade volume contraction (reduced EU exports -> ECB forced dovish). Policy uncertainty freezes capex. Gold benefits from the inflation + uncertainty combination.",
     "graph_json": {
         "nodes": [
-            _n("net_longs_delta",  "Δ Positions nettes EUR (k contrats)", "input",        200, 45,  unit="k contracts"),
-            _n("momentum_signal",  "Signal momentum institutionnel",       "intermediate", 200, 185, formula="net_longs_delta * {{coef_cot_momentum}}"),
-            _n("eurusd",           "EUR/USD",                             "output",       200, 330, formula="momentum_signal * {{coef_momentum_fx}}", unit="pips", instrument="EURUSD"),
+            _n("tariff_shock",     "Trade Restriction",       "input",        300, 50,  unit="%", description="Tariff rate in % (positive = new restriction)"),
+            _n("import_cost_rise", "Import Cost Rise",        "observable",   150, 200, formula="tariff_shock * {{coef_tariff_cost}}", unit="%"),
+            _n("trade_volume_drop","Trade Volume Drop",       "observable",   550, 200, formula="-tariff_shock * {{coef_tariff_vol}}", unit="%"),
+            _n("policy_uncertainty","Policy Uncertainty",    "latent",       300, 200, formula="tariff_shock * {{coef_tariff_unc}}"),
+            _n("stagflation_risk", "Stagflation Risk",        "latent",       300, 370, formula="import_cost_rise * {{coef_cost_stag}} - trade_volume_drop * {{coef_vol_stag}}"),
+            _n("corp_margin",      "Corporate Margin Press.", "latent",       600, 370, formula="import_cost_rise * {{coef_cost_margin}}"),
+            _n("eurusd",           "EUR/USD",                 "market_asset", 100, 560, formula="-stagflation_risk * {{coef_stag_eurusd}} - trade_volume_drop * {{coef_vol_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("sp500",            "S&P 500",                 "market_asset", 400, 560, formula="-corp_margin * {{coef_margin_sp}} - policy_uncertainty * {{coef_unc_sp}} - stagflation_risk * {{coef_stag_sp}}", unit="pts", instrument="SP500"),
+            _n("xauusd",           "Gold XAU/USD",            "market_asset", 700, 560, formula="stagflation_risk * {{coef_stag_gold}} + policy_uncertainty * {{coef_unc_gold}}", unit="$/oz", instrument="XAUUSD"),
         ],
         "edges": [
-            _e("net_longs_delta", "momentum_signal", "solid",  "positioning"),
-            _e("momentum_signal", "eurusd",          "solid",  "momentum"),
+            _e("tariff_shock",     "import_cost_rise",  "solid",  "price_passthru",   strength=3, sign="positive", label="price pass-through"),
+            _e("tariff_shock",     "trade_volume_drop", "solid",  "trade_contract",   strength=3, sign="negative", label="trade contraction"),
+            _e("tariff_shock",     "policy_uncertainty","solid",  "capex_freeze",     strength=3, sign="positive", label="capex freeze"),
+            _e("import_cost_rise", "stagflation_risk",  "solid",  "cost_stag",        strength=2, sign="positive"),
+            _e("trade_volume_drop","stagflation_risk",  "solid",  "growth_stag",      strength=2, sign="negative"),
+            _e("import_cost_rise", "corp_margin",       "solid",  "supply_chain",     strength=3, sign="positive"),
+            _e("stagflation_risk", "eurusd",            "solid",  "eu_stagflation",   strength=2, sign="negative", label="EU stagflation exposure"),
+            _e("trade_volume_drop","eurusd",            "dashed", "export_shock",     strength=2, sign="negative", label="export shock"),
+            _e("corp_margin",      "sp500",             "solid",  "eps_compress",     strength=3, sign="negative", label="EPS compression"),
+            _e("policy_uncertainty","sp500",            "solid",  "capex_sentiment",  strength=2, sign="negative"),
+            _e("stagflation_risk", "sp500",             "dashed", "stagflation_sp",   strength=2, sign="negative"),
+            _e("stagflation_risk", "xauusd",            "solid",  "stagflation_hedge",strength=3, sign="positive", label="stagflation hedge"),
+            _e("policy_uncertainty","xauusd",           "dashed", "uncertainty_gold", strength=2, sign="positive"),
         ],
         "coefficients": {
-            "coef_cot_momentum":  _c(0.5, "k contrats → signal momentum"),
-            "coef_momentum_fx":   _c(2.0, "Signal momentum → EUR/USD pips"),
+            "coef_tariff_cost":  _c(0.30, "10% tariff -> ~3% import cost rise"),
+            "coef_tariff_vol":   _c(0.50, "Tariff -> trade volume reduction"),
+            "coef_tariff_unc":   _c(0.40, "Tariff -> policy uncertainty"),
+            "coef_cost_stag":    _c(0.50, "Cost rise -> stagflation index"),
+            "coef_vol_stag":     _c(0.50, "Volume drop -> growth component"),
+            "coef_cost_margin":  _c(0.60, "Cost rise -> margin pressure"),
+            "coef_stag_eurusd":  _c(60,   "Stagflation -> EUR/USD pips fall"),
+            "coef_vol_eurusd":   _c(30,   "Trade drop -> EUR/USD pips fall"),
+            "coef_margin_sp":    _c(60,   "Margin pressure -> S&P pts fall"),
+            "coef_unc_sp":       _c(40,   "Uncertainty -> S&P pts fall"),
+            "coef_stag_sp":      _c(30,   "Stagflation -> S&P pts fall"),
+            "coef_stag_gold":    _c(20,   "Stagflation -> Gold $/oz rise"),
+            "coef_unc_gold":     _c(15,   "Uncertainty -> Gold $/oz rise"),
         },
-        "instruments": ["EURUSD"],
+        "instruments": ["EURUSD", "SP500", "XAUUSD"],
         "input_mapping": {
-            "net_longs_delta": {"source": "actual_value", "unit": "k contracts"}
+            "tariff_shock": {"source": "user_input", "unit": "%", "range": [0, 50]}
         },
     },
   },
 
-  # ── 8. EIA stocks pétrole ────────────────────────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 7. CREDIT_SYSTEMIC_EVENT
+  # Covers: bank failure, sovereign debt crisis, credit event, financial contagion
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "EIA — stocks pétroliers hebdomadaires",
-    "category": "report",
-    "sub_type": "EIA",
-    "instruments": ["BRENT", "EURUSD"],
-    "description": "Surprise stocks EIA → prix pétrole → canal inflation / risk appetite → EUR/USD",
-    "ai_rationale": (
-        "Une surprise négative sur les stocks EIA (stocks < consensus) signale une demande forte "
-        "ou une offre réduite, ce qui fait monter le pétrole. Impact EUR/USD indirect via "
-        "le canal inflation EU (coût imports) et le risk appetite."
-    ),
+    "name": "Credit & Systemic Stress",
+    "slug": "CREDIT_SYSTEMIC_EVENT",
+    "category": "credit_stress",
+    "heuristic_ver": 1,
+    "instruments": ["EURUSD", "SP500", "XAUUSD"],
+    "description": "Credit event / bank stress / sovereign crisis -> spread widening -> financial conditions tighten -> systemic risk-off",
+    "ai_rationale": "Credit events trigger spread widening (tightens financial conditions -> equities fall) and counterparty risk (forced deleveraging -> margin calls -> asset sales). USD strengthens via liquidity premium. Gold reaction: initially up (safe haven), then temporarily down if sold to cover margin calls.",
     "graph_json": {
         "nodes": [
-            _n("eia_surprise_mb",  "Surprise EIA (Mb vs consensus)", "input",        200, 45,  unit="Mb", description="négatif = stocks inférieurs aux attentes"),
-            _n("oil_reaction",     "Réaction pétrole (%)",           "intermediate", 200, 165, formula="-eia_surprise_mb * {{coef_eia_oil}}"),
-            _n("brent",            "Δ Brent ($/bbl)",                "output",       110, 290, formula="oil_reaction * {{coef_oil_dollar}}", unit="$/bbl", instrument="BRENT"),
-            _n("eurusd",           "EUR/USD",                        "output",       290, 290, formula="-oil_reaction * {{coef_oil_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("credit_trigger",   "Credit Event",           "input",        300, 50,  unit="bps", description="HY spread widening equivalent (100bps=moderate, 300bps=severe)"),
+            _n("spread_widening",  "Credit Spread Widening", "observable",   150, 200, formula="credit_trigger * {{coef_trig_spread}}", unit="bps"),
+            _n("counterparty_risk","Counterparty Risk",      "latent",       550, 200, formula="credit_trigger * {{coef_trig_cp}}"),
+            _n("fin_conditions",   "Financial Conditions",   "observable",   150, 370, formula="spread_widening * {{coef_spread_fc}}"),
+            _n("liq_premium",      "Liquidity Premium",      "latent",       400, 370, formula="spread_widening * {{coef_spread_liq}} + counterparty_risk * {{coef_cp_liq}}"),
+            _n("deleveraging",     "Forced Deleveraging",    "latent",       700, 370, formula="counterparty_risk * {{coef_cp_delev}}"),
+            _n("eurusd",           "EUR/USD",                "market_asset", 100, 570, formula="-liq_premium * {{coef_liq_eurusd}} - fin_conditions * {{coef_fc_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("sp500",            "S&P 500",                "market_asset", 400, 570, formula="-fin_conditions * {{coef_fc_sp}} - deleveraging * {{coef_delev_sp}}", unit="pts", instrument="SP500"),
+            _n("xauusd",           "Gold XAU/USD",           "market_asset", 700, 570, formula="liq_premium * {{coef_liq_gold}} - deleveraging * {{coef_delev_gold}}", unit="$/oz", instrument="XAUUSD"),
         ],
         "edges": [
-            _e("eia_surprise_mb", "oil_reaction", "solid",  "supply_demand",  "stocks bas → oil monte"),
-            _e("oil_reaction",    "brent",        "solid",  "direct"),
-            _e("oil_reaction",    "eurusd",       "dashed", "trade_balance",  "coût imports EU"),
+            _e("credit_trigger",   "spread_widening",  "solid",  "contagion",     strength=3, sign="positive", label="spread contagion"),
+            _e("credit_trigger",   "counterparty_risk","solid",  "systemic_fear", strength=3, sign="positive", label="systemic fear"),
+            _e("spread_widening",  "fin_conditions",   "solid",  "tightening",    strength=3, sign="positive", label="tightening"),
+            _e("spread_widening",  "liq_premium",      "solid",  "cash_demand",   strength=2, sign="positive"),
+            _e("counterparty_risk","liq_premium",      "solid",  "cash_hoarding", strength=3, sign="positive", label="cash hoarding"),
+            _e("counterparty_risk","deleveraging",     "solid",  "margin_calls",  strength=3, sign="positive", label="margin calls"),
+            _e("liq_premium",      "eurusd",           "solid",  "usd_flight",    strength=3, sign="negative", label="USD flight"),
+            _e("fin_conditions",   "eurusd",           "dashed", "fin_cond_fx",   strength=2, sign="negative"),
+            _e("fin_conditions",   "sp500",            "solid",  "valuation_earn",strength=3, sign="negative", label="valuation + earnings"),
+            _e("deleveraging",     "sp500",            "solid",  "forced_sell",   strength=3, sign="negative", label="forced selling"),
+            _e("liq_premium",      "xauusd",           "dashed", "safe_initial",  strength=2, sign="positive", label="safe haven (initial)"),
+            _e("deleveraging",     "xauusd",           "dashed", "sold_margin",   strength=2, sign="negative", label="sold to cover losses"),
         ],
         "coefficients": {
-            "coef_eia_oil":    _c(0.5,  "1 Mb sous consensus → % hausse pétrole"),
-            "coef_oil_dollar": _c(1.0,  "% hausse oil → Δ Brent $/bbl"),
-            "coef_oil_eurusd": _c(3.0,  "% hausse oil → EUR/USD pips (négatif pour EUR)"),
+            "coef_trig_spread":  _c(1.0,  "Credit event -> HY spread widening"),
+            "coef_trig_cp":      _c(0.60, "Credit event -> counterparty risk"),
+            "coef_spread_fc":    _c(0.50, "Spread widening -> fin conditions tightening"),
+            "coef_spread_liq":   _c(0.40, "Spread -> liquidity premium"),
+            "coef_cp_liq":       _c(0.60, "Counterparty risk -> liquidity premium"),
+            "coef_cp_delev":     _c(0.50, "Counterparty risk -> deleveraging"),
+            "coef_liq_eurusd":   _c(80,   "Liquidity premium -> EUR/USD pips fall"),
+            "coef_fc_eurusd":    _c(40,   "Fin conditions -> EUR/USD fall"),
+            "coef_fc_sp":        _c(100,  "Fin conditions tightening -> S&P pts fall"),
+            "coef_delev_sp":     _c(80,   "Deleveraging -> S&P pts fall"),
+            "coef_liq_gold":     _c(10,   "Liquidity premium -> Gold rise (initial)"),
+            "coef_delev_gold":   _c(15,   "Deleveraging -> Gold fall (sold for cash)"),
         },
-        "instruments": ["BRENT", "EURUSD"],
+        "instruments": ["EURUSD", "SP500", "XAUUSD"],
         "input_mapping": {
-            "eia_surprise_mb": {"source": "surprise", "unit": "Mb"}
+            "credit_trigger": {"source": "user_input", "unit": "bps", "range": [50, 500]}
         },
     },
   },
 
-  # ── 9. Risk-off global ───────────────────────────────────────────────────────
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 8. TECHNICAL_MOMENTUM_BREAKOUT
+  # Covers: MA crosses, RSI extremes, Bollinger squeezes, 52-week H/L, key level breaks
+  # ═══════════════════════════════════════════════════════════════════════════════
   {
-    "name": "Risk-off global — fuite vers la sécurité",
-    "category": "sentiment",
-    "sub_type": "Risk",
-    "instruments": ["EURUSD", "XAUUSD", "SP500"],
-    "description": "Choc d'aversion au risque → flight-to-safety → USD & Or montent, actions baissent",
-    "ai_rationale": (
-        "Un épisode de risk-off global (crash, crise financière, choc exogène) provoque "
-        "une fuite vers les actifs refuge : USD (liquidity premium), Or (store of value), "
-        "et une sortie des actifs risqués (actions, EM, EUR). Le VIX s'envole et amplifie la réaction."
-    ),
-    "graph_json": {
-        "nodes": [
-            _n("risk_score",     "Score risk-off (1−10)",     "input",        200, 45,  unit="score", description="1=légère tension, 10=crise majeure"),
-            _n("vix_spike",      "Δ VIX",                    "intermediate", 110, 165, formula="risk_score * {{coef_risk_vix}}"),
-            _n("gold_demand",    "Demande actifs refuge",    "intermediate", 290, 165, formula="risk_score * {{coef_risk_refuge}}"),
-            _n("usd_safe",       "USD safe-haven",           "intermediate", 110, 285, formula="vix_spike * {{coef_vix_usd}}"),
-            _n("eurusd",         "EUR/USD",                  "output",       80,  400, formula="-usd_safe * {{coef_usd_eurusd}}", unit="pips", instrument="EURUSD"),
-            _n("xauusd",         "Or (XAU/USD)",             "output",       200, 400, formula="gold_demand * {{coef_refuge_gold}}", unit="$/oz", instrument="XAUUSD"),
-            _n("sp500",          "S&P 500",                  "output",       320, 400, formula="-vix_spike * {{coef_vix_sp}}", unit="pts", instrument="SP500"),
-        ],
-        "edges": [
-            _e("risk_score",  "vix_spike",   "solid",  "fear_gauge"),
-            _e("risk_score",  "gold_demand", "solid",  "safe_haven"),
-            _e("vix_spike",   "usd_safe",    "solid",  "liquidity",   "fuite liquidité USD"),
-            _e("usd_safe",    "eurusd",      "solid",  "fx_safe_haven"),
-            _e("gold_demand", "xauusd",      "solid",  "store_value"),
-            _e("vix_spike",   "sp500",       "solid",  "risk_asset",  "risk premium"),
-        ],
-        "coefficients": {
-            "coef_risk_vix":    _c(4.0,  "Score risk → Δ VIX pts"),
-            "coef_risk_refuge": _c(2.0,  "Score risk → demande refuges (score)"),
-            "coef_vix_usd":     _c(0.8,  "Δ VIX → signal USD safe-haven"),
-            "coef_usd_eurusd":  _c(20.0, "Signal USD → EUR/USD pips (négatif)"),
-            "coef_refuge_gold": _c(15.0, "Demande refuge → Or $/oz"),
-            "coef_vix_sp":      _c(12.0, "1 pt VIX → S&P 500 pts (négatif)"),
-        },
-        "instruments": ["EURUSD", "XAUUSD", "SP500"],
-        "input_mapping": {
-            "risk_score": {"source": "impact_score_scaled", "unit": "score", "range": [1, 10]}
-        },
-    },
-  },
-
-  # ── 10. Tensions commerciales / tarifs ──────────────────────────────────────
-  {
-    "name": "Tarifs douaniers — tensions commerciales",
-    "category": "geopolitical",
-    "sub_type": "Trade",
+    "name": "Technical Momentum Breakout",
+    "slug": "TECHNICAL_MOMENTUM_BREAKOUT",
+    "category": "technical",
+    "heuristic_ver": 1,
     "instruments": ["EURUSD", "SP500"],
-    "description": "Annonce tarifs → choc exportations EU + risk-off → EUR/USD & actions",
-    "ai_rationale": (
-        "Les tarifs douaniers impactent l'EUR/USD via deux canaux : "
-        "le choc direct sur les exportations européennes (BCE plus dovish = EUR baisse) "
-        "et le canal risk-off global (incertitude → fuite USD → EUR baisse, S&P corrige)."
-    ),
+    "description": "Technical breakout/breakdown through key level -> stop cascade + momentum -> instrument price action",
+    "ai_rationale": "Technical events operate via market microstructure: breakout triggers stop orders, creating a cascade that amplifies the move. Volume confirmation distinguishes true breakouts from false breaks. The correlated asset move is weaker and follows with a lag.",
     "graph_json": {
         "nodes": [
-            _n("tariff_pct",     "Tarifs annoncés (%)",       "input",        200, 45,  unit="%"),
-            _n("eu_export_shock","Choc exportations EU",      "intermediate", 110, 165, formula="tariff_pct * {{coef_tariff_export}}"),
-            _n("risk_off_signal","Signal risk-off",           "intermediate", 290, 165, formula="tariff_pct * {{coef_tariff_risk}}"),
-            _n("ecb_dovish",     "Pression BCE dovish",       "intermediate", 110, 285, formula="eu_export_shock * {{coef_export_ecb}}"),
-            _n("eurusd",         "EUR/USD",                   "output",       110, 400, formula="-(ecb_dovish * {{coef_ecb_fx}} + risk_off_signal * {{coef_risk_fx}})", unit="pips", instrument="EURUSD"),
-            _n("sp500",          "S&P 500",                   "output",       290, 400, formula="-risk_off_signal * {{coef_risk_sp}}", unit="pts", instrument="SP500"),
+            _n("tech_signal",    "Technical Signal",       "input",        300, 50,  unit="sigma", description="+sigma = bullish breakout, -sigma = bearish breakdown"),
+            _n("momentum_score", "Momentum Score",         "observable",   150, 210, formula="tech_signal * {{coef_sig_mom}}"),
+            _n("stop_cascade",   "Stop Order Cascade",     "latent",       500, 210, formula="tech_signal * {{coef_sig_stop}}"),
+            _n("trend_strength", "Trend Strength",         "latent",       300, 380, formula="momentum_score * {{coef_mom_trend}} + stop_cascade * {{coef_stop_trend}}"),
+            _n("primary_inst",   "Primary Instrument",     "market_asset", 200, 560, formula="trend_strength * {{coef_trend_inst}} + stop_cascade * {{coef_stop_inst}}", unit="pips", instrument="EURUSD"),
+            _n("correl_move",    "Correlated Asset",       "market_asset", 500, 560, formula="trend_strength * {{coef_trend_corr}}", unit="pts", instrument="SP500"),
         ],
         "edges": [
-            _e("tariff_pct",      "eu_export_shock", "solid",  "trade_impact"),
-            _e("tariff_pct",      "risk_off_signal", "dashed", "uncertainty"),
-            _e("eu_export_shock", "ecb_dovish",      "solid",  "growth_slowdown"),
-            _e("ecb_dovish",      "eurusd",          "solid",  "rate_differential"),
-            _e("risk_off_signal", "eurusd",          "dashed", "safe_haven"),
-            _e("risk_off_signal", "sp500",           "solid",  "risk_asset"),
+            _e("tech_signal",    "momentum_score",  "solid",  "signal_strength",strength=3, sign="positive", label="signal strength"),
+            _e("tech_signal",    "stop_cascade",    "solid",  "stop_trigger",   strength=3, sign="positive", label="triggered stops"),
+            _e("momentum_score", "trend_strength",  "solid",  "trend_confirm",  strength=3, sign="positive"),
+            _e("stop_cascade",   "trend_strength",  "solid",  "amplification",  strength=2, sign="positive", label="amplification"),
+            _e("trend_strength", "primary_inst",    "solid",  "price_action",   strength=3, sign="positive", label="price action"),
+            _e("stop_cascade",   "primary_inst",    "solid",  "liquidity_grab", strength=2, sign="positive", label="liquidity grab"),
+            _e("trend_strength", "correl_move",     "dashed", "spillover",      strength=2, sign="positive", label="spillover"),
         ],
         "coefficients": {
-            "coef_tariff_export": _c(1.5,  "% tarif → pression exports EU"),
-            "coef_tariff_risk":   _c(1.0,  "% tarif → signal risk-off"),
-            "coef_export_ecb":    _c(0.5,  "Choc exports → pression dovish BCE"),
-            "coef_ecb_fx":        _c(15.0, "Pression BCE dovish → EUR/USD pips (négatif)"),
-            "coef_risk_fx":       _c(10.0, "Risk-off → EUR/USD pips (négatif)"),
-            "coef_risk_sp":       _c(25.0, "Risk-off → S&P 500 pts (négatif)"),
+            "coef_sig_mom":    _c(1.0,  "Signal sigma -> momentum score"),
+            "coef_sig_stop":   _c(0.60, "Signal sigma -> stop cascade magnitude"),
+            "coef_mom_trend":  _c(0.70, "Momentum -> trend strength"),
+            "coef_stop_trend": _c(0.50, "Stop cascade -> trend amplification"),
+            "coef_trend_inst": _c(50,   "Trend strength -> primary instrument (pips)"),
+            "coef_stop_inst":  _c(30,   "Stop cascade -> extra move (pips)"),
+            "coef_trend_corr": _c(20,   "Trend -> correlated asset (pts)"),
         },
         "instruments": ["EURUSD", "SP500"],
         "input_mapping": {
-            "tariff_pct": {"source": "impact_score_pct", "unit": "%"}
+            "tech_signal": {"source": "user_input", "unit": "sigma", "range": [-5, 5]}
+        },
+    },
+  },
+
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 9. SENTIMENT_POSITIONING_EXTREME
+  # Covers: VIX spike extremes, COT crowded positions, skew extremes, yield curve signals
+  # ═══════════════════════════════════════════════════════════════════════════════
+  {
+    "name": "Sentiment & Positioning Extreme",
+    "slug": "SENTIMENT_POSITIONING_EXTREME",
+    "category": "sentiment",
+    "heuristic_ver": 1,
+    "instruments": ["SP500", "EURUSD", "XAUUSD"],
+    "description": "Extreme sentiment / crowded positioning -> mean reversion force -> contrarian price action",
+    "ai_rationale": "When positioning reaches statistical extremes (COT multi-year high, VIX spike above 40, extreme put/call skew), the asymmetry of forced unwinds generates a contrarian signal. The mean reversion is not immediate — it typically takes 3-10 days to materialize. Gold falls when fear recedes.",
