Add trailing stops and parameter sweeps

Trailing stops: strategies can pass trailing_stop_pct to enter_long/enter_short.
advance_trailing_stop in app/engine/portfolio.py ratchets the stop with the price
(up for longs, down for shorts) and never loosens; the engine persists the
ratcheted level and the backtester applies the same logic. Position gains a
trailing_stop_pct column (additive migration). momentum exposes it as a param.

Parameter sweeps: app/backtest/sweep.py runs a cartesian grid through the same
backtester and ranks by return minus max drawdown. POST /api/sweep plus a
dashboard Parameter sweep panel.

backend/app/engine/strategies/base.py

@@ -26,6 +26,7 @@ class Intent:
     size: float | None = None
     stop_loss: float | None = None
     take_profit: float | None = None
+    trailing_stop_pct: float = 0.0
     reason: str = ""
 
 
@@ -121,18 +122,24 @@ class StrategyContext:
         size: float | None = None,
         stop_loss: float | None = None,
         take_profit: float | None = None,
+        trailing_stop_pct: float = 0.0,
         reason: str = "",
     ) -> None:
-        self._intents.append(Intent("enter_long", size, stop_loss, take_profit, reason))
+        self._intents.append(
+            Intent("enter_long", size, stop_loss, take_profit, trailing_stop_pct, reason)
+        )
 
     def enter_short(
         self,
         size: float | None = None,
         stop_loss: float | None = None,
         take_profit: float | None = None,
+        trailing_stop_pct: float = 0.0,
         reason: str = "",
     ) -> None:
-        self._intents.append(Intent("enter_short", size, stop_loss, take_profit, reason))
+        self._intents.append(
+            Intent("enter_short", size, stop_loss, take_profit, trailing_stop_pct, reason)
+        )
 
     def close(self, reason: str = "") -> None:
         self._intents.append(Intent("close", reason=reason))

backend/app/engine/strategies/momentum.py

@@ -21,19 +21,22 @@ class Momentum(Strategy):
         "entry_threshold": 0.01,
         "atr_period": 14,
         "atr_stop_mult": 2.0,
+        "trailing_stop_pct": 0.0,
         "size": 1.0,
     }
     param_help: ClassVar[dict] = {
         "period": "ROC lookback in bars",
         "entry_threshold": "Minimum ROC to enter (0.01 = 1%)",
-        "atr_period": "ATR lookback for the stop",
+        "atr_period": "ATR lookback for the initial stop",
         "atr_stop_mult": "Stop distance in ATRs (0 disables)",
+        "trailing_stop_pct": "Trailing stop distance as a fraction of price (0 disables)",
         "size": "Fraction of equity per trade",
     }
     param_bounds: ClassVar[dict] = {
         "period": (2, 200),
         "entry_threshold": (0.0, 1.0),
         "atr_stop_mult": (0.0, 10.0),
+        "trailing_stop_pct": (0.0, 0.5),
         "size": (0.01, 1.0),
     }
 
@@ -52,6 +55,7 @@ class Momentum(Strategy):
             ctx.enter_long(
                 size=float(self.params["size"]),
                 stop_loss=stop,
+                trailing_stop_pct=float(self.params["trailing_stop_pct"]),
                 reason=f"ROC {value:.2%} above threshold",
             )
         elif ctx.side == PositionSide.LONG and value < 0: