redesign activation gate to expected value + make pipelines cron-configurable

Diagnosing "no qualified signals for 5 days": setups were generated but none
qualified. The gate required BOTH a high min_rr (2.0) AND a high
min_target_probability (60), which became contradictory after the Jun-15
probability recalibration — probability already embeds R:R via the 1/(rr+1) ruin
term, so high-R:R targets are inherently low-probability and nothing cleared both.

Gate is now expected value (R): p*rr - (1-p) from the primary target's
probability. R:R and confidence stay as floors; high-conviction / exclude-conflicts
/ min-target-probability become optional tighteners (default off). Defaults:
min_expected_value=0.15, min_rr=1.2, min_confidence=55. EV is only enforced when
computable. Migration 009 clears stored activation_* rows so the new defaults
apply. Backtest sweeps min_expected_value instead of target probability.

Scheduling: pipelines are now cron-configurable in Admin -> Jobs. daily_pipeline
(full, default 0 7 * * *) plus a new light intraday_pipeline (OHLCV + outcome eval,
default hourly US session) that keeps prices/live-R:R current without setup churn.
Fundamentals on its own early weekly cron. Timezone configurable (default
Europe/Berlin). Moving interval->CronTrigger also fixes the restart-deferral bug
where an interval job's countdown resets on every process restart.

319 backend unit tests pass; frontend tsc clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tests/unit/test_qualification.py

@@ -1,12 +1,30 @@
-"""Unit tests for the activation qualification predicate."""
+"""Unit tests for the activation qualification predicate (EV-based gate)."""
 
 from __future__ import annotations
 
 from types import SimpleNamespace
 
-from app.services.qualification import best_target_probability, setup_qualifies
+from app.services.qualification import (
+    best_target_probability,
+    expected_value_r,
+    primary_target_probability,
+    setup_qualifies,
+)
 
-FULL_GATE = {
+# Default gate: expected value is the core test; conviction/conflict/target-prob
+# are optional tighteners, off here.
+DEFAULT_GATE = {
+    "min_expected_value": 0.15,
+    "min_rr": 1.2,
+    "min_confidence": 55.0,
+    "min_target_probability": 0.0,
+    "require_high_conviction": False,
+    "exclude_conflicts": False,
+}
+
+# Strict gate: every optional tightener turned on (the old shipped defaults).
+STRICT_GATE = {
+    "min_expected_value": 0.0,
     "min_rr": 2.0,
     "min_confidence": 70.0,
     "min_target_probability": 60.0,
@@ -21,73 +39,101 @@ def _setup(**kwargs):
         confidence_score=80.0,
         recommended_action="LONG_HIGH",
         risk_level="Low",
-        targets=[{"probability": 65.0}],
+        targets=[{"probability": 50.0, "is_primary": True}],
     )
     base.update(kwargs)
     return SimpleNamespace(**base)
 
 
-class TestSetupQualifies:
-    def test_clean_high_conviction_setup_passes(self):
-        assert setup_qualifies(_setup(), FULL_GATE) is True
+class TestExpectedValue:
+    def test_uses_primary_target_not_best(self):
+        s = _setup(
+            rr_ratio=1.5,
+            targets=[
+                {"probability": 80.0},
+                {"probability": 30.0, "is_primary": True},
+            ],
+        )
+        # EV from the primary (30%): 0.3*1.5 - 0.7 = -0.25
+        assert expected_value_r(s) == -0.25
+        assert primary_target_probability(s) == 30.0
 
-    def test_low_rr_fails(self):
-        assert setup_qualifies(_setup(rr_ratio=1.5), FULL_GATE) is False
+    def test_falls_back_to_best_when_no_primary_flag(self):
+        s = _setup(rr_ratio=2.0, targets=[{"probability": 40.0}, {"probability": 60.0}])
+        assert primary_target_probability(s) == 60.0
+        # 0.6*2.0 - 0.4 = 0.8
+        assert abs(expected_value_r(s) - 0.8) < 1e-9
+
+    def test_none_when_no_targets(self):
+        assert expected_value_r(_setup(targets=[])) is None
+        assert primary_target_probability(_setup(targets=[])) is None
+
+
+class TestSetupQualifies:
+    def test_positive_ev_setup_passes(self):
+        # primary 50% @ rr 3.0 → EV = 1.0
+        assert setup_qualifies(_setup(), DEFAULT_GATE) is True
+
+    def test_negative_ev_fails(self):
+        # primary 30% @ rr 1.3 → EV = -0.31, below the 0.15 floor
+        s = _setup(rr_ratio=1.3, targets=[{"probability": 30.0, "is_primary": True}])
+        assert setup_qualifies(s, DEFAULT_GATE) is False
+
+    def test_thin_positive_ev_below_floor_fails(self):
+        # Positive but thin: 0.45*1.3 - 0.55 = 0.035, under the 0.15 floor.
+        s = _setup(rr_ratio=1.3, targets=[{"probability": 45.0, "is_primary": True}])
+        assert setup_qualifies(s, DEFAULT_GATE) is False
+
+    def test_low_rr_floor_fails(self):
+        assert setup_qualifies(_setup(rr_ratio=1.0), DEFAULT_GATE) is False
 
     def test_low_confidence_fails(self):
-        assert setup_qualifies(_setup(confidence_score=60.0), FULL_GATE) is False
+        assert setup_qualifies(_setup(confidence_score=40.0), DEFAULT_GATE) is False
 
-    def test_moderate_action_fails_when_high_conviction_required(self):
-        assert setup_qualifies(_setup(recommended_action="LONG_MODERATE"), FULL_GATE) is False
+    def test_no_targets_defers_to_rr_and_confidence(self):
+        # No probability → EV uncomputable → not blocked on EV; passes on floors.
+        assert setup_qualifies(_setup(targets=[]), DEFAULT_GATE) is True
+        # ...but still subject to the rr/confidence floors.
+        assert setup_qualifies(_setup(targets=[], rr_ratio=1.0), DEFAULT_GATE) is False
 
-    def test_neutral_action_fails(self):
-        assert setup_qualifies(_setup(recommended_action="NEUTRAL"), FULL_GATE) is False
-
-    def test_short_high_passes(self):
-        assert setup_qualifies(_setup(recommended_action="SHORT_HIGH"), FULL_GATE) is True
-
-    def test_non_low_risk_fails_when_excluding_conflicts(self):
-        assert setup_qualifies(_setup(risk_level="Medium"), FULL_GATE) is False
-        assert setup_qualifies(_setup(risk_level="High"), FULL_GATE) is False
-
-    def test_low_target_probability_fails(self):
-        assert setup_qualifies(_setup(targets=[{"probability": 40.0}]), FULL_GATE) is False
-
-    def test_no_targets_fails_when_probability_required(self):
-        assert setup_qualifies(_setup(targets=[]), FULL_GATE) is False
+    def test_conviction_and_conflict_ignored_by_default(self):
+        # Moderate action + medium risk still pass when tighteners are off.
+        s = _setup(recommended_action="LONG_MODERATE", risk_level="Medium")
+        assert setup_qualifies(s, DEFAULT_GATE) is True
 
     def test_over_progressed_setup_fails_on_live_rr(self):
-        # long target 120, stop 95; price already at 117 → live R:R ≈ 0.14
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=117.0)
-        assert setup_qualifies(s, FULL_GATE) is False
+        assert setup_qualifies(s, DEFAULT_GATE) is False
 
     def test_fresh_setup_passes_live_rr(self):
-        # price near entry (100): live R:R ≈ 3.2, well above min
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=101.0)
-        assert setup_qualifies(s, FULL_GATE) is True
+        assert setup_qualifies(s, DEFAULT_GATE) is True
 
     def test_past_stop_fails_live_rr(self):
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=94.0)
-        assert setup_qualifies(s, FULL_GATE) is False
+        assert setup_qualifies(s, DEFAULT_GATE) is False
 
-    def test_no_current_price_skips_live_check(self):
-        # Historical setups have no current_price → live check skipped
-        assert setup_qualifies(_setup(), FULL_GATE) is True
+    def test_missing_min_ev_key_skips_ev(self):
+        # Legacy callers without min_expected_value: EV defaults to -inf (no floor).
+        legacy = {k: v for k, v in DEFAULT_GATE.items() if k != "min_expected_value"}
+        s = _setup(rr_ratio=1.3, targets=[{"probability": 30.0, "is_primary": True}])
+        assert setup_qualifies(s, legacy) is True
 
-    def test_conviction_filters_can_be_disabled(self):
-        relaxed = {
-            "min_rr": 2.0,
-            "min_confidence": 70.0,
-            "min_target_probability": 0.0,
-            "require_high_conviction": False,
-            "exclude_conflicts": False,
-        }
-        # Moderate action, medium risk, no targets — still passes on rr+confidence alone
-        s = _setup(recommended_action="LONG_MODERATE", risk_level="Medium", targets=[])
-        assert setup_qualifies(s, relaxed) is True
 
-    def test_missing_confidence_treated_as_zero(self):
-        assert setup_qualifies(_setup(confidence_score=None), FULL_GATE) is False
+class TestStrictTighteners:
+    def test_clean_high_conviction_passes(self):
+        assert setup_qualifies(_setup(targets=[{"probability": 65.0, "is_primary": True}]), STRICT_GATE) is True
+
+    def test_moderate_action_fails(self):
+        s = _setup(recommended_action="LONG_MODERATE", targets=[{"probability": 65.0, "is_primary": True}])
+        assert setup_qualifies(s, STRICT_GATE) is False
+
+    def test_non_low_risk_fails(self):
+        s = _setup(risk_level="Medium", targets=[{"probability": 65.0, "is_primary": True}])
+        assert setup_qualifies(s, STRICT_GATE) is False
+
+    def test_low_target_probability_fails(self):
+        assert setup_qualifies(_setup(targets=[{"probability": 40.0, "is_primary": True}]), STRICT_GATE) is False
 
 
 class TestBestTargetProbability: