feat: add market sentiment filters (Fear & Greed, CryptoPanic, CryptoQuant)

- SentimentProvider: fetches Fear & Greed Index (free, no key),
  CryptoPanic news sentiment (free key), CryptoQuant exchange
  netflow (free key)
- SentimentData: aggregated should_buy/should_block logic
  - Fear < 30 = buy opportunity, Greed > 80 = block buying
  - Negative news < -0.5 = block buying
  - Exchange outflow = bullish, inflow = bearish
- Integrated into Asian Session RSI strategy as entry filter
- All providers optional — disabled when API key missing
- 14 sentiment tests + 386 total tests passing

1 files changed, 9 insertions, 3 deletions

diff --git a/services/strategy-engine/strategies/combined_strategy.py b/services/strategy-engine/strategies/combined_strategy.py
index 907d9c5..ba92485 100644
--- a/services/strategy-engine/strategies/combined_strategy.py
+++ b/services/strategy-engine/strategies/combined_strategy.py
@@ -53,7 +53,9 @@ class CombinedStrategy(BaseStrategy):
         self._trade_history[strategy_name].append(is_win)
         # Keep only last N results
         if len(self._trade_history[strategy_name]) > self._history_window:
-            self._trade_history[strategy_name] = self._trade_history[strategy_name][-self._history_window:]
+            self._trade_history[strategy_name] = self._trade_history[strategy_name][
+                -self._history_window :
+            ]
 
     def _get_adaptive_weight(self, strategy_name: str, base_weight: float) -> float:
         """Get weight adjusted by recent performance."""
@@ -90,10 +92,14 @@ class CombinedStrategy(BaseStrategy):
                 effective_weight = self._get_adaptive_weight(strategy.name, weight)
                 if signal.side == OrderSide.BUY:
                     score += effective_weight * signal.conviction
-                    reasons.append(f"{strategy.name}:BUY({effective_weight}*{signal.conviction:.2f})")
+                    reasons.append(
+                        f"{strategy.name}:BUY({effective_weight}*{signal.conviction:.2f})"
+                    )
                 elif signal.side == OrderSide.SELL:
                     score -= effective_weight * signal.conviction
-                    reasons.append(f"{strategy.name}:SELL({effective_weight}*{signal.conviction:.2f})")
+                    reasons.append(
+                        f"{strategy.name}:SELL({effective_weight}*{signal.conviction:.2f})"
+                    )
 
         normalized = score / total_weight  # Range: -1.0 to 1.0