From cb55c81dbc43df83ef4d5b717fe22b4d04a93d2e Mon Sep 17 00:00:00 2001
From: TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com>
Date: Wed, 1 Apr 2026 18:44:20 +0900
Subject: feat(strategy): apply filters, conviction scoring, and ATR stops to
 all strategies

---
 .../strategy-engine/strategies/rsi_strategy.py     | 32 ++++++++++++++++++++--
 1 file changed, 30 insertions(+), 2 deletions(-)

(limited to 'services/strategy-engine/strategies/rsi_strategy.py')

diff --git a/services/strategy-engine/strategies/rsi_strategy.py b/services/strategy-engine/strategies/rsi_strategy.py
index 490a8a9..0ec6780 100644
--- a/services/strategy-engine/strategies/rsi_strategy.py
+++ b/services/strategy-engine/strategies/rsi_strategy.py
@@ -55,10 +55,34 @@ class RsiStrategy(BaseStrategy):
         if self._quantity <= 0:
             raise ValueError(f"Quantity must be positive, got {self._quantity}")
 
+        self._init_filters(
+            require_trend=False,
+            adx_threshold=float(params.get("adx_threshold", 25.0)),
+            min_volume_ratio=float(params.get("min_volume_ratio", 0.5)),
+            atr_stop_multiplier=float(params.get("atr_stop_multiplier", 2.0)),
+            atr_tp_multiplier=float(params.get("atr_tp_multiplier", 3.0)),
+        )
+
     def reset(self) -> None:
         self._closes.clear()
 
+    def _rsi_conviction(self, rsi_value: float) -> float:
+        """Map RSI value to conviction strength (0.0-1.0).
+
+        For BUY (oversold): lower RSI = higher conviction.
+        For SELL (overbought): higher RSI = higher conviction.
+        Linear scale from the threshold to the extreme (0 or 100).
+        """
+        if rsi_value < self._oversold:
+            # RSI 0 -> 1.0, RSI at oversold threshold -> 0.0
+            return min(1.0, max(0.1, (self._oversold - rsi_value) / self._oversold))
+        elif rsi_value > self._overbought:
+            # RSI 100 -> 1.0, RSI at overbought threshold -> 0.0
+            return min(1.0, max(0.1, (rsi_value - self._overbought) / (100.0 - self._overbought)))
+        return 0.0
+
     def on_candle(self, candle: Candle) -> Signal | None:
+        self._update_filter_data(candle)
         self._closes.append(float(candle.close))
 
         if len(self._closes) < self._period + 1:
@@ -71,22 +95,26 @@ class RsiStrategy(BaseStrategy):
             return None
 
         if rsi_value < self._oversold:
-            return Signal(
+            signal = Signal(
                 strategy=self.name,
                 symbol=candle.symbol,
                 side=OrderSide.BUY,
                 price=candle.close,
                 quantity=self._quantity,
+                conviction=self._rsi_conviction(rsi_value),
                 reason=f"RSI {rsi_value:.2f} below oversold threshold {self._oversold}",
             )
+            return self._apply_filters(signal)
         elif rsi_value > self._overbought:
-            return Signal(
+            signal = Signal(
                 strategy=self.name,
                 symbol=candle.symbol,
                 side=OrderSide.SELL,
                 price=candle.close,
                 quantity=self._quantity,
+                conviction=self._rsi_conviction(rsi_value),
                 reason=f"RSI {rsi_value:.2f} above overbought threshold {self._overbought}",
             )
+            return self._apply_filters(signal)
 
         return None
-- 
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