major update

app/services/rr_scanner_service.py

@@ -34,10 +34,32 @@ async def _get_ticker(db: AsyncSession, symbol: str) -> Ticker:
     return ticker
 
 
+def _compute_quality_score(
+    rr: float,
+    strength: int,
+    distance: float,
+    entry_price: float,
+    *,
+    w_rr: float = 0.35,
+    w_strength: float = 0.35,
+    w_proximity: float = 0.30,
+    rr_cap: float = 10.0,
+) -> float:
+    """Compute a quality score for a candidate S/R level.
+
+    Combines normalized R:R ratio, level strength, and proximity to entry
+    into a single 0–1 score using configurable weights.
+    """
+    norm_rr = min(rr / rr_cap, 1.0)
+    norm_strength = strength / 100.0
+    norm_proximity = 1.0 - min(distance / entry_price, 1.0)
+    return w_rr * norm_rr + w_strength * norm_strength + w_proximity * norm_proximity
+
+
 async def scan_ticker(
     db: AsyncSession,
     symbol: str,
-    rr_threshold: float = 3.0,
+    rr_threshold: float = 1.5,
     atr_multiplier: float = 1.5,
 ) -> list[TradeSetup]:
     """Scan a single ticker for trade setups meeting the R:R threshold.
@@ -120,41 +142,65 @@ async def scan_ticker(
     setups: list[TradeSetup] = []
 
     # Long setup: target = nearest SR above, stop = entry - ATR × multiplier
+    # Check all resistance levels above and pick the one with the best quality score
     if levels_above:
-        target = levels_above[0].price_level
         stop = entry_price - (atr_value * atr_multiplier)
-        reward = target - entry_price
         risk = entry_price - stop
-        if risk > 0 and reward > 0:
-            rr = reward / risk
-            if rr >= rr_threshold:
+        if risk > 0:
+            best_quality = 0.0
+            best_candidate_rr = 0.0
+            best_candidate_target = 0.0
+            for lv in levels_above:
+                reward = lv.price_level - entry_price
+                if reward > 0:
+                    rr = reward / risk
+                    if rr >= rr_threshold:
+                        distance = lv.price_level - entry_price
+                        quality = _compute_quality_score(rr, lv.strength, distance, entry_price)
+                        if quality > best_quality:
+                            best_quality = quality
+                            best_candidate_rr = rr
+                            best_candidate_target = lv.price_level
+            if best_candidate_rr > 0:
                 setups.append(TradeSetup(
                     ticker_id=ticker.id,
                     direction="long",
                     entry_price=round(entry_price, 4),
                     stop_loss=round(stop, 4),
-                    target=round(target, 4),
-                    rr_ratio=round(rr, 4),
+                    target=round(best_candidate_target, 4),
+                    rr_ratio=round(best_candidate_rr, 4),
                     composite_score=round(composite_score, 4),
                     detected_at=now,
                 ))
 
     # Short setup: target = nearest SR below, stop = entry + ATR × multiplier
+    # Check all support levels below and pick the one with the best quality score
     if levels_below:
-        target = levels_below[0].price_level
         stop = entry_price + (atr_value * atr_multiplier)
-        reward = entry_price - target
         risk = stop - entry_price
-        if risk > 0 and reward > 0:
-            rr = reward / risk
-            if rr >= rr_threshold:
+        if risk > 0:
+            best_quality = 0.0
+            best_candidate_rr = 0.0
+            best_candidate_target = 0.0
+            for lv in levels_below:
+                reward = entry_price - lv.price_level
+                if reward > 0:
+                    rr = reward / risk
+                    if rr >= rr_threshold:
+                        distance = entry_price - lv.price_level
+                        quality = _compute_quality_score(rr, lv.strength, distance, entry_price)
+                        if quality > best_quality:
+                            best_quality = quality
+                            best_candidate_rr = rr
+                            best_candidate_target = lv.price_level
+            if best_candidate_rr > 0:
                 setups.append(TradeSetup(
                     ticker_id=ticker.id,
                     direction="short",
                     entry_price=round(entry_price, 4),
                     stop_loss=round(stop, 4),
-                    target=round(target, 4),
-                    rr_ratio=round(rr, 4),
+                    target=round(best_candidate_target, 4),
+                    rr_ratio=round(best_candidate_rr, 4),
                     composite_score=round(composite_score, 4),
                     detected_at=now,
                 ))
@@ -177,7 +223,7 @@ async def scan_ticker(
 
 async def scan_all_tickers(
     db: AsyncSession,
-    rr_threshold: float = 3.0,
+    rr_threshold: float = 1.5,
     atr_multiplier: float = 1.5,
 ) -> list[TradeSetup]:
     """Scan all tracked tickers for trade setups.