fix: align daily matrix ranking universe
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@@ -37,7 +37,7 @@ POLICY_NAMES = (
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"gate_reset_improved",
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"two_session_confirmation",
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)
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CACHE_VERSION = "daily-reentry-matrix-v1"
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CACHE_VERSION = "daily-reentry-matrix-v2-full-ranking-universe"
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def _sqlite_url(path: Path) -> str:
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@@ -312,12 +312,16 @@ async def _main() -> None:
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cache_path = Path(args.candidate_cache) if args.candidate_cache else None
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qualified_candidates: list[dict] | None = None
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entry_candidate_count = 0
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entry_candidates_by_direction: dict[str, int] = {}
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if cache_path is not None and cache_path.exists():
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with cache_path.open("rb") as handle:
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cached = pickle.load(handle) # noqa: S301 - trusted local cache
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if cached.get("key") == cache_key:
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qualified_candidates = list(cached["qualified_candidates"])
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entry_candidate_count = int(cached["entry_candidate_count"])
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entry_candidates_by_direction = dict(
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cached["entry_candidates_by_direction"]
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)
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if not args.quiet:
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print(f"loaded qualified candidate cache: {cache_path}", flush=True)
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elif not args.quiet:
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@@ -338,6 +342,7 @@ async def _main() -> None:
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benchmark_closes,
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replay_start,
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"daily",
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True,
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): symbol
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for symbol, columns in prices.items()
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}
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@@ -347,6 +352,9 @@ async def _main() -> None:
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print(f"daily replay: {index}/{len(futures)} tickers", flush=True)
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entry_candidate_count = len(candidates)
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entry_candidates_by_direction = dict(
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Counter(row["direction"] for row in candidates)
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)
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bt._assign_momentum_percentiles(candidates)
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bt._assign_residual_momentum_percentiles(candidates)
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bt._assign_low_volatility_percentiles(candidates)
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@@ -368,6 +376,9 @@ async def _main() -> None:
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{
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"key": cache_key,
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"entry_candidate_count": entry_candidate_count,
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"entry_candidates_by_direction": (
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entry_candidates_by_direction
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),
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"qualified_candidates": qualified_candidates,
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},
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handle,
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@@ -489,6 +500,53 @@ async def _main() -> None:
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**row,
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})
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immediate_baseline_parity: dict
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if "immediate" in policies:
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direct_daily_baseline = bt._simulate_portfolio(
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qualified_candidates,
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simulation_prices,
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benchmark_closes,
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exit_policy,
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hold_days,
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ranking_key=ranking_key,
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max_positions=args.base_capacity,
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risk_per_trade=float(entry_config["risk_per_trade"]),
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atr_trail_multiplier=trail_multiplier,
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cost_per_side=args.base_cost_per_side_pct / 100.0,
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start_date=requested_start,
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)
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if direct_daily_baseline is None:
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raise RuntimeError("Direct daily no-lockdown baseline produced no trades")
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immediate_all = next(
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row
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for row in primary
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if row["lookback"] == "all" and row["arm"] == "immediate"
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)
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parity_fields = tuple(sorted(direct_daily_baseline))
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parity_differences = {
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field: {
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"direct_daily_baseline": direct_daily_baseline.get(field),
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"immediate_callback": immediate_all.get(field),
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}
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for field in parity_fields
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if direct_daily_baseline.get(field) != immediate_all.get(field)
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}
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if parity_differences:
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raise RuntimeError(
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"Immediate callback diverges from direct daily baseline: "
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f"{parity_differences}"
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)
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immediate_baseline_parity = {
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"passed": True,
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"compared_fields": list(parity_fields),
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"direct_daily_baseline": direct_daily_baseline,
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}
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else:
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immediate_baseline_parity = {
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"passed": None,
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"skipped": "immediate policy was not selected",
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}
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robustness: list[dict] = []
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for cost_pct in all_costs:
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for capacity in all_capacities:
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@@ -543,10 +601,12 @@ async def _main() -> None:
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"tickers_loaded": len(prices),
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"tickers_qualified": len(qualified_symbols),
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"entry_candidates": entry_candidate_count,
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"entry_candidates_by_direction": entry_candidates_by_direction,
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"qualified_candidates": len(qualified_candidates),
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"params": {
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"entry_cadence": "daily",
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"target_model": "production_gtl",
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"ranking_universe": "all_long_and_short_setups",
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"policies": list(policies),
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"base_cost_per_side_pct": args.base_cost_per_side_pct,
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"base_capacity": args.base_capacity,
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@@ -564,12 +624,17 @@ async def _main() -> None:
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"ranking_key": ranking_key,
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},
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"primary_lookback_matrix": primary,
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"immediate_baseline_parity": immediate_baseline_parity,
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"cost_capacity_robustness": robustness,
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"holdout": holdout,
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"portfolio_simulations_executed": completed_sims,
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"note": (
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"The point-in-time daily setup replay and universe ranking are executed "
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"once. All arms reuse the identical production-qualified candidate set. "
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"once. Long and short setups both contribute to the production-faithful "
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"cross-sectional percentiles; only qualified longs are tradable. All arms "
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"reuse that identical production-qualified candidate set. The immediate "
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"callback, when selected, must match a direct daily no-lockdown "
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"simulation exactly. "
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"Immediate is the daily no-lockdown baseline; next_session blocks only "
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"the stop day; cooldown_5 permits re-entry at wait_sessions=5; gate_reset "
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"requires an unqualified close before requalification; "
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