feat: use playbook allocation_pct in position sizing (#172)
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- Add playbook_allocation_pct and scenario_confidence parameters to
  _determine_order_quantity() with playbook-based sizing taking priority
  over volatility-score fallback when provided
- Confidence scaling: confidence/80 multiplier (confidence 96 → 1.2x)
  clipped to [POSITION_MIN_ALLOCATION_PCT, POSITION_MAX_ALLOCATION_PCT]
- Pass matched_scenario.allocation_pct and match.confidence from
  trading_cycle so AI's allocation decisions reach order execution
- Add 4 new tests: playbook priority, confidence scaling, max clamp,
  and fallback behavior

Closes #172

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
agentson
2026-02-20 08:29:09 +09:00
parent 03f8d220a4
commit c7640a30d7
2 changed files with 105 additions and 1 deletions

View File

@@ -205,6 +205,84 @@ class TestDetermineOrderQuantity:
)
assert result == 2
def test_determine_order_quantity_uses_playbook_allocation_pct(self) -> None:
"""playbook_allocation_pct should take priority over volatility-based sizing."""
settings = MagicMock(spec=Settings)
settings.POSITION_SIZING_ENABLED = True
settings.POSITION_MAX_ALLOCATION_PCT = 30.0
settings.POSITION_MIN_ALLOCATION_PCT = 1.0
# playbook says 20%, confidence 80 → scale=1.0 → 20%
# 1,000,000 * 20% = 200,000 // 50,000 price = 4 shares
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=1000000.0,
candidate=None,
settings=settings,
playbook_allocation_pct=20.0,
scenario_confidence=80,
)
assert result == 4
def test_determine_order_quantity_confidence_scales_allocation(self) -> None:
"""Higher confidence should produce a larger allocation (up to max)."""
settings = MagicMock(spec=Settings)
settings.POSITION_SIZING_ENABLED = True
settings.POSITION_MAX_ALLOCATION_PCT = 30.0
settings.POSITION_MIN_ALLOCATION_PCT = 1.0
# confidence 96 → scale=1.2 → 10% * 1.2 = 12%
# 1,000,000 * 12% = 120,000 // 50,000 price = 2 shares
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=1000000.0,
candidate=None,
settings=settings,
playbook_allocation_pct=10.0,
scenario_confidence=96,
)
# scale = 96/80 = 1.2 → effective_pct = 12.0
# budget = 1_000_000 * 0.12 = 120_000 → qty = 120_000 // 50_000 = 2
assert result == 2
def test_determine_order_quantity_confidence_clamped_to_max(self) -> None:
"""Confidence scaling should not exceed POSITION_MAX_ALLOCATION_PCT."""
settings = MagicMock(spec=Settings)
settings.POSITION_SIZING_ENABLED = True
settings.POSITION_MAX_ALLOCATION_PCT = 15.0
settings.POSITION_MIN_ALLOCATION_PCT = 1.0
# playbook 20% * scale 1.5 = 30% → clamped to 15%
# 1,000,000 * 15% = 150,000 // 50,000 price = 3 shares
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=1000000.0,
candidate=None,
settings=settings,
playbook_allocation_pct=20.0,
scenario_confidence=120, # extreme → scale = 1.5
)
assert result == 3
def test_determine_order_quantity_fallback_when_no_playbook(self) -> None:
"""Without playbook_allocation_pct, falls back to volatility-based sizing."""
settings = MagicMock(spec=Settings)
settings.POSITION_SIZING_ENABLED = True
settings.POSITION_VOLATILITY_TARGET_SCORE = 50.0
settings.POSITION_BASE_ALLOCATION_PCT = 10.0
settings.POSITION_MAX_ALLOCATION_PCT = 30.0
settings.POSITION_MIN_ALLOCATION_PCT = 1.0
# Same as test_buy_with_position_sizing_calculates_correctly (no playbook)
result = _determine_order_quantity(
action="BUY",
current_price=50000.0,
total_cash=1000000.0,
candidate=None,
settings=settings,
playbook_allocation_pct=None, # explicit None → fallback
)
assert result == 2
class TestSafeFloat:
"""Test safe_float() helper function."""