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signal-platform/tests/unit/test_qualification.py
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dennisthiessen c34f3cb1a4
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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>
2026-06-23 14:46:38 +02:00

146 lines
5.5 KiB
Python

"""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,
expected_value_r,
primary_target_probability,
setup_qualifies,
)
# 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,
"require_high_conviction": True,
"exclude_conflicts": True,
}
def _setup(**kwargs):
base = dict(
rr_ratio=3.0,
confidence_score=80.0,
recommended_action="LONG_HIGH",
risk_level="Low",
targets=[{"probability": 50.0, "is_primary": True}],
)
base.update(kwargs)
return SimpleNamespace(**base)
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_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=40.0), DEFAULT_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_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):
s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=117.0)
assert setup_qualifies(s, DEFAULT_GATE) is False
def test_fresh_setup_passes_live_rr(self):
s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=101.0)
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, DEFAULT_GATE) is False
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
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:
def test_returns_max(self):
s = _setup(targets=[{"probability": 40.0}, {"probability": 72.0}, {"probability": 55.0}])
assert best_target_probability(s) == 72.0
def test_empty_is_zero(self):
assert best_target_probability(_setup(targets=[])) == 0.0