Clean up superseded configs and commit accumulated R&D infrastructure

Key changes:
- Delete superseded strategy configs: orb_gainers safe_v2-v9, orb_pullback, vwap_reclaim, hypergap, leader_safe
- Add V46 prior_event_types param to domain.py + run.py event type wiring
- Major simulator.py enhancements: sector thrust sleeve, sector proxy mapping, helper functions
- Improve screener.py with better scoring/filtering
- Add new test coverage: test_simulator.py (776 lines) + test_screener.py (313 lines)
- Add V24.1 research candidate configs (w002/w003/w004/entrycap/losscap010 variants)
- Add leader momentum research configs and sweep files
- Update configs/snapshots/registry.json with new strategy registrations
- Add docs/leader_intraday_momentum_workflow.md

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

apps/intraday_bt/momentum_research.py

@@ -585,12 +585,15 @@ async def build_momentum_research_context(
     if print_progress:
         print(f"\n  Intraday loaded: {len(all_intraday)} days")
 
+    ticker_sectors = await _load_ticker_sectors_with_oracle(tickers, client)
+
     if _momentum_uses_historical_intraday_first(config.strategy):
         candidates = momentum_intraday_first_candidates(
             all_intraday,
             trading_days,
             config.strategy,
             daily_enrichment=daily_enrichment,
+            ticker_sectors=ticker_sectors,
             max_per_day=config.strategy.candidate_final_max_per_day,
         )
     else:
@@ -609,7 +612,7 @@ async def build_momentum_research_context(
     context = MomentumResearchContext(
         config=config,
         tickers=tickers,
-        ticker_sectors=await _load_ticker_sectors_with_oracle(tickers, client),
+        ticker_sectors=ticker_sectors,
         trading_days=trading_days,
         daily_bars=daily_bars,
         all_intraday=all_intraday,
@@ -680,6 +683,7 @@ def simulate_momentum_params(
             trading_days,
             strategy,
             daily_enrichment=context.daily_enrichment,
+            ticker_sectors=context.ticker_sectors,
             max_per_day=strategy.candidate_final_max_per_day,
         )
     else:

apps/intraday_bt/run.py

@@ -1669,9 +1669,11 @@ async def run(config: IntradayConfig, refresh_cache: bool = False) -> tuple:
                 _prior_lookback = int(getattr(orb_params, "prior_event_lookback_days", 0) or 0)
                 if _prior_lookback > 0:
                     all_tickers = list({t for day_tickers in candidates.values() for t in day_tickers})
-                    print(f"      Prefetching prior-event features from DB (D-{_prior_lookback}) for {len(all_tickers)} tickers...")
+                    _prior_event_types = tuple(getattr(orb_params, "prior_event_types", None) or ["earnings_release", "guidance_update"])
+                    print(f"      Prefetching prior-event features from DB (D-{_prior_lookback}, types={_prior_event_types}) for {len(all_tickers)} tickers...")
                     event_features = await _prefetch_prior_event_features_db(
-                        all_tickers, trading_days, lookback_calendar_days=_prior_lookback
+                        all_tickers, trading_days, lookback_calendar_days=_prior_lookback,
+                        event_types=_prior_event_types,
                     )
                     print(f"      Prior-event coverage: {len(event_features)} tickers with events")
                 else:
@@ -2168,9 +2170,11 @@ async def run_with_sweep(config: IntradayConfig, sweep_path: str) -> None:
                 _prior_lookback_sw = int(getattr(orb_params, "prior_event_lookback_days", 0) or 0)
                 if _prior_lookback_sw > 0:
                     all_tickers_sw = list({t for day_tickers in candidates.values() for t in day_tickers})
-                    print(f"      Prefetching prior-event features from DB (D-{_prior_lookback_sw}) for {len(all_tickers_sw)} tickers...")
+                    _prior_event_types_sw = tuple(getattr(orb_params, "prior_event_types", None) or ["earnings_release", "guidance_update"])
+                    print(f"      Prefetching prior-event features from DB (D-{_prior_lookback_sw}, types={_prior_event_types_sw}) for {len(all_tickers_sw)} tickers...")
                     event_features = await _prefetch_prior_event_features_db(
-                        all_tickers_sw, trading_days, lookback_calendar_days=_prior_lookback_sw
+                        all_tickers_sw, trading_days, lookback_calendar_days=_prior_lookback_sw,
+                        event_types=_prior_event_types_sw,
                     )
                     print(f"      Prior-event coverage: {len(event_features)} tickers with events")
                 else:

apps/intraday_bt/sweep.py

@@ -95,6 +95,7 @@ def run_sweep(
     momentum_enrichment: dict | None = None,
     vix_by_day: dict[str, float] | None = None,
     ticker_sectors: dict[str, str] | None = None,
+    sector_proxy_intraday_by_day: dict[str, dict[str, list[dict]]] | None = None,
 ) -> list[SweepResult]:
     """Run simulation for each parameter combination.
 
@@ -132,6 +133,7 @@ def run_sweep(
                 daily_enrichment=momentum_enrichment,
                 vix_by_day=vix_by_day,
                 ticker_sectors=ticker_sectors,
+                sector_proxy_intraday_by_day=sector_proxy_intraday_by_day,
             )
 
         metrics = compute_metrics(day_results, config, run_id=f"sw{i:04d}")

apps/paper_trader/backtest_sim.py

@@ -524,6 +524,8 @@ def run_backtest(
                 universe_profile = "midwide-liquid-long-v1"
             elif "smallcap" in snapshot_id:
                 universe_profile = "smallcap-liquid-long-v1"
+            elif "broad" in snapshot_id:
+                universe_profile = "broad-liquid-long-v1"
 
             if console:
                 console.print(f"\n[bold yellow]Snapshot '{snapshot_id}' is stale — refreshing...[/]")

apps/pipeline/filing_poller/main.py

@@ -5,7 +5,9 @@ import argparse
 import asyncio
 import datetime as dt
 import uuid
+from pathlib import Path
 
+import yaml
 from sqlalchemy import select
 
 from libs.common.config import get_settings
@@ -19,13 +21,27 @@ from libs.oracle_client import FilingsService, make_oracle_client
 logger = get_logger(__name__)
 
 
+def _load_symbols_from_yaml(path: str) -> list[str]:
+    """Load ticker list from a symbols YAML (supports list or dict with 'symbols' key)."""
+    raw = yaml.safe_load(Path(path).read_text())
+    if isinstance(raw, list):
+        items = raw
+    elif isinstance(raw, dict):
+        items = raw.get("symbols", [])
+    else:
+        items = []
+    return sorted({str(s).upper() for s in items if s})
+
+
 async def poll_filings(
     run_id: str,
     start_date: str | None = None,
     end_date: str | None = None,
+    symbols: list[str] | None = None,
 ) -> dict[str, int]:
     settings = get_settings()
-    symbols = settings.get_symbols()
+    if symbols is None:
+        symbols = settings.get_symbols()
     app_config = settings.get_app_config()
     form_types = ",".join(app_config.get("pipeline", {}).get("form_types", ["8-K", "6-K"]))
 
