feat: instrument model

backend/services/instrument_models.py

@@ -1085,25 +1085,29 @@ def simulate_timeline(
     structural_pips = round(float(vals_struct.get(output_id, 0.0)), 1)
     fundamental_level_base = round(price_intercept + structural_pips * pip_to_price, 6)
 
-    # Auto-anchor : caler le niveau fondamental sur le prix réel au début de la fenêtre.
-    # start_offset = prix_réel_début - niveau_fondamental_machine
-    # → synthetic_price(t) = prix_réel_début + event_pips(t) * pip_to_price
-    start_offset = 0.0
+    # Guidance EMA : la baseline de la synthétique est l'EMA lissée du prix réel.
+    # synthetic_price(t) = EMA(t) + event_pips(t) × pip_to_price
+    # → sans event perturbateur : synthétique colle au lissé historique
+    # → avec events : déviation proportionnelle à leur contribution
+    ema_prices: dict[str, float] = {}
+    last_ema: float = fundamental_level_base   # fallback si pas de données prix
     try:
-        ph_row = conn.execute(
-            """SELECT close FROM price_history_cache
-               WHERE instrument=? AND date>=? ORDER BY date ASC LIMIT 1""",
-            (inst_upper, str(date_from))
-        ).fetchone()
-        if ph_row is None:
-            # Weekends/jours fériés : on remonte jusqu'à 7 jours avant
-            ph_row = conn.execute(
-                """SELECT close FROM price_history_cache
-                   WHERE instrument=? AND date>=? ORDER BY date ASC LIMIT 1""",
-                (inst_upper, str(date_from - timedelta(days=7)))
-            ).fetchone()
-        if ph_row:
-            start_offset = round(float(ph_row["close"]) - fundamental_level_base, 6)
+        # 30j de warmup avant date_from pour que l'EMA soit stabilisée dès le début
+        warmup_from = str(date_from - timedelta(days=30))
+        ph_rows = conn.execute(
+            """SELECT date, close FROM price_history_cache
+               WHERE instrument=? AND date>=? ORDER BY date ASC""",
+            (inst_upper, warmup_from)
+        ).fetchall()
+        alpha = 0.15   # lissage EMA (~6j de demi-vie)
+        ema_val: Optional[float] = None
+        for r in ph_rows:
+            c = float(r["close"])
+            ema_val = c if ema_val is None else alpha * c + (1.0 - alpha) * ema_val
+            if r["date"] >= str(date_from):
+                ema_prices[r["date"]] = round(ema_val, 6)
+        if ema_prices:
+            last_ema = list(ema_prices.values())[-1]
     except Exception:
         pass
 
@@ -1150,13 +1154,23 @@ def simulate_timeline(
             net    = structural_pips
             regime_label = "BALANCED"
 
+        # Guide price : EMA du prix réel si disponible, sinon dernier EMA connu (futur)
+        date_str = str(cur)
+        if date_str in ema_prices:
+            guide_price = ema_prices[date_str]
+            last_ema    = guide_price
+        else:
+            guide_price = last_ema   # dates futures : tient le dernier EMA connu
+
+        event_pips = round(net - structural_pips, 1)
+
         timeline.append({
-            "date":              str(cur),
+            "date":              date_str,
             "net_pips":          net,
             "structural_pips":   structural_pips,
-            "event_pips":        round(net - structural_pips, 1),
-            "fundamental_level": round(fundamental_level_base + start_offset, 6),
-            "synthetic_price":   round(price_intercept + start_offset + net * pip_to_price, 6),
+            "event_pips":        event_pips,
+            "fundamental_level": guide_price,
+            "synthetic_price":   round(guide_price + event_pips * pip_to_price, 6),
             "regime":            regime_label,
             "nodes":             {k: round(float(v), 1) for k, v in vals.items()},
             "active_events":     active_events_detail,