🧪 Fix VIX trend logic and add extensive tests for macro regime short history edge cases

- Fixed `_signal_vix_trend` to correctly return neutral for insufficient history (`< 21`).
- Added `test_short_history_is_neutral` to `TestSignalVixTrend`.
- Extended coverage for short history and edge cases in `TestSignalCreditSpread`, `TestSignalYieldCurve`, `TestSignalMarketBreadth`, and `TestSignalSectorRotation`.

Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>

tests/unit/test_macro_regime.py

@@ -86,6 +86,12 @@ class TestSignalVixTrend:
         score, desc = self.fn(vix)
         assert score == 0
 
+    def test_short_history_is_neutral(self):
+        vix = _make_series([20.0] * 20)
+        score, desc = self.fn(vix)
+        assert score == 0
+        assert "insufficient history" in desc
+
     def test_none_series_is_neutral(self):
         score, desc = self.fn(None)
         assert score == 0
@@ -110,6 +116,42 @@ class TestSignalCreditSpread:
         score, desc = self.fn(hyg, lqd)
         assert score == -1
 
+    def test_short_history_is_neutral(self):
+        hyg = _trending_series(80, 85, 21)
+        lqd = _flat_series(100, 21)
+        score, desc = self.fn(hyg, lqd)
+        assert score == 0
+        assert "insufficient history" in desc
+
+    def test_none_data_is_neutral(self):
+        score, _ = self.fn(None, None)
+        assert score == 0
+
+
+class TestSignalYieldCurve:
+    def setup_method(self):
+        from tradingagents.dataflows.macro_regime import _signal_yield_curve
+        self.fn = _signal_yield_curve
+
+    def test_flight_to_safety_is_risk_off(self):
+        tlt = _trending_series(100, 110, 30)
+        shy = _flat_series(100, 30)
+        score, desc = self.fn(tlt, shy)
+        assert score == -1
+
+    def test_risk_appetite_is_risk_on(self):
+        tlt = _trending_series(110, 100, 30)
+        shy = _flat_series(100, 30)
+        score, desc = self.fn(tlt, shy)
+        assert score == 1
+
+    def test_short_history_is_neutral(self):
+        tlt = _trending_series(100, 110, 21)
+        shy = _flat_series(100, 21)
+        score, desc = self.fn(tlt, shy)
+        assert score == 0
+        assert "insufficient history" in desc
+
     def test_none_data_is_neutral(self):
         score, _ = self.fn(None, None)
         assert score == 0
@@ -140,6 +182,45 @@ class TestSignalMarketBreadth:
         score, _ = self.fn(spx)
         assert score == 0  # < 200 points for SMA200
 
+    def test_short_history_is_neutral(self):
+        spx = _make_series([5000.0] * 199)
+        score, desc = self.fn(spx)
+        assert score == 0
+        assert "insufficient history" in desc
+
+    def test_none_data_is_neutral(self):
+        score, _ = self.fn(None)
+        assert score == 0
+
+
+class TestSignalSectorRotation:
+    def setup_method(self):
+        from tradingagents.dataflows.macro_regime import _signal_sector_rotation
+        self.fn = _signal_sector_rotation
+
+    def test_defensives_leading_is_risk_off(self):
+        defensives = {"XLU": _trending_series(100, 110, 30)}
+        cyclicals = {"XLY": _flat_series(100, 30)}
+        score, desc = self.fn(defensives, cyclicals)
+        assert score == -1
+
+    def test_cyclicals_leading_is_risk_on(self):
+        defensives = {"XLU": _flat_series(100, 30)}
+        cyclicals = {"XLY": _trending_series(100, 110, 30)}
+        score, desc = self.fn(defensives, cyclicals)
+        assert score == 1
+
+    def test_short_history_is_neutral(self):
+        defensives = {"XLU": _trending_series(100, 110, 21)}
+        cyclicals = {"XLY": _flat_series(100, 21)}
+        score, desc = self.fn(defensives, cyclicals)
+        assert score == 0
+        assert "unavailable" in desc
+
+    def test_empty_dicts_is_neutral(self):
+        score, desc = self.fn({}, {})
+        assert score == 0
+
 
 # ---------------------------------------------------------------------------
 # Classify macro regime

tradingagents/dataflows/macro_regime.py

@@ -92,8 +92,8 @@ def _signal_vix_level(vix_price: Optional[float]) -> tuple[int, str]:
 
 def _signal_vix_trend(vix_series: Optional[pd.Series]) -> tuple[int, str]:
     """VIX 5-day SMA vs 20-day SMA: rising VIX = risk-off."""
-    if vix_series is None:
-        return 0, "VIX trend: unavailable (neutral)"
+    if vix_series is None or len(vix_series) < 21:
+        return 0, "VIX trend: insufficient history (neutral)"
     sma5 = _sma(vix_series, 5)
     sma20 = _sma(vix_series, 20)
     if sma5 is None or sma20 is None: