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, 22 insertions, 18 deletions

diff --git a/services/strategy-engine/strategies/bollinger_strategy.py b/services/strategy-engine/strategies/bollinger_strategy.py
index a195cb8..ebe7967 100644
--- a/services/strategy-engine/strategies/bollinger_strategy.py
+++ b/services/strategy-engine/strategies/bollinger_strategy.py
@@ -102,27 +102,31 @@ class BollingerStrategy(BaseStrategy):
             if price > sma:
                 # Breakout upward
                 conv = min(0.5 + squeeze_duration * 0.1, 1.0)
-                return self._apply_filters(Signal(
-                    strategy=self.name,
-                    symbol=candle.symbol,
-                    side=OrderSide.BUY,
-                    price=candle.close,
-                    quantity=self._quantity,
-                    conviction=conv,
-                    reason=f"Bollinger squeeze breakout UP after {squeeze_duration} bars",
-                ))
+                return self._apply_filters(
+                    Signal(
+                        strategy=self.name,
+                        symbol=candle.symbol,
+                        side=OrderSide.BUY,
+                        price=candle.close,
+                        quantity=self._quantity,
+                        conviction=conv,
+                        reason=f"Bollinger squeeze breakout UP after {squeeze_duration} bars",
+                    )
+                )
             else:
                 # Breakout downward
                 conv = min(0.5 + squeeze_duration * 0.1, 1.0)
-                return self._apply_filters(Signal(
-                    strategy=self.name,
-                    symbol=candle.symbol,
-                    side=OrderSide.SELL,
-                    price=candle.close,
-                    quantity=self._quantity,
-                    conviction=conv,
-                    reason=f"Bollinger squeeze breakout DOWN after {squeeze_duration} bars",
-                ))
+                return self._apply_filters(
+                    Signal(
+                        strategy=self.name,
+                        symbol=candle.symbol,
+                        side=OrderSide.SELL,
+                        price=candle.close,
+                        quantity=self._quantity,
+                        conviction=conv,
+                        reason=f"Bollinger squeeze breakout DOWN after {squeeze_duration} bars",
+                    )
+                )
 
         # Bandwidth filter: skip sideways markets
         if sma != 0 and bandwidth < self._min_bandwidth: