1 files changed, 58 insertions, 0 deletions
diff --git a/services/strategy-engine/tests/test_macd_strategy.py b/services/strategy-engine/tests/test_macd_strategy.py
index 9931b43..cd24ee0 100644
--- a/services/strategy-engine/tests/test_macd_strategy.py
+++ b/services/strategy-engine/tests/test_macd_strategy.py
@@ -78,3 +78,61 @@ def test_macd_reset_clears_state():
     s.reset()
     assert len(s._closes) == 0
     assert s._prev_histogram is None
+    assert s._prev_macd is None
+    assert s._prev_signal is None
+
+
+def test_macd_signal_line_crossover():
+    """Test that MACD signal-line crossover generates signals."""
+    s = _make_strategy()
+    # Declining then rising prices should produce a signal-line bullish crossover
+    prices = [100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88]
+    prices += [89, 91, 94, 98, 103, 109, 116, 124, 133, 143]
+    signals = []
+    for p in prices:
+        result = s.on_candle(_candle(float(p)))
+        if result is not None:
+            signals.append(result)
+
+    buy_signals = [sig for sig in signals if sig.side == OrderSide.BUY]
+    assert len(buy_signals) > 0, "Expected at least one BUY signal"
+    # Check that at least one is a signal-line crossover or histogram crossover
+    all_reasons = [sig.reason for sig in buy_signals]
+    assert any("crossover" in r for r in all_reasons), f"Expected crossover signal, got: {all_reasons}"
+
+
+def test_macd_conviction_varies_with_distance():
+    """Test that conviction varies based on MACD distance from zero line."""
+    s1 = _make_strategy()
+    s2 = _make_strategy()
+
+    # Small price movements -> MACD near zero -> lower conviction
+    small_prices = [100, 99.5, 99, 98.5, 98, 97.5, 97, 96.5, 96, 95.5, 95, 94.5, 94]
+    small_prices += [94.5, 95, 95.5, 96, 96.5, 97, 97.5, 98, 98.5, 99]
+    small_signals = []
+    for p in small_prices:
+        result = s1.on_candle(_candle(float(p)))
+        if result is not None:
+            small_signals.append(result)
+
+    # Large price movements -> MACD far from zero -> higher conviction
+    large_prices = [100, 95, 90, 85, 80, 75, 70, 65, 60, 55, 50, 45, 40]
+    large_prices += [45, 55, 70, 90, 115, 145, 180, 220, 265, 315]
+    large_signals = []
+    for p in large_prices:
+        result = s2.on_candle(_candle(float(p)))
+        if result is not None:
+            large_signals.append(result)
+
+    # Both should produce signals
+    assert len(small_signals) > 0, "Expected signals from small movements"
+    assert len(large_signals) > 0, "Expected signals from large movements"
+
+    # The large-movement signals should generally have higher conviction
+    # (or at least different conviction, since distance from zero affects it)
+    small_conv = small_signals[-1].conviction
+    large_conv = large_signals[-1].conviction
+    # Large movements should produce conviction >= small movements
+    assert large_conv >= small_conv, (
+        f"Expected large movement conviction ({large_conv}) >= small ({small_conv})"
+    )