@@ -58,66 +74,85 @@ async def poll_filings(
             ticker_to_symbol = {s.ticker: s.symbol_id for s in symbol_result.scalars().all()}
 
             for ticker in symbols:
-                try:
+                last_exc: Exception | None = None
-                    response = await svc.search_filings(
+                response = None
-                        ticker,
+                for attempt in range(3):
-                        form_type=form_types,
+                    try:
-                        start_date=effective_start,
+                        response = await svc.search_filings(
-                        end_date=end_date,
+                            ticker,
-                    )
+                            form_type=form_types,
-                    stats["seen"] += len(response.filings)
+                            start_date=effective_start,
-
+                            end_date=end_date,
-                    for filing in response.filings:
-                        # Check for duplicate
-                        existing = await session.execute(
-                            select(Document).where(
-                                Document.accession_no == filing.accession_no,
-                                Document.form_type == filing.form_type,
-                            )
-                        )
-                        if existing.scalar_one_or_none() is not None:
-                            stats["skipped"] += 1
-                            continue
-
-                        doc_id = make_document_id(
-                            "sec",
-                            f"TICKER::{ticker}",
-                            filing.filing_date,
-                            filing.accession_no,
                         )
-
+                        last_exc = None
-                        doc = Document(
+                        break
-                            document_id=doc_id,
+                    except Exception as exc:
-                            source_name="sec",
+                        last_exc = exc
-                            issuer_id=ticker_to_issuer.get(ticker),
+                        wait = 2 ** attempt  # 1s, 2s, 4s
-                            symbol_id=ticker_to_symbol.get(ticker),
+                        logger.warning(
-                            accession_no=filing.accession_no,
+                            "poll_retry",
-                            form_type=filing.form_type,
-                            filing_date=dt.date.fromisoformat(filing.filing_date),
-                            accepted_at_utc=(
-                                dt.datetime.fromisoformat(
-                                    filing.accepted_at.replace("Z", "+00:00")
-                                )
-                                if filing.accepted_at
-                                else None
-                            ),
-                            primary_document_name=filing.primary_document,
-                            item_numbers=filing.items if filing.items else None,
-                            parsed_status="pending",
-                        )
-                        session.add(doc)
-                        stats["written"] += 1
-                        logger.info(
-                            "new_filing_discovered",
                             ticker=ticker,
-                            accession_no=filing.accession_no,
+                            attempt=attempt + 1,
-                            form_type=filing.form_type,
+                            wait=wait,
-                            filing_date=filing.filing_date,
+                            error=str(exc) or repr(exc),
+                            exc_type=type(exc).__name__,
                         )
+                        await asyncio.sleep(wait)
 
-                except Exception as exc:
+                if last_exc is not None:
-                    logger.error("poll_error", ticker=ticker, error=str(exc) or repr(exc), exc_type=type(exc).__name__)
+                    logger.error("poll_error", ticker=ticker, error=str(last_exc) or repr(last_exc), exc_type=type(last_exc).__name__)
                     stats["errors"] += 1
+                    continue
+
+                stats["seen"] += len(response.filings)
+
+                for filing in response.filings:
+                    # Check for duplicate
+                    existing = await session.execute(
+                        select(Document).where(
+                            Document.accession_no == filing.accession_no,
+                            Document.form_type == filing.form_type,
+                        )
+                    )
+                    if existing.scalar_one_or_none() is not None:
+                        stats["skipped"] += 1
+                        continue
+
+                    doc_id = make_document_id(
+                        "sec",
+                        f"TICKER::{ticker}",
+                        filing.filing_date,
+                        filing.accession_no,
+                    )
+
+                    doc = Document(
+                        document_id=doc_id,
+                        source_name="sec",
+                        issuer_id=ticker_to_issuer.get(ticker),
+                        symbol_id=ticker_to_symbol.get(ticker),
+                        accession_no=filing.accession_no,
+                        form_type=filing.form_type,
+                        filing_date=dt.date.fromisoformat(filing.filing_date),
+                        accepted_at_utc=(
+                            dt.datetime.fromisoformat(
+                                filing.accepted_at.replace("Z", "+00:00")
+                            )
+                            if filing.accepted_at
+                            else None
+                        ),
+                        primary_document_name=filing.primary_document,
+                        item_numbers=filing.items if filing.items else None,
+                        parsed_status="pending",
+                    )
+                    session.add(doc)
+                    stats["written"] += 1
+                    logger.info(
+                        "new_filing_discovered",
+                        ticker=ticker,
+                        accession_no=filing.accession_no,
+                        form_type=filing.form_type,
+                        filing_date=filing.filing_date,
+                    )
 
             # Update job record
             job.status = "succeeded" if stats["errors"] == 0 else "partial"
@@ -146,13 +181,26 @@ def main() -> None:
         metavar="YYYY-MM-DD",
         help="End date for filing search (default: today)",
     )
+    parser.add_argument(
+        "--symbols-file",
+        default=None,
+        help="Override symbols YAML (default: settings.symbols_file). "
+             "Use for one-off backfills against a wider universe (e.g. broad snapshot).",
+    )
     args = parser.parse_args()
 
     settings = get_settings()
     configure_logging(settings.log_level)
     bind_job_run_id(args.run_id)
 
-    asyncio.run(poll_filings(args.run_id, start_date=args.start_date, end_date=args.end_date))
+    override_symbols = _load_symbols_from_yaml(args.symbols_file) if args.symbols_file else None
+
+    asyncio.run(poll_filings(
+        args.run_id,
+        start_date=args.start_date,
+        end_date=args.end_date,
+        symbols=override_symbols,
+    ))
 
 
 if __name__ == "__main__":

configs/intraday/strategies/hypergap_failure_v1.yaml

@@ -1,119 +0,0 @@
-_meta:
-  id: 38
-  name: "Hypergap Failure V1"
-  status: aborted
-  aborted_date: "2026-04-21"
-  aborted_reason: >
-    3 tests all failed. Test 1 (quality filters + regime gate): -33%, WR ~27%.
-    Test 2 (quality filters, no regime): -59%, WR ~25%.
-    Test 3 (inverted quality - no rvol, no premarket_vol): -59.16%, WR 42.9%, DD -59.16%.
-    Structural R/R problem: avg_win 3.55% < avg_loss 4.10%. Need WR ≥ 54% to break even at
-    this R/R — unachievable. High-quality stocks fail hard but rarely; low-quality stocks fail
-    often but with small moves. Neither profile yields positive expectancy on gap-failure shorts.
-    Root cause: gap-up short positions have inherently adverse asymmetry (stocks rocket up when
-    wrong, drift down slowly when right). No filter combination overcomes this.
-  description: >
-    Phase 3 / diagnostic: extreme-gap stocks (≥6%) that fail to hold the ORB.
-
-    Hypothesis: V23's portfolio-level correlation (~0.40) with any long-momentum engine is
-    regime-driven (both long-momentum, both triggered by QQQ-positive days). The only way to
-    break regime correlation is to be directionally orthogonal.
-
-    Gap failure = stock gaps up ≥6%, but ORB candle is bearish (sold off in first 5 min).
-    Entry: short when price breaks below ORB low. On days when V23's stocks are succeeding
-    (trend), these stocks should not be bearish-ORB (so no trades). On days when market
-    reverses (V23 losing), gap stocks are more likely to fail → shorts enter → anti-correlation.
-
-    Gate: WR ≥ 42% (shorts tolerate lower WR than longs due to asymmetric payout),
-    total_return ≥ 0%, max_dd ≥ -20%.
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: hypergap_failure_v1
-  live_readiness: research_only
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: short_only   # only trade bearish ORB candles (gap failure)
-  order_timeout_minutes: 45
-
-  allow_doji_breakout: false
-  allow_red_to_green_breakout: false
-
-  # === Candidate filters: extreme gap pool (≥6%), same quality bars as V23 ===
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-  min_rvol: null           # inverted: allow low-rvol retail stocks (test #3: invert quality)
-  min_abs_gap_pct: 0.06   # extreme gap: ≥6% (gap failure more likely above this threshold)
-  min_premarket_dollar_vol: null  # inverted: allow low-premarket-vol retail stocks
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: null  # no cap
-
-  min_candidate_breadth: null   # no breadth gate — operate on any breadth day
-  market_regime_spy_threshold: null  # no QQQ regime gate — need to find own signal first
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  rolling_loss_threshold: null  # no rolling loss kill — diagnostic mode
-  max_simultaneous_entries: 3
-  min_breakout_rel_vol: null
-
-  # === Scoring weights (same as V23) ===
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  # === Stop / exit (conservative start for diagnostic) ===
-  atr_stop_multiplier: 1.0      # wider stop for shorts (gap stocks can be volatile)
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  partial_exit_at_r: 99.0
-  partial_exit_pct: 0.50
-
-  risk_per_trade_pct: 0.05
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.05
-  max_stops_per_day: 5
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  drawdown_governor_threshold: 0.025
-  drawdown_governor_min_scale: 0.30
-
-  streak_sizing_win_bonus: 0.70
-  streak_sizing_max: 2.5
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/leader_intraday_momentum_actual_catalyst_liquid.yaml

@@ -0,0 +1,109 @@
+_meta:
+  name: Leader Intraday Momentum Actual Catalyst Liquid
+  description: Separate actual-catalyst liquid-leader continuation engine. Uses only filing-backed catalyst candidates of selected event types, seeds a broad intraday-first shortlist from same-day events, then ranks and trades the liquid leaders showing early continuation.
+  id: 26
+strategy_mode: momentum
+strategy:
+  compound_returns: false
+  entry_minutes_after_open: 10
+  confirmation_minutes_after_entry: 5
+  min_confirmation_return_pct: 0.003
+  exit_minutes_before_close: 10
+  stop_loss_pct: null
+  trailing_stop_pct: -0.08
+  overextended_trailing_gain_pct: 0.05
+  overextended_trailing_stop_pct: -0.07
+  min_gap_pct: 0.0
+  min_morning_gain_pct: 0.008
+  max_morning_gain_pct: 0.06
+  max_gap_pct: 0.12
+  min_volume_ratio_14d: 0.02
+  min_entry_volume: 100000
+  min_entry_dollar_volume: 12000000
+  ticker_cooldown_days: 0
+  top_n: 5
+  max_positions_per_sector: 2
+  use_five_sleeves: true
+  five_sleeve_force_count: 3
+  use_event_sleeve: true
+  event_weight: 0.20
+  event_min_score: 1.0
+  event_sleeve_soft_day_only: false
+  use_liquid_largecap_sleeve: true
+  liquid_largecap_weight: 0.15
+  liquid_largecap_min_gain_pct: 0.004
+  liquid_largecap_max_gain_pct: 0.03
+  liquid_largecap_min_confirmation_return_pct: 0.001
+  liquid_largecap_min_entry_dollar_volume: 50000000
+  liquid_largecap_min_avg_dollar_vol_30d: 1000000000
+  liquid_largecap_max_entropy_20d: 0.85
+  use_moderate_gap_liquid_sleeve: true
+  moderate_gap_liquid_weight: 0.10
+  moderate_gap_liquid_min_gap_pct: 0.003
+  moderate_gap_liquid_max_gap_pct: 0.04
+  moderate_gap_liquid_min_gain_pct: 0.008
+  moderate_gap_liquid_max_gain_pct: 0.04
+  moderate_gap_liquid_min_confirmation_return_pct: 0.002
+  moderate_gap_liquid_min_entry_dollar_volume: 20000000
+  moderate_gap_liquid_min_avg_dollar_vol_30d: 250000000
+  moderate_gap_liquid_max_avg_dollar_vol_30d: 3000000000
+  moderate_gap_liquid_min_volume_ratio_14d: 0.02
+  moderate_gap_liquid_max_entropy_20d: 0.84
+  max_entropy_20d: 0.85
+  entropy_size_scale_low: 0.78
+  entropy_size_scale_high: 0.85
+  entropy_size_scale_min: 0.7
+  sector_concentration_scale_low: 0.4
+  sector_concentration_scale_high: 0.67
+  sector_concentration_scale_min: 0.85
+  max_vix: 35.0
+  initial_capital: 10000.0
+  slippage_bps: 5.0
+  candidate_source_mode: intraday_first
+  candidate_seed_threshold: 0.0
+  candidate_seed_max_per_day: 80
+  candidate_seed_liquid_overlay_slots: 0
+  candidate_seed_leader_overlay_slots: 0
+  candidate_seed_moderate_liquid_overlay_slots: 0
+  candidate_seed_event_overlay_slots: 20
+  candidate_seed_event_min_score: 1.0
+  candidate_seed_event_min_gap_pct: 0.0
+  candidate_seed_event_max_gap_pct: 0.12
+  candidate_seed_event_min_avg_dollar_vol_30d: 150000000
+  candidate_seed_event_min_ret_5d: 0.0
+  candidate_seed_event_max_entropy_20d: 0.85
+  candidate_final_max_per_day: 12
+  candidate_intraday_rank_mode: weighted
+  candidate_intraday_weight_gain: 0.10
+  candidate_intraday_weight_confirmation: 0.25
+  candidate_intraday_weight_volume_ratio: 0.15
+  candidate_intraday_weight_entry_dollar_volume: 0.20
+  candidate_intraday_weight_avg_dollar_vol_30d: 0.15
+  candidate_intraday_weight_gap: 0.05
+  candidate_intraday_weight_low_entropy: 0.05
+  candidate_intraday_weight_event_score: 0.20
+  candidate_intraday_event_reserve_slots: 2
+  candidate_intraday_event_reserve_min_score: 1.0
+  candidate_intraday_event_reserve_soft_day_only: false
+  candidate_intraday_moderate_liquid_reserve_slots: 0
+  candidate_require_event_flag: true
+  candidate_min_event_score: 1.0
+  candidate_allowed_event_types:
+    - earnings_release
+    - guidance_update
+    - material_contract
+    - other_material_event
+universe:
+  source: broad
+  min_price: 10.0
+backtest:
+  start_date: null
+  end_date: null
+  lookback_trading_days: 200
+  pre_screen_threshold: 0.02
+cache:
+  enabled: true
+  dir: data/cache/intraday
+output:
+  dir: runs/intraday
+  verbose: false

configs/intraday/strategies/leader_intraday_momentum_event_day_liquid_hybrid.yaml

