research: prepare effective risk floor ab

This commit is contained in:
2026-08-05 22:49:50 +02:00
parent aa6cd5cac4
commit 6f1ee450f1
5 changed files with 573 additions and 51 deletions
@@ -10,6 +10,7 @@ import pytest
from app.services import backtest_service as bt
from scripts.portfolio_capacity_research import (
ANCHOR_YEARS,
RISK_FLOOR_ARMS,
aggregate_results,
bootstrap_median_interval,
build_cells,
@@ -20,6 +21,7 @@ from scripts.portfolio_capacity_research import (
)
from scripts.run_portfolio_construction_matrix import (
CACHE_VERSION,
STUDIES,
_assert_clean_worktree,
_build_candidate_cache,
_checkpoint_state,
@@ -29,6 +31,7 @@ from scripts.run_portfolio_construction_matrix import (
_load_snapshot,
_markdown,
_operational_summary,
_risk_floor_markdown,
_worker_init,
_worker_run_cell,
_write_cell_checkpoint,
@@ -538,6 +541,29 @@ def test_cohort_manifest_realizes_seven_frozen_clusters():
assert len(cells) == (
len(manifest['empty_book']) + len(manifest['warm_book'])
) * 4 * 2
floor_cells = build_cells(manifest, arms=RISK_FLOOR_ARMS)
assert len(floor_cells) == (
len(manifest['empty_book']) + len(manifest['warm_book'])
) * 2 * 2
assert {row['arm_id'] for row in floor_cells} == {
'cap10_incumbent',
'cap10_min_risk_005',
}
def test_risk_floor_study_changes_only_the_effective_risk_floor():
control, treatment = RISK_FLOOR_ARMS
assert control['max_positions'] == treatment['max_positions'] == 10
assert (
control['weekly_top_n_rebalance']
== treatment['weekly_top_n_rebalance']
is False
)
assert control['min_initial_risk_fraction'] is None
assert treatment['min_initial_risk_fraction'] == 0.005
assert STUDIES['risk-floor-ab']['arms'] == RISK_FLOOR_ARMS
assert STUDIES['capacity-bracket']['arms'] != RISK_FLOOR_ARMS
def test_zero_outcome_horizon_extends_rank_replay_to_last_session(monkeypatch):
@@ -700,6 +726,18 @@ def test_aggregate_reports_paired_years_and_separate_warm_iqrs():
assert cash_empty['headline']['ev_net_r']['paired_delta_median'] == pytest.approx(
0.2
)
cash_paths = next(
row
for row in report['paired_path_distributions']
if row['arm_id'] == 'cash_unbounded'
and row['protocol'] == 'empty_book'
and row['cost_per_side_pct'] == 0.1
)
assert cash_paths['metrics']['ev_net_r']['paired_delta_mean'] == pytest.approx(
0.2
)
assert cash_paths['metrics']['ev_net_r']['positive_fraction'] == 1.0
assert cash_paths['metrics']['ev_net_r']['identical_fraction'] == 0.0
cash_warm = next(
row
for row in report['warm_seed_dispersion']
@@ -738,6 +776,43 @@ def test_aggregate_reports_paired_years_and_separate_warm_iqrs():
assert 'Rank-only qualified rows removed: 137000.' in markdown
assert 'formal promotion gate' in markdown
focused_cells = [
row
for row in cells
if row['arm_id'] == 'cap10_incumbent'
] + [
{
**row,
'arm_id': 'cap10_min_risk_005',
}
for row in cells
if row['arm_id'] == 'cash_unbounded'
]
focused_analysis = aggregate_results(
focused_cells,
arms=RISK_FLOOR_ARMS,
include_warm_dispersion=False,
)
assert focused_analysis['warm_seed_dispersion'] == []
focused_markdown = _risk_floor_markdown({
'generated_at': '2026-08-05T00:00:00Z',
'arms': list(RISK_FLOOR_ARMS),
'protocols': ['empty_book', 'warm_book'],
'costs_per_side_pct': [0.1, 0.2],
'analysis': focused_analysis,
'operational_summary': _operational_summary(
focused_cells,
arms=RISK_FLOOR_ARMS,
),
})
assert '# Effective initial-risk floor A/B' in focused_markdown
assert 'Mean dEV' in focused_markdown
assert 'Identical' in focused_markdown
assert 'Mean dGtP' in focused_markdown
assert 'Mean dCalmar/MAR' in focused_markdown
assert 'Floor rejects' in focused_markdown
assert 'not independent evidence' in focused_markdown
def test_synthetic_worker_matrix_covers_four_arms_protocols_and_costs(monkeypatch):
monkeypatch.setenv('BACKTEST_SNAPSHOT_OFFLINE', '0')