+    "graph_json": {
+        "nodes": [
+            _n("sent_trigger",   "Sentiment Extreme",      "input",        300, 50,  unit="sigma", description="+sigma = extreme fear/oversold (contrarian buy), -sigma = extreme greed"),
+            _n("pos_imbalance",  "Positioning Imbalance",  "observable",   150, 210, formula="sent_trigger * {{coef_sent_pos}}"),
+            _n("vol_regime",     "Volatility Regime",      "observable",   550, 210, formula="-sent_trigger * {{coef_sent_vol}}"),
+            _n("crowd_risk",     "Crowded Trade Risk",     "latent",       150, 380, formula="pos_imbalance * {{coef_pos_crowd}}"),
+            _n("mr_force",       "Mean Reversion Force",  "latent",       380, 380, formula="crowd_risk * {{coef_crowd_mr}}"),
+            _n("sp500",          "S&P 500",                "market_asset", 200, 580, formula="mr_force * {{coef_mr_sp}} + vol_regime * {{coef_vol_sp}}", unit="pts", instrument="SP500"),
+            _n("eurusd",         "EUR/USD",                "market_asset", 480, 580, formula="mr_force * {{coef_mr_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("xauusd",         "Gold XAU/USD",           "market_asset", 720, 580, formula="-mr_force * {{coef_mr_gold}}", unit="$/oz", instrument="XAUUSD"),
+        ],
+        "edges": [
+            _e("sent_trigger",  "pos_imbalance", "solid",  "flow_data",    strength=3, sign="positive", label="flow / positioning data"),
+            _e("sent_trigger",  "vol_regime",    "dashed", "vol_signal",   strength=2, sign="negative", label="vol regime shift"),
+            _e("pos_imbalance", "crowd_risk",    "solid",  "crowd_build",  strength=3, sign="positive"),
+            _e("crowd_risk",    "mr_force",      "solid",  "squeeze_setup",strength=3, sign="positive", label="squeeze setup"),
+            _e("mr_force",      "sp500",         "solid",  "contrarian_sp",strength=3, sign="positive", label="contrarian rally/drop"),
+            _e("vol_regime",    "sp500",         "dashed", "vol_collapse", strength=2, sign="positive", label="vol compression"),
+            _e("mr_force",      "eurusd",        "solid",  "unwind_fx",    strength=2, sign="positive", label="position unwind"),
+            _e("mr_force",      "xauusd",        "dashed", "safe_exit",    strength=2, sign="negative", label="safe haven exit on recovery"),
+        ],
+        "coefficients": {
+            "coef_sent_pos": _c(1.0,  "Sentiment extreme -> positioning imbalance"),
+            "coef_sent_vol": _c(0.50, "Extreme fear -> vol expansion (inverted for compression)"),
+            "coef_pos_crowd":_c(0.80, "Positioning -> crowded trade risk"),
+            "coef_crowd_mr": _c(0.70, "Crowded trade -> mean reversion force"),
+            "coef_mr_sp":    _c(60,   "Mean reversion -> S&P pts"),
+            "coef_vol_sp":   _c(30,   "Vol compression -> S&P pts"),
+            "coef_mr_eurusd":_c(40,   "Mean reversion -> EUR/USD pips"),
+            "coef_mr_gold":  _c(15,   "Fear recedes -> Gold falls ($/oz)"),
+        },
+        "instruments": ["SP500", "EURUSD", "XAUUSD"],
+        "input_mapping": {
+            "sent_trigger": {"source": "user_input", "unit": "sigma", "range": [-4, 4]}
+        },
+    },
+  },
+
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 10. COMMODITY_INVENTORY_REPORT
+  # Covers: EIA crude oil weekly, EIA products, API crude, WASDE grain stocks
+  # ═══════════════════════════════════════════════════════════════════════════════
+  {
+    "name": "Commodity Inventory Report",
+    "slug": "COMMODITY_INVENTORY_REPORT",
+    "category": "commodity",
+    "heuristic_ver": 1,
+    "instruments": ["BRENT", "EURUSD", "XAUUSD"],
+    "description": "Weekly inventory surprise -> supply/demand balance -> Brent spot + forward curve -> EUR/USD and Gold (inflation channel)",
+    "ai_rationale": "EIA / API reports provide weekly updates on oil supply/demand balance. A draw vs consensus signals demand strength or supply tightness -> Brent spot rally + backwardation. Secondary channel: energy inflation expectations impact EU trade balance and gold as inflation hedge.",
+    "graph_json": {
+        "nodes": [
+            _n("inv_surprise",    "Inventory Surprise",     "input",        300, 50,  unit="mb", description="+mb = draw vs consensus (bullish), -mb = build"),
+            _n("sd_balance",      "Supply/Demand Balance",  "observable",   200, 210, formula="inv_surprise * {{coef_surp_balance}}"),
+            _n("price_pressure",  "Spot Price Pressure",    "latent",       200, 380, formula="sd_balance * {{coef_balance_pressure}}"),
+            _n("fwd_curve_shift", "Forward Curve Shift",    "observable",   550, 380, formula="sd_balance * {{coef_balance_fwd}}"),
+            _n("energy_cost_fwd", "Energy Cost Outlook",    "latent",       700, 380, formula="price_pressure * {{coef_pressure_cost}}"),
+            _n("brent",           "Brent Crude",            "market_asset", 200, 580, formula="price_pressure * {{coef_pressure_brent}} + fwd_curve_shift * {{coef_fwd_brent}}", unit="$/bbl", instrument="BRENT"),
+            _n("eurusd",          "EUR/USD",                "market_asset", 520, 580, formula="-energy_cost_fwd * {{coef_energy_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("xauusd",          "Gold XAU/USD",           "market_asset", 760, 580, formula="energy_cost_fwd * {{coef_energy_gold}}", unit="$/oz", instrument="XAUUSD"),
+        ],
+        "edges": [
+            _e("inv_surprise",    "sd_balance",     "solid",  "tightness_sig",  strength=3, sign="positive", label="tightness signal"),
+            _e("sd_balance",      "price_pressure", "solid",  "spot_impact",    strength=3, sign="positive"),
+            _e("sd_balance",      "fwd_curve_shift","solid",  "curve_structure",strength=2, sign="positive", label="curve structure"),
+            _e("price_pressure",  "energy_cost_fwd","dashed", "cost_outlook",   strength=2, sign="positive"),
+            _e("price_pressure",  "brent",          "solid",  "spot_move",      strength=3, sign="positive", label="spot move"),
+            _e("fwd_curve_shift", "brent",          "solid",  "backwardation",  strength=2, sign="positive", label="curve normalization"),
+            _e("energy_cost_fwd", "eurusd",         "dashed", "trade_deficit",  strength=2, sign="negative", label="EU trade deficit"),
+            _e("energy_cost_fwd", "xauusd",         "dashed", "infl_hedge",     strength=2, sign="positive", label="inflation hedge"),
+        ],
+        "coefficients": {
+            "coef_surp_balance":    _c(1.0,  "1mb surprise -> supply/demand balance signal"),
+            "coef_balance_pressure":_c(0.8,  "Balance -> spot price pressure"),
+            "coef_balance_fwd":     _c(0.4,  "Balance -> forward curve shift"),
+            "coef_pressure_cost":   _c(0.3,  "Price pressure -> energy cost outlook"),
+            "coef_pressure_brent":  _c(0.5,  "1mb surprise -> Brent $/bbl move"),
+            "coef_fwd_brent":       _c(0.2,  "Forward curve shift -> Brent $/bbl"),
+            "coef_energy_eurusd":   _c(20,   "Energy cost rise -> EUR/USD pips fall"),
+            "coef_energy_gold":     _c(5,    "Energy cost rise -> Gold $/oz (inflation hedge)"),
+        },
+        "instruments": ["BRENT", "EURUSD", "XAUUSD"],
+        "input_mapping": {
+            "inv_surprise": {"source": "surprise", "unit": "mb", "range": [-10, 10]}
+        },
+    },
+  },
+
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 11. INSTITUTIONAL_FLOW
+  # Covers: COT repositioning, FX intervention, end-of-month rebalancing
+  # ═══════════════════════════════════════════════════════════════════════════════
+  {
+    "name": "Institutional Flow & Repositioning",
+    "slug": "INSTITUTIONAL_FLOW",
+    "category": "positioning",
+    "heuristic_ver": 1,
+    "instruments": ["EURUSD", "SP500", "XAUUSD"],
+    "description": "Large institutional flow without direct fundamental trigger -> order flow imbalance -> momentum + mean reversion risk",
+    "ai_rationale": "Institutional repositioning (COT data, FX intervention, end-of-month rebalancing) moves prices via order flow mechanics rather than fundamental repricing. The move is self-limiting: large flows reduce liquidity and create a mean reversion setup once the flow exhausts.",
+    "graph_json": {
+        "nodes": [
+            _n("flow_trigger",    "Institutional Flow",     "input",        300, 50,  unit="$B", description="+$B = accumulation (buy), -$B = distribution (sell)"),
+            _n("order_imbalance", "Order Flow Imbalance",   "observable",   150, 210, formula="flow_trigger * {{coef_flow_imbalance}}"),
+            _n("market_impact",   "Market Impact",          "latent",       150, 380, formula="order_imbalance * {{coef_imbalance_impact}}"),
+            _n("momentum_sig",    "Flow Momentum",          "latent",       450, 380, formula="market_impact * {{coef_impact_mom}} + order_imbalance * {{coef_imbalance_mom}}"),
+            _n("mr_risk",         "Mean Reversion Risk",    "latent",       700, 380, formula="-momentum_sig * {{coef_mom_mr}}"),
+            _n("eurusd",          "EUR/USD",                "market_asset", 150, 580, formula="momentum_sig * {{coef_mom_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("sp500",           "S&P 500",                "market_asset", 430, 580, formula="momentum_sig * {{coef_mom_sp}}", unit="pts", instrument="SP500"),
+            _n("xauusd",          "Gold XAU/USD",           "market_asset", 700, 580, formula="momentum_sig * {{coef_mom_gold}}", unit="$/oz", instrument="XAUUSD"),
+        ],
+        "edges": [
+            _e("flow_trigger",    "order_imbalance","solid",  "execution_impact",strength=3, sign="positive", label="execution impact"),
+            _e("order_imbalance", "market_impact",  "solid",  "price_impact",    strength=3, sign="positive"),
+            _e("market_impact",   "momentum_sig",   "solid",  "momentum_build",  strength=2, sign="positive"),
+            _e("order_imbalance", "momentum_sig",   "solid",  "order_flow",      strength=2, sign="positive"),
+            _e("momentum_sig",    "mr_risk",        "dashed", "exhaustion",      strength=2, sign="negative", label="flow exhaustion"),
+            _e("momentum_sig",    "eurusd",         "solid",  "fx_flow",         strength=3, sign="positive"),
+            _e("momentum_sig",    "sp500",          "solid",  "eq_flow",         strength=2, sign="positive"),
+            _e("momentum_sig",    "xauusd",         "dashed", "gold_flow",       strength=2, sign="positive"),
+        ],
+        "coefficients": {
+            "coef_flow_imbalance":   _c(0.50, "$1B flow -> order imbalance score"),
+            "coef_imbalance_impact": _c(0.60, "Imbalance -> market impact"),
+            "coef_impact_mom":       _c(0.70, "Market impact -> momentum"),
+            "coef_imbalance_mom":    _c(0.40, "Imbalance -> momentum direct"),
+            "coef_mom_mr":           _c(0.40, "Momentum -> mean reversion risk (inverted)"),
+            "coef_mom_eurusd":       _c(30,   "Momentum -> EUR/USD pips"),
+            "coef_mom_sp":           _c(15,   "Momentum -> S&P pts"),
+            "coef_mom_gold":         _c(8,    "Momentum -> Gold $/oz"),
+        },
+        "instruments": ["EURUSD", "SP500", "XAUUSD"],
+        "input_mapping": {
+            "flow_trigger": {"source": "cot_report", "field": "net_non_commercial", "unit": "$B", "range": [-20, 20]}
+        },
+    },
+  },
+
+  # ═══════════════════════════════════════════════════════════════════════════════
+  # 12. UNCLASSIFIED_IMPACT
+  # Fallback: any event that doesn't fit the 11 regimes above
+  # Low confidence — direct instrument impact without causal chain
+  # ═══════════════════════════════════════════════════════════════════════════════
+  {
+    "name": "Unclassified Market Impact",
+    "slug": "UNCLASSIFIED_IMPACT",
+    "category": "unclassified",
+    "heuristic_ver": 1,
+    "instruments": ["EURUSD", "SP500", "XAUUSD"],
+    "description": "Fallback template — event doesn't fit established regimes. Direct instrument impact without causal chain. Low confidence.",
+    "ai_rationale": "Used when no regime template matches with sufficient confidence. No intermediate causal nodes — direct trigger to output. Precision scores from this template are marked low-confidence and should not be used for calibration.",
+    "graph_json": {
+        "nodes": [
+            _n("unknown_trigger","Market Trigger",         "input",        300, 80,  unit="score", description="Impact score: + positive (bullish), - negative (bearish)"),
+            _n("market_reaction","Market Reaction",        "latent",       300, 280, formula="unknown_trigger * {{coef_trig_react}}"),
+            _n("eurusd",         "EUR/USD",                "market_asset", 100, 500, formula="market_reaction * {{coef_react_eurusd}}", unit="pips", instrument="EURUSD"),
+            _n("sp500",          "S&P 500",                "market_asset", 300, 500, formula="market_reaction * {{coef_react_sp}}", unit="pts", instrument="SP500"),
+            _n("xauusd",         "Gold XAU/USD",           "market_asset", 520, 500, formula="market_reaction * {{coef_react_gold}}", unit="$/oz", instrument="XAUUSD"),
+        ],
+        "edges": [
+            _e("unknown_trigger","market_reaction","dashed", "direct_impact",strength=1, sign="positive", label="direct impact (low confidence)"),
+            _e("market_reaction","eurusd",         "dashed", "output_fx",    strength=1, sign="positive"),
+            _e("market_reaction","sp500",          "dashed", "output_eq",    strength=1, sign="positive"),
+            _e("market_reaction","xauusd",         "dashed", "output_gold",  strength=1, sign="positive"),
+        ],
+        "coefficients": {
+            "coef_trig_react":   _c(0.50, "Trigger score -> market reaction (low confidence)"),
+            "coef_react_eurusd": _c(20,   "Reaction -> EUR/USD pips (low confidence)"),
+            "coef_react_sp":     _c(15,   "Reaction -> S&P pts (low confidence)"),
+            "coef_react_gold":   _c(5,    "Reaction -> Gold $/oz (low confidence)"),
+        },
+        "instruments": ["EURUSD", "SP500", "XAUUSD"],
+        "input_mapping": {
+            "unknown_trigger": {"source": "user_input", "unit": "score", "range": [-5, 5]}
         },
     },
   },
@@ -546,7 +763,18 @@ def init_tables(conn):
 
 
 def seed_templates(conn):
-    """Insère les templates built-in ; met à jour si heuristic_ver a été augmentée."""
+    """Insert built-in templates; update if heuristic_ver increased. One-shot migration: truncates old non-regime templates."""
+    # One-shot migration: remove templates that don't have a slug in REGIME_SLUGS
+    existing_slugs = conn.execute(
+        "SELECT name FROM causal_graph_templates WHERE created_by='system'"
+    ).fetchall()
+    for row in existing_slugs:
+        old_name = row["name"]
+        # Check if any new template has this name
+        has_match = any(t["name"] == old_name for t in BUILT_IN_TEMPLATES)
+        if not has_match:
+            conn.execute("DELETE FROM causal_graph_templates WHERE name=? AND created_by='system'", (old_name,))
+
     for t in BUILT_IN_TEMPLATES:
         ver = t.get("heuristic_ver", 1)
         existing = conn.execute(
diff --git a/backend/services/database.py b/backend/services/database.py
index c2aef85..493f931 100644
--- a/backend/services/database.py
+++ b/backend/services/database.py
@@ -1238,6 +1238,16 @@ def init_db():
     except Exception:
         pass
 
+    # Purge macro_series_log entries from multi-country contamination.
+    # USD-series (UNRATE, PAYEMS…) were logging both US and foreign events → flip-flop.
+    # Safe to truncate: all data is synthetic backfill, no real live captures yet.
+    try:
+        c.execute(
+            "DELETE FROM macro_series_log WHERE source IN ('backfill', 'calendar_sync')"
+        )
+    except Exception:
+        pass
+
     conn.commit()
     conn.close()
 
diff --git a/backend/services/macro_series_log.py b/backend/services/macro_series_log.py
index 3be881c..91fb06d 100644
--- a/backend/services/macro_series_log.py
+++ b/backend/services/macro_series_log.py
@@ -83,8 +83,10 @@ def backfill_from_ff_calendar(conn) -> dict:
     """
     Seed macro_series_log from existing ff_calendar rows (historical).
     Only inserts rows that don't already exist (idempotent).
-    Skips events without series_id.
+    Filters by ff_currency to avoid multi-country contamination.
     """
+    currency_map = _series_currency_map()
+
     rows = conn.execute(
         """SELECT series_id, event_name, event_date, actual_value, forecast_value,
                   previous_value, currency, impact, fetched_at
@@ -96,6 +98,9 @@ def backfill_from_ff_calendar(conn) -> dict:
 
     inserted = 0
     for r in rows:
+        expected = currency_map.get(r['series_id'])
+        if expected and r['currency'] != expected:
+            continue
         already = conn.execute(
             "SELECT 1 FROM macro_series_log WHERE series_id=? AND event_date=? AND source='backfill' LIMIT 1",
             (r['series_id'], r['event_date'])
@@ -135,11 +140,22 @@ def backfill_from_ff_calendar(conn) -> dict:
     return {"inserted": inserted, "scanned": len(rows)}
 
 
+def _series_currency_map() -> dict:
+    """Return {series_id: ff_currency} for series that have a currency restriction."""
+    try:
+        from services.fred_bootstrap import FRED_SERIES
+        return {sid: meta['ff_currency'] for sid, meta in FRED_SERIES.items() if meta.get('ff_currency')}
+    except Exception:
+        return {}
+
+
 def scan_and_log_all(conn, source: str = 'calendar_sync') -> dict:
     """
     After a calendar sync, scan all ff_calendar rows with series_id and log any changes.
-    Typically called at end of each 6h sync cycle.
+    Filters by ff_currency to avoid multi-country flip-flop (e.g. US vs CA unemployment).
     """
+    currency_map = _series_currency_map()
+
     rows = conn.execute(
         """SELECT series_id, event_name, event_date, actual_value, forecast_value,
                   previous_value, currency, impact
@@ -150,6 +166,9 @@ def scan_and_log_all(conn, source: str = 'calendar_sync') -> dict:
 
     logged = 0
     for r in rows:
+        expected = currency_map.get(r['series_id'])
+        if expected and r['currency'] != expected:
+            continue
         did_log = log_if_changed(
             conn,
             series_id=r['series_id'],
diff --git a/frontend/src/pages/MacroSeriesPage.tsx b/frontend/src/pages/MacroSeriesPage.tsx
index cf6b8a5..8faa4f5 100644
--- a/frontend/src/pages/MacroSeriesPage.tsx
+++ b/frontend/src/pages/MacroSeriesPage.tsx
@@ -372,6 +372,18 @@ export default function MacroSeriesPage() {
 
   const EVO_COLORS = ['#f59e0b', '#38bdf8', '#a78bfa', '#34d399', '#fb923c', '#f472b6']
 
+  // Compute focused event date for the Log tab (used by both chart and table)
+  const logFocusDate = (() => {
+    if (!forecastEvolution.allDates.length) return null
+    const today = new Date().toISOString().slice(0, 10)
+    const twelveMonthsAgo = new Date(); twelveMonthsAgo.setFullYear(twelveMonthsAgo.getFullYear() - 1)
+    const cutoff = twelveMonthsAgo.toISOString().slice(0, 10)
+    const upcoming   = forecastEvolution.allDates.filter(d => d >= today).sort()
+    const recentPast = forecastEvolution.allDates.filter(d => d >= cutoff && d < today).sort().reverse()
+    const ordered    = [...upcoming, ...recentPast]
+    return selectedEventDate ?? ordered[0] ?? null
+  })()
+
   return (
     <div className="flex h-full overflow-hidden" style={{ minHeight: 0 }}>
       {/* Sidebar */}
@@ -531,7 +543,12 @@ export default function MacroSeriesPage() {
           <div className="flex items-center justify-between mb-3">
             <span className="text-sm font-medium text-slate-300">
               Journal des changements — {selectedId}
-              <span className="text-slate-500 text-xs ml-2">({logEntries.length} entrées)</span>
+              {logFocusDate && <span className="text-slate-400 text-xs ml-2">· release {logFocusDate}</span>}
+              <span className="text-slate-500 text-xs ml-2">
+                ({logFocusDate
+                  ? logEntries.filter(e => e.event_date === logFocusDate).length
+                  : logEntries.length} entrées)
+              </span>
             </span>
             {logEntries.length === 0 && (
               <button onClick={handleBackfill} disabled={backfilling}
@@ -543,18 +560,20 @@ export default function MacroSeriesPage() {
           {/* Forecast evolution — focus one release at a time */}
           {forecastEvolution.allDates.length > 0 && (() => {
             const today = new Date().toISOString().slice(0, 10)
-            const upcoming = forecastEvolution.allDates.filter(d => d >= today).sort()
-            const past     = forecastEvolution.allDates.filter(d => d < today).sort().reverse()
-            const ordered  = [...upcoming, ...past]
+            const twelveMonthsAgo = new Date(); twelveMonthsAgo.setFullYear(twelveMonthsAgo.getFullYear() - 1)
+            const cutoff = twelveMonthsAgo.toISOString().slice(0, 10)
+            const upcoming   = forecastEvolution.allDates.filter(d => d >= today).sort()
+            const recentPast = forecastEvolution.allDates.filter(d => d >= cutoff && d < today).sort().reverse()
+            const ordered    = [...upcoming, ...recentPast]
             const focusDate = selectedEventDate ?? ordered[0] ?? null
             if (!focusDate) return null
 
             const allPts = forecastEvolution.byDate[focusDate] ?? []
             // Keep only the 4 weeks window before event_date
-            const cutoff = new Date(focusDate)
-            cutoff.setDate(cutoff.getDate() - 28)
-            const cutoffStr = cutoff.toISOString().slice(0, 16)
-            const pts = allPts.filter(p => p.time >= cutoffStr)
+            const windowStart = new Date(focusDate)
+            windowStart.setDate(windowStart.getDate() - 28)
+            const windowStr = windowStart.toISOString().slice(0, 16)
+            const pts = allPts.filter(p => p.time >= windowStr)
             const chartPts = pts.map(p => ({ time: p.time.slice(0, 10), forecast: p.forecast, actual: p.actual }))
             const hasActual = pts.some(p => p.actual != null)
             const actualVal = pts.find(p => p.actual != null)?.actual ?? null
@@ -647,7 +666,7 @@ export default function MacroSeriesPage() {
                   </tr>
                 </thead>
                 <tbody>
-                  {[...logEntries].reverse().map((e, i) => {
+                  {[...logEntries].filter(e => !logFocusDate || e.event_date === logFocusDate).reverse().map((e, i) => {
                     const isActual = e.actual_value != null
                     const isForecastChange = e.changed === 'forecast' || e.changed === 'both'
                     return (