@@ -0,0 +1,185 @@
+_meta:
+  name: Leader Intraday Momentum Event Day Liquid Hybrid
+  description: Flagship high-WR intraday-first basket plus a separate multi-event liquid overlay. The core basket stays identical to the flagship strategy; only on broad same-day filing clusters does the strategy reserve a small extra budget slice for liquid continuation names outside the base basket.
+  id: 27
+strategy_mode: momentum
+strategy:
+  compound_returns: false
+  entry_minutes_after_open: 10
+  confirmation_minutes_after_entry: 5
+  min_confirmation_return_pct: 0.005
+  exit_minutes_before_close: 10
+  stop_loss_pct: null
+  trailing_stop_pct: -0.07
+  overextended_trailing_gain_pct: 0.04
+  overextended_trailing_stop_pct: -0.065
+  min_morning_gain_pct: 0.015
+  max_morning_gain_pct: 0.06
+  max_gap_pct: 0.055
+  min_volume_ratio_14d: 0.04
+  min_entry_volume: 125000
+  min_entry_dollar_volume: 1500000
+  ticker_cooldown_days: 0
+  top_n: 9
+  max_positions_per_sector: 2
+  use_five_sleeves: true
+  five_sleeve_force_count: 4
+  use_event_sleeve: true
+  event_weight: 0.12
+  event_min_score: 1.0
+  event_sleeve_soft_day_only: true
+  soft_day_sparse_max_trades: 2
+  soft_day_sparse_require_no_event: true
+  soft_day_sparse_exempt_largecap: true
+  soft_day_sparse_exempt_moderate_gap_liquid: true
+  soft_day_sparse_scale: 0.7
+  tail_risk_day_max_trades: 3
+  tail_risk_day_min_max_gain_pct: 0.025
+  tail_risk_day_max_support_score: 1.0
+  tail_risk_day_min_max_confirmation_return_pct: 0.01
+  tail_risk_day_require_no_event: true
+  tail_risk_day_event_exemption_min_support_score: 0.35
+  tail_risk_day_exempt_largecap: true
+  tail_risk_day_scale: 0.55
+  low_momentum_single_name_max_gain_pct: 0.025
+  low_momentum_single_name_require_no_event: true
+  low_momentum_single_name_exempt_largecap: true
+  low_momentum_single_name_scale: 0.55
+  max_entropy_20d: 0.86
+  entropy_size_scale_low: 0.78
+  entropy_size_scale_high: 0.86
+  entropy_size_scale_min: 0.6
+  sector_concentration_scale_low: 0.4
+  sector_concentration_scale_high: 0.67
+  sector_concentration_scale_min: 0.8
+  max_vix: 30.0
+  recent_live_scan_days: 0
+  recent_live_scan_min_price: 2.0
+  recent_live_scan_avg_volume_min: 200000
+  recent_live_scan_market_cap_min: 100000000.0
+  recent_live_scan_max_candidates_per_day: 150
+  recent_live_scan_top_n: 6
+  recent_live_scan_min_morning_gain_pct: 0.005
+  recent_live_scan_max_morning_gain_pct: 0.05
+  recent_live_scan_min_confirmation_return_pct: 0.0005
+  recent_live_scan_min_entry_dollar_volume: 50000000.0
+  recent_live_scan_max_gap_pct: 0.04
+  recent_live_scan_max_entropy_20d: 0.9
+  recent_live_scan_use_slow_ignite_sleeve: true
+  recent_live_scan_slow_ignite_weight: 0.30
+  recent_live_scan_slow_ignite_min_gain_pct: 0.003
+  recent_live_scan_slow_ignite_max_gain_pct: 0.015
+  recent_live_scan_slow_ignite_min_entry_dollar_volume: 50000000.0
+  recent_live_scan_slow_ignite_max_entropy_20d: 0.9
+  recent_live_scan_use_liquid_largecap_sleeve: true
+  recent_live_scan_liquid_largecap_weight: 0.35
+  recent_live_scan_liquid_largecap_min_gain_pct: 0.004
+  recent_live_scan_liquid_largecap_max_gain_pct: 0.02
+  recent_live_scan_liquid_largecap_min_confirmation_return_pct: 0.0005
+  recent_live_scan_liquid_largecap_min_entry_dollar_volume: 50000000.0
+  recent_live_scan_liquid_largecap_min_avg_dollar_vol_30d: 500000000.0
+  recent_live_scan_liquid_largecap_max_entropy_20d: 0.9
+  initial_capital: 10000.0
+  slippage_bps: 5.0
+  candidate_source_mode: intraday_first
+  candidate_seed_threshold: 0.0075
+  candidate_seed_max_per_day: 150
+  candidate_seed_liquid_overlay_slots: 3
+  candidate_seed_liquid_min_gap_pct: 0.005
+  candidate_seed_liquid_max_gap_pct: 0.025
+  candidate_seed_liquid_min_avg_dollar_vol_30d: 5000000000.0
+  candidate_seed_liquid_min_ret_5d: 0.0
+  candidate_seed_liquid_max_entropy_20d: 0.87
+  candidate_seed_leader_overlay_slots: 1
+  candidate_seed_leader_min_gap_pct: -0.025
+  candidate_seed_leader_max_gap_pct: 0.01
+  candidate_seed_leader_min_avg_dollar_vol_30d: 500000000.0
+  candidate_seed_leader_min_ret_5d: 0.15
+  candidate_seed_leader_min_atr_pct: 0.06
+  candidate_seed_leader_max_entropy_20d: 0.75
+  candidate_seed_moderate_liquid_overlay_slots: 20
+  candidate_seed_moderate_liquid_min_gap_pct: 0.005
+  candidate_seed_moderate_liquid_max_gap_pct: 0.025
+  candidate_seed_moderate_liquid_min_avg_dollar_vol_30d: 250000000.0
+  candidate_seed_moderate_liquid_max_avg_dollar_vol_30d: 2000000000.0
+  candidate_seed_moderate_liquid_max_entropy_20d: 0.86
+  candidate_seed_event_overlay_slots: 0
+  candidate_seed_event_min_score: null
+  candidate_seed_event_min_gap_pct: null
+  candidate_seed_event_max_gap_pct: null
+  candidate_seed_event_min_avg_dollar_vol_30d: null
+  candidate_seed_event_min_ret_5d: null
+  candidate_seed_event_max_entropy_20d: null
+  candidate_final_max_per_day: 14
+  candidate_intraday_rank_mode: weighted
+  candidate_intraday_weight_gain: 0.10
+  candidate_intraday_weight_confirmation: 0.45
+  candidate_intraday_weight_volume_ratio: 0.20
+  candidate_intraday_weight_entry_dollar_volume: 0.15
+  candidate_intraday_weight_gap: 0.05
+  candidate_intraday_weight_low_entropy: 0.05
+  candidate_intraday_weight_avg_dollar_vol_30d: 0.08
+  candidate_intraday_weight_event_score: 0.0
+  candidate_intraday_event_reserve_slots: 0
+  candidate_intraday_event_reserve_min_score: null
+  candidate_intraday_event_reserve_soft_day_only: false
+  candidate_intraday_moderate_liquid_reserve_slots: 1
+  candidate_intraday_moderate_liquid_reserve_trigger_below: 2
+  candidate_allowed_event_types: []
+  use_event_day_liquid_sleeve: true
+  event_day_liquid_capital_fraction: 0.12
+  event_day_liquid_max_positions: 2
+  event_day_liquid_allowed_event_types:
+    - earnings_release
+    - guidance_update
+    - material_contract
+    - other_material_event
+    - management_change
+    - unknown
+  event_day_liquid_min_event_names: 2
+  event_day_liquid_min_event_score: 1.0
+  event_day_liquid_min_event_support_score: 0.15
+  event_day_liquid_min_total_event_entry_dollar_volume: 100000000.0
+  event_day_liquid_min_gain_pct: 0.004
+  event_day_liquid_max_gain_pct: 0.04
+  event_day_liquid_min_confirmation_return_pct: 0.0005
+  event_day_liquid_min_entry_dollar_volume: 25000000.0
+  event_day_liquid_min_avg_dollar_vol_30d: 250000000.0
+  event_day_liquid_max_entropy_20d: 0.88
+  event_day_liquid_min_support_score: 0.35
+  use_liquid_largecap_sleeve: true
+  liquid_largecap_weight: 0.05
+  use_moderate_gap_liquid_sleeve: true
+  moderate_gap_liquid_weight: 0.0
+  moderate_gap_liquid_min_gap_pct: 0.005
+  moderate_gap_liquid_max_gap_pct: 0.025
+  moderate_gap_liquid_min_gain_pct: 0.015
+  moderate_gap_liquid_max_gain_pct: 0.04
+  moderate_gap_liquid_min_confirmation_return_pct: 0.005
+  moderate_gap_liquid_min_entry_dollar_volume: 40000000.0
+  moderate_gap_liquid_min_avg_dollar_vol_30d: 250000000.0
+  moderate_gap_liquid_max_avg_dollar_vol_30d: 2000000000.0
+  moderate_gap_liquid_min_volume_ratio_14d: 0.04
+  moderate_gap_liquid_max_entropy_20d: 0.86
+  fallback_liquid_largecap_slots: 1
+  fallback_liquid_largecap_trigger_below: 2
+  liquid_largecap_min_gain_pct: 0.004
+  liquid_largecap_max_gain_pct: 0.015
+  liquid_largecap_min_confirmation_return_pct: 0.0005
+  liquid_largecap_min_entry_dollar_volume: 50000000.0
+  liquid_largecap_min_avg_dollar_vol_30d: 2000000000.0
+  liquid_largecap_max_entropy_20d: 0.87
+universe:
+  source: broad
+  min_price: 10.0
+backtest:
+  start_date: null
+  end_date: null
+  lookback_trading_days: 200
+  pre_screen_threshold: 0.02
+cache:
+  enabled: true
+  dir: data/cache/intraday
+output:
+  dir: runs/intraday
+  verbose: false

