kjh2064
aedabdd37b
suggest/quant_investment_engine_v8_9_portfolio_optimizer_canonical_refactored.yaml의
implementation_todo_v8_9(P0~P4) 전체를 spec/tool/golden case 레벨로 구현.
- P0: PORTFOLIO_TRANSITION_UTILITY_V1, SELL_LOT_PARETO_SELECTOR_V1, FORECAST_SIMULATION_ENGINE_V1
- P1: SECTOR_EXPOSURE_GRAPH_V1/LEADER_LIFECYCLE_GATE_V1, EXECUTION_CAPACITY_LADDER_V1, MODEL_GOVERNANCE_KILL_SWITCH_V1
- P2: SCENARIO_SHOCK_MATRIX_V1, TRANSITION_SET_ENUMERATOR_V1, IMMUTABLE_DECISION_LEDGER_V1, EXECUTION_PLAN_COMPILER_V1
- P3: STATE_VECTOR_CONSTRUCTOR_V1, WALK_FORWARD_BOOTSTRAP_V1, TRANSITION_SET_ENUMERATOR_V1(MRC/CVaR 확장),
REBALANCE_CADENCE_GATE_V1, WEEKLY_LEGACY_TRANSFER_PLAN_V1
기존 regime/cluster 연동 정책 수치(현금방어선, 반도체 cap)는 그대로 유지하고 신규 cap 필드만 추가.
spec/09_decision_flow.yaml과 runtime/active_artifact_manifest.yaml에 전 엔진 배선 완료.
governance/todo/v8_9_p{0,1,2,3}_adoption_plan.yaml에 각 단계 작업 추적 기록.
검증: validate_specs/validate_golden_coverage_100(100%)/validate_calibration_registry_v1/
validate_schema_model_generation_v1/validate_agents_shrink_v1 전부 PASS. golden test 53/53 PASS.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
"""Golden tests for WALK_FORWARD_BOOTSTRAP_V1 (governance/todo/v8_9_p3_adoption_plan.yaml P3-B).
|
|
|
|
Maps to v8.9 proposal golden cases V89_014 (same_regime_sample_low) and
|
|
V89_048 (solver_failure -- here, no historical_returns at all).
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import importlib.util
|
|
import random
|
|
from pathlib import Path
|
|
|
|
ROOT = Path(__file__).resolve().parents[3]
|
|
MODULE_PATH = ROOT / "tools" / "build_walk_forward_bootstrap_v1.py"
|
|
|
|
|
|
def _load_module():
|
|
spec = importlib.util.spec_from_file_location("build_walk_forward_bootstrap_v1", MODULE_PATH)
|
|
module = importlib.util.module_from_spec(spec)
|
|
assert spec.loader is not None
|
|
spec.loader.exec_module(module)
|
|
return module
|
|
|
|
|
|
def _sample_returns(n=30):
|
|
rng = random.Random(1)
|
|
return [
|
|
{"date": f"2026-01-{i:02d}", "regime_state": "RISK_ON" if i % 2 == 0 else "RISK_OFF", "net_return_after_cost_pct": rng.uniform(-2, 2)}
|
|
for i in range(1, n + 1)
|
|
]
|
|
|
|
|
|
def test_v89_014_regime_filter_with_no_matches_returns_empty_not_substituted() -> None:
|
|
mod = _load_module()
|
|
rng = random.Random(1)
|
|
distribution = mod.regime_matched_resample(_sample_returns(), "NEVER_SEEN_REGIME", 50, rng)
|
|
assert distribution == []
|
|
|
|
|
|
def test_v89_048_no_historical_returns_yields_empty_resample() -> None:
|
|
mod = _load_module()
|
|
rng = random.Random(1)
|
|
distribution = mod.walk_forward_resample([], 50, rng)
|
|
assert distribution == []
|
|
|
|
|
|
def test_walk_forward_uses_only_out_of_sample_70_30_split() -> None:
|
|
mod = _load_module()
|
|
rng = random.Random(1)
|
|
returns = _sample_returns(20)
|
|
distribution = mod.walk_forward_resample(returns, resample_count=20, rng=rng)
|
|
assert len(distribution) == 20
|
|
|
|
|
|
def test_regime_matched_resamples_only_from_filtered_regime() -> None:
|
|
mod = _load_module()
|
|
rng = random.Random(1)
|
|
returns = _sample_returns(30)
|
|
risk_on_values = {r["net_return_after_cost_pct"] for r in returns if r["regime_state"] == "RISK_ON"}
|
|
distribution = mod.regime_matched_resample(returns, "RISK_ON", 50, rng)
|
|
assert all(v in risk_on_values for v in distribution)
|