configs/intraday/strategies/leader_intraday_momentum_high_wr.yaml

@@ -1,48 +0,0 @@
-_meta:
-  name: Leader Intraday Momentum High WR
-  description: More selective high-win-rate variant of the safe momentum basket. Uses a 5-minute confirmation that requires +0.45% follow-through, a 2.0M entry dollar-volume floor, a tighter 6.0% morning overextension cap, a 5.5% opening-gap cap, an 8.0% base trailing stop, and a slightly tighter 7.5% trail once a name is already up 4%+ at entry. Intended for users who prioritize win rate over basket breadth.
-  id: 20
-strategy_mode: momentum
-strategy:
-  compound_returns: false
-  entry_minutes_after_open: 10
-  confirmation_minutes_after_entry: 5
-  min_confirmation_return_pct: 0.0045
-  exit_minutes_before_close: 10
-  stop_loss_pct: null
-  trailing_stop_pct: -0.08
-  overextended_trailing_gain_pct: 0.04
-  overextended_trailing_stop_pct: -0.075
-  min_morning_gain_pct: 0.015
-  max_morning_gain_pct: 0.06
-  max_gap_pct: 0.055
-  min_entry_volume: 125000
-  min_entry_dollar_volume: 2000000
-  ticker_cooldown_days: 4
-  top_n: 8
-  max_positions_per_sector: 2
-  use_five_sleeves: true
-  max_entropy_20d: 0.86
-  max_vix: 30.0
-  recent_live_scan_days: 0
-  recent_live_scan_min_price: 2.0
-  recent_live_scan_avg_volume_min: 200000
-  recent_live_scan_market_cap_min: 100000000.0
-  recent_live_scan_max_candidates_per_day: 150
-  initial_capital: 10000.0
-  slippage_bps: 5.0
-  market_regime_spy_threshold: null
-universe:
-  source: broad
-  min_price: 10.0
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-  pre_screen_threshold: 0.02
-cache:
-  enabled: true
-  dir: data/cache/intraday
-output:
-  dir: runs/intraday
-  verbose: false

configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml

@@ -1,6 +1,6 @@
 _meta:
   name: Leader Intraday Momentum High WR Intraday First
-  description: Corrected high-win-rate momentum variant that replaces the pure daily-gap candidate source with a historical intraday-first shortlist. It uses a 1.5% seed gap, reranks the shortlist at entry time using confirmation, volume-ratio, dollar-volume, gap, and low-entropy quality, trims exposure on the noisiest high-entropy names, only on soft days lets one event sleeve substitute a catalyst-backed name into the basket, adds a bounded moderate-gap liquid follow-through reserve for names that broad scan catches but the raw gap rank misses, and applies a no-event sparse basket tail defense. Intended to improve corrected Q1 and weak 2025 quarter robustness without reintroducing lookahead.
+  description: Corrected high-win-rate momentum variant that replaces the pure daily-gap candidate source with a historical intraday-first shortlist. It uses a 1.5% seed gap, reranks the shortlist at entry time using confirmation, volume-ratio, dollar-volume, gap, and low-entropy quality, trims exposure on the noisiest high-entropy names, only on soft days lets one event sleeve substitute a catalyst-backed name into the basket, adds a bounded moderate-gap liquid follow-through reserve for names that broad scan catches but the raw gap rank misses, scales down sparse soft-day baskets that lack supportive event or liquid-follow-through structure, and now reserves a small extra budget slice on broad same-day filing clusters to add liquid continuation names outside the base basket.
   id: 25
 strategy_mode: momentum
 strategy:
@@ -28,14 +28,24 @@ strategy:
   event_weight: 0.12
   event_min_score: 1.0
   event_sleeve_soft_day_only: true
+  soft_day_sparse_max_trades: 2
+  soft_day_sparse_require_no_event: true
+  soft_day_sparse_exempt_largecap: true
+  soft_day_sparse_exempt_moderate_gap_liquid: true
+  soft_day_sparse_scale: 0.7
   tail_risk_day_max_trades: 3
   tail_risk_day_min_max_gain_pct: 0.025
   tail_risk_day_max_support_score: 1.0
   tail_risk_day_min_max_entropy_20d: null
   tail_risk_day_min_max_confirmation_return_pct: 0.01
   tail_risk_day_require_no_event: true
+  tail_risk_day_event_exemption_min_support_score: 0.35
   tail_risk_day_exempt_largecap: true
   tail_risk_day_scale: 0.55
+  low_momentum_single_name_max_gain_pct: 0.025
+  low_momentum_single_name_require_no_event: true
+  low_momentum_single_name_exempt_largecap: true
+  low_momentum_single_name_scale: 0.55
   max_entropy_20d: 0.86
   entropy_size_scale_low: 0.78
   entropy_size_scale_high: 0.86
@@ -106,6 +116,27 @@ strategy:
   candidate_intraday_weight_avg_dollar_vol_30d: 0.08
   candidate_intraday_moderate_liquid_reserve_slots: 1
   candidate_intraday_moderate_liquid_reserve_trigger_below: 2
+  use_event_day_liquid_sleeve: true
+  event_day_liquid_capital_fraction: 0.12
+  event_day_liquid_max_positions: 2
+  event_day_liquid_allowed_event_types:
+    - earnings_release
+    - guidance_update
+    - material_contract
+    - other_material_event
+    - management_change
+    - unknown
+  event_day_liquid_min_event_names: 2
+  event_day_liquid_min_event_score: 1.0
+  event_day_liquid_min_event_support_score: 0.15
+  event_day_liquid_min_total_event_entry_dollar_volume: 100000000.0
+  event_day_liquid_min_gain_pct: 0.004
+  event_day_liquid_max_gain_pct: 0.04
+  event_day_liquid_min_confirmation_return_pct: 0.0005
+  event_day_liquid_min_entry_dollar_volume: 25000000.0
+  event_day_liquid_min_avg_dollar_vol_30d: 250000000.0
+  event_day_liquid_max_entropy_20d: 0.88
+  event_day_liquid_min_support_score: 0.35
   use_liquid_largecap_sleeve: true
   liquid_largecap_weight: 0.05
   use_moderate_gap_liquid_sleeve: true

configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first_cluster_overlay_base.yaml

@@ -1,7 +1,7 @@
 _meta:
-  name: Leader Intraday Momentum Defended
+  name: Leader Intraday Momentum High WR Intraday First Cluster Overlay Base
-  description: Intraday-first leader momentum with layered downside defense. It keeps the corrected broad-universe candidate engine, then scales down weak market/breadth days and also shrinks thin, weak-support single-name breakout days to improve loss containment without changing the core entry logic.
+  description: Experimental base config for evaluating post-allocation liquid-cluster and sector-ETF breadth overlays on top of the High WR Intraday First flagship. This is not the official production strategy; it exists to fetch the wider metadata/proxy set needed for overlay research.
-  id: 31
+  id: 26
 strategy_mode: momentum
 strategy:
   compound_returns: false
@@ -10,9 +10,9 @@ strategy:
   min_confirmation_return_pct: 0.005
   exit_minutes_before_close: 10
   stop_loss_pct: null
-  trailing_stop_pct: -0.08
+  trailing_stop_pct: -0.07
   overextended_trailing_gain_pct: 0.04
-  overextended_trailing_stop_pct: -0.075
+  overextended_trailing_stop_pct: -0.065
   min_morning_gain_pct: 0.015
   max_morning_gain_pct: 0.06
   max_gap_pct: 0.055
@@ -24,32 +24,36 @@ strategy:
   max_positions_per_sector: 2
   use_five_sleeves: true
   five_sleeve_force_count: 4
-  tail_risk_day_max_trades: 1
+  use_event_sleeve: true
-  tail_risk_day_min_max_gain_pct: 0.03
+  event_weight: 0.12
-  tail_risk_day_max_support_score: 0.25
+  event_min_score: 1.0
-  tail_risk_day_min_max_entropy_20d: 0.79
+  event_sleeve_soft_day_only: true
+  soft_day_sparse_max_trades: 2
+  soft_day_sparse_require_no_event: true
+  soft_day_sparse_exempt_largecap: true
+  soft_day_sparse_exempt_moderate_gap_liquid: true
+  soft_day_sparse_scale: 0.7
+  tail_risk_day_max_trades: 3
+  tail_risk_day_min_max_gain_pct: 0.025
+  tail_risk_day_max_support_score: 1.0
+  tail_risk_day_min_max_entropy_20d: null
   tail_risk_day_min_max_confirmation_return_pct: 0.01
+  tail_risk_day_require_no_event: true
+  tail_risk_day_event_exemption_min_support_score: 0.35
   tail_risk_day_exempt_largecap: true
   tail_risk_day_scale: 0.55
+  low_momentum_single_name_max_gain_pct: 0.025
+  low_momentum_single_name_require_no_event: true
+  low_momentum_single_name_exempt_largecap: true
+  low_momentum_single_name_scale: 0.55
   max_entropy_20d: 0.86
   entropy_size_scale_low: 0.78
   entropy_size_scale_high: 0.86
   entropy_size_scale_min: 0.6
+  sector_concentration_scale_low: 0.4
+  sector_concentration_scale_high: 0.67
+  sector_concentration_scale_min: 0.8
   max_vix: 30.0
-  market_regime_spy_threshold: null
-  market_regime_gap_threshold: -0.015
-  market_regime_gap_ticker: SPY
-  regime_size_scale_low: -0.015
-  regime_size_scale_high: 0.002
-  regime_size_scale_min: 0.65
-  min_candidate_breadth: 0.4
-  breadth_size_scale_low: 0.4
-  breadth_size_scale_high: 0.62
-  breadth_size_scale_min: 0.7
-  soft_day_scaler_threshold: 0.88
-  soft_day_max_trades: 5
-  rolling_loss_days: null
-  rolling_loss_threshold: null
   recent_live_scan_days: 0
   recent_live_scan_min_price: 2.0
   recent_live_scan_avg_volume_min: 200000
@@ -78,6 +82,7 @@ strategy:
   recent_live_scan_liquid_largecap_max_entropy_20d: 0.9
   initial_capital: 10000.0
   slippage_bps: 5.0
+  market_regime_spy_threshold: null
   candidate_source_mode: intraday_first
   candidate_seed_threshold: 0.0075
   candidate_seed_max_per_day: 150
@@ -94,6 +99,12 @@ strategy:
   candidate_seed_leader_min_ret_5d: 0.15
   candidate_seed_leader_min_atr_pct: 0.06
   candidate_seed_leader_max_entropy_20d: 0.75
+  candidate_seed_moderate_liquid_overlay_slots: 20
+  candidate_seed_moderate_liquid_min_gap_pct: 0.005
+  candidate_seed_moderate_liquid_max_gap_pct: 0.025
+  candidate_seed_moderate_liquid_min_avg_dollar_vol_30d: 250000000.0
+  candidate_seed_moderate_liquid_max_avg_dollar_vol_30d: 2000000000.0
+  candidate_seed_moderate_liquid_max_entropy_20d: 0.86
   candidate_final_max_per_day: 14
   candidate_intraday_rank_mode: weighted
   candidate_intraday_weight_gain: 0.10
@@ -103,8 +114,22 @@ strategy:
   candidate_intraday_weight_gap: 0.05
   candidate_intraday_weight_low_entropy: 0.05
   candidate_intraday_weight_avg_dollar_vol_30d: 0.08
+  candidate_intraday_moderate_liquid_reserve_slots: 1
+  candidate_intraday_moderate_liquid_reserve_trigger_below: 2
   use_liquid_largecap_sleeve: true
   liquid_largecap_weight: 0.05
+  use_moderate_gap_liquid_sleeve: true
+  moderate_gap_liquid_weight: 0.0
+  moderate_gap_liquid_min_gap_pct: 0.005
+  moderate_gap_liquid_max_gap_pct: 0.025
+  moderate_gap_liquid_min_gain_pct: 0.015
+  moderate_gap_liquid_max_gain_pct: 0.04
+  moderate_gap_liquid_min_confirmation_return_pct: 0.005
+  moderate_gap_liquid_min_entry_dollar_volume: 40000000.0
+  moderate_gap_liquid_min_avg_dollar_vol_30d: 250000000.0
+  moderate_gap_liquid_max_avg_dollar_vol_30d: 2000000000.0
+  moderate_gap_liquid_min_volume_ratio_14d: 0.04
+  moderate_gap_liquid_max_entropy_20d: 0.86
   fallback_liquid_largecap_slots: 1
   fallback_liquid_largecap_trigger_below: 2
   liquid_largecap_min_gain_pct: 0.004
@@ -113,6 +138,26 @@ strategy:
   liquid_largecap_min_entry_dollar_volume: 50000000.0
   liquid_largecap_min_avg_dollar_vol_30d: 2000000000.0
   liquid_largecap_max_entropy_20d: 0.87
+  use_liquid_cluster_engine: true
+  liquid_cluster_capital_fraction: 0.15
+  liquid_cluster_max_positions: 1
+  liquid_cluster_max_positions_per_sector: 1
+  liquid_cluster_min_members: 2
+  liquid_cluster_min_gain_pct: 0.015
+  liquid_cluster_max_gain_pct: 0.04
+  liquid_cluster_min_confirmation_return_pct: 0.005
+  liquid_cluster_min_entry_dollar_volume: 40000000.0
+  liquid_cluster_min_avg_dollar_vol_30d: 250000000.0
+  liquid_cluster_max_avg_dollar_vol_30d: 2000000000.0
+  liquid_cluster_min_volume_ratio_14d: 0.04
+  liquid_cluster_max_entropy_20d: 0.86
+  liquid_cluster_min_sector_avg_confirmation_return_pct: 0.005
+  liquid_cluster_min_sector_total_entry_dollar_volume: 100000000.0
+  liquid_cluster_require_special_liquidity_gate: true
+  use_sector_etf_sleeve: true
+  sector_etf_capital_fraction: 0.10
+  sector_etf_max_positions: 1
+  sector_etf_min_sector_score: 0.20
 universe:
   source: broad
   min_price: 10.0

configs/intraday/strategies/leader_intraday_momentum_liquid_continuation_core.yaml

@@ -0,0 +1,117 @@
+_meta:
+  name: Leader Intraday Momentum Liquid Continuation Core
+  description: Separate liquid-continuation core engine. Instead of treating liquid follow-through as an overlay, this strategy makes moderate-gap liquid names, liquid large-cap leaders, and sector breadth-confirmed continuation the primary basket selection path.
+  id: 28
+strategy_mode: momentum
+strategy:
+  compound_returns: false
+  entry_minutes_after_open: 10
+  confirmation_minutes_after_entry: 5
+  min_confirmation_return_pct: 0.003
+  exit_minutes_before_close: 10
+  stop_loss_pct: null
+  trailing_stop_pct: -0.075
+  overextended_trailing_gain_pct: 0.04
+  overextended_trailing_stop_pct: -0.06
+  min_gap_pct: 0.0
+  min_morning_gain_pct: 0.006
+  max_morning_gain_pct: 0.04
+  max_gap_pct: 0.05
+  min_volume_ratio_14d: 0.02
+  min_entry_volume: 100000
+  min_entry_dollar_volume: 20000000
+  ticker_cooldown_days: 0
+  top_n: 4
+  max_positions_per_sector: 2
+  use_five_sleeves: false
+  momentum_selection_mode: liquid_continuation
+  soft_day_sparse_max_trades: 2
+  soft_day_sparse_exempt_largecap: true
+  soft_day_sparse_exempt_moderate_gap_liquid: true
+  soft_day_sparse_scale: 0.8
+  tail_risk_day_max_trades: 3
+  tail_risk_day_min_max_gain_pct: 0.02
+  tail_risk_day_min_max_confirmation_return_pct: 0.006
+  tail_risk_day_exempt_largecap: true
+  tail_risk_day_scale: 0.65
+  max_entropy_20d: 0.88
+  entropy_size_scale_low: 0.80
+  entropy_size_scale_high: 0.88
+  entropy_size_scale_min: 0.7
+  sector_concentration_scale_low: 0.4
+  sector_concentration_scale_high: 0.67
+  sector_concentration_scale_min: 0.85
+  max_vix: 35.0
+  initial_capital: 10000.0
+  slippage_bps: 5.0
+  market_regime_spy_threshold: null
+  candidate_source_mode: intraday_first
+  candidate_seed_threshold: 0.0
+  candidate_seed_max_per_day: 180
+  candidate_seed_liquid_overlay_slots: 10
+  candidate_seed_liquid_min_gap_pct: -0.015
+  candidate_seed_liquid_max_gap_pct: 0.03
+  candidate_seed_liquid_min_avg_dollar_vol_30d: 2000000000.0
+  candidate_seed_liquid_min_ret_5d: 0.0
+  candidate_seed_liquid_max_entropy_20d: 0.88
+  candidate_seed_leader_overlay_slots: 6
+  candidate_seed_leader_min_gap_pct: -0.02
+  candidate_seed_leader_max_gap_pct: 0.03
+  candidate_seed_leader_min_avg_dollar_vol_30d: 500000000.0
+  candidate_seed_leader_min_ret_5d: 0.10
+  candidate_seed_leader_min_atr_pct: 0.04
+  candidate_seed_leader_max_entropy_20d: 0.82
+  candidate_seed_moderate_liquid_overlay_slots: 40
+  candidate_seed_moderate_liquid_min_gap_pct: 0.002
+  candidate_seed_moderate_liquid_max_gap_pct: 0.04
+  candidate_seed_moderate_liquid_min_avg_dollar_vol_30d: 250000000.0
+  candidate_seed_moderate_liquid_max_avg_dollar_vol_30d: 4000000000.0
+  candidate_seed_moderate_liquid_min_ret_5d: 0.0
+  candidate_seed_moderate_liquid_max_entropy_20d: 0.88
+  candidate_final_max_per_day: 14
+  candidate_intraday_rank_mode: liquid_continuation
+  candidate_intraday_moderate_liquid_reserve_slots: 2
+  candidate_intraday_moderate_liquid_reserve_trigger_below: 3
+  use_liquid_largecap_sleeve: true
+  liquid_largecap_weight: 0.0
+  liquid_largecap_min_gain_pct: 0.006
+  liquid_largecap_max_gain_pct: 0.025
+  liquid_largecap_min_confirmation_return_pct: 0.003
+  liquid_largecap_min_entry_dollar_volume: 60000000.0
+  liquid_largecap_min_avg_dollar_vol_30d: 2000000000.0
+  liquid_largecap_max_entropy_20d: 0.90
+  use_moderate_gap_liquid_sleeve: true
+  moderate_gap_liquid_weight: 0.0
+  moderate_gap_liquid_min_gap_pct: 0.005
+  moderate_gap_liquid_max_gap_pct: 0.035
+  moderate_gap_liquid_min_gain_pct: 0.01
+  moderate_gap_liquid_max_gain_pct: 0.04
+  moderate_gap_liquid_min_confirmation_return_pct: 0.003
+  moderate_gap_liquid_min_entry_dollar_volume: 40000000.0
+  moderate_gap_liquid_min_avg_dollar_vol_30d: 250000000.0
+  moderate_gap_liquid_max_avg_dollar_vol_30d: 4000000000.0
+  moderate_gap_liquid_min_volume_ratio_14d: 0.04
+  moderate_gap_liquid_max_entropy_20d: 0.88
+  use_sector_thrust_sleeve: true
+  sector_thrust_weight: 0.0
+  sector_thrust_min_members: 2
+  sector_thrust_min_gain_pct: 0.01
+  sector_thrust_min_confirmation_return_pct: 0.003
+  sector_thrust_min_entry_dollar_volume: 40000000.0
+  sector_thrust_min_avg_dollar_vol_30d: 250000000.0
+  sector_thrust_min_sector_avg_confirmation_return_pct: 0.003
+  sector_thrust_min_sector_total_entry_dollar_volume: 150000000.0
+universe:
+  source: broad
+  min_price: 10.0
+backtest:
+  start_date: null
+  end_date: null
+  lookback_trading_days: 200
+  pre_screen_threshold: 0.02
+cache:
+  enabled: true
+  dir: data/cache/intraday
+output:
+  dir: runs/intraday
+  verbose: false

configs/intraday/strategies/leader_intraday_momentum_safe.yaml

@@ -1,101 +0,0 @@
-_meta:
-  name: Leader Intraday Momentum Safe
-  description: Safer intraday-first leader basket derived from the current high-win-rate engine. It keeps the liquid-largecap-aware candidate stack, same-day confirmation rerank, and five-sleeve blend, but scales sparse 1-5 position days below full size to reduce trap-day drawdowns without reverting to the stale pre-intraday-first safe rules.
-  id: 19
-strategy_mode: momentum
-strategy:
-  compound_returns: false
-  entry_minutes_after_open: 10
-  confirmation_minutes_after_entry: 5
-  min_confirmation_return_pct: 0.005
-  exit_minutes_before_close: 10
-  stop_loss_pct: null
-  trailing_stop_pct: -0.08
-  overextended_trailing_gain_pct: 0.04
-  overextended_trailing_stop_pct: -0.075
-  min_morning_gain_pct: 0.015
-  max_morning_gain_pct: 0.06
-  max_gap_pct: 0.055
-  min_volume_ratio_14d: 0.04
-  min_entry_volume: 125000
-  min_entry_dollar_volume: 1500000
-  ticker_cooldown_days: 0
-  top_n: 9
-  full_size_positions_threshold: 6
-  sparse_day_size_floor: 0.5
-  max_positions_per_sector: 2
-  use_five_sleeves: true
-  five_sleeve_force_count: 4
-  max_entropy_20d: 0.86
-  max_vix: 30.0
-  recent_live_scan_days: 0
-  recent_live_scan_min_price: 2.0
-  recent_live_scan_avg_volume_min: 200000
-  recent_live_scan_market_cap_min: 100000000.0
-  recent_live_scan_max_candidates_per_day: 150
-  recent_live_scan_top_n: 6
-  recent_live_scan_min_morning_gain_pct: 0.005
-  recent_live_scan_max_morning_gain_pct: 0.05
-  recent_live_scan_min_confirmation_return_pct: 0.0005
-  recent_live_scan_min_entry_dollar_volume: 50000000.0
-  recent_live_scan_max_gap_pct: 0.04
-  recent_live_scan_max_entropy_20d: 0.9
-  recent_live_scan_use_slow_ignite_sleeve: true
-  recent_live_scan_slow_ignite_weight: 0.30
-  recent_live_scan_slow_ignite_min_gain_pct: 0.003
-  recent_live_scan_slow_ignite_max_gain_pct: 0.015
-  recent_live_scan_slow_ignite_min_entry_dollar_volume: 50000000.0
-  recent_live_scan_slow_ignite_max_entropy_20d: 0.9
-  recent_live_scan_use_liquid_largecap_sleeve: true
-  recent_live_scan_liquid_largecap_weight: 0.35
-  recent_live_scan_liquid_largecap_min_gain_pct: 0.004
-  recent_live_scan_liquid_largecap_max_gain_pct: 0.02
-  recent_live_scan_liquid_largecap_min_confirmation_return_pct: 0.0005
-  recent_live_scan_liquid_largecap_min_entry_dollar_volume: 50000000.0
-  recent_live_scan_liquid_largecap_min_avg_dollar_vol_30d: 500000000.0
-  recent_live_scan_liquid_largecap_max_entropy_20d: 0.9
-  initial_capital: 10000.0
-  slippage_bps: 5.0
-  market_regime_spy_threshold: null
-  candidate_source_mode: intraday_first
-  candidate_seed_threshold: 0.0075
-  candidate_seed_max_per_day: 150
-  candidate_seed_liquid_overlay_slots: 3
-  candidate_seed_liquid_min_gap_pct: 0.005
-  candidate_seed_liquid_max_gap_pct: 0.025
-  candidate_seed_liquid_min_avg_dollar_vol_30d: 5000000000.0
-  candidate_seed_liquid_min_ret_5d: 0.0
-  candidate_seed_liquid_max_entropy_20d: 0.87
-  candidate_final_max_per_day: 12
-  candidate_intraday_rank_mode: weighted
-  candidate_intraday_weight_gain: 0.10
-  candidate_intraday_weight_confirmation: 0.45
-  candidate_intraday_weight_volume_ratio: 0.20
-  candidate_intraday_weight_entry_dollar_volume: 0.15
-  candidate_intraday_weight_gap: 0.05
-  candidate_intraday_weight_low_entropy: 0.05
-  candidate_intraday_weight_avg_dollar_vol_30d: 0.08
-  use_liquid_largecap_sleeve: true
-  liquid_largecap_weight: 0.05
-  fallback_liquid_largecap_slots: 1
-  fallback_liquid_largecap_trigger_below: 2
-  liquid_largecap_min_gain_pct: 0.004
-  liquid_largecap_max_gain_pct: 0.015
-  liquid_largecap_min_confirmation_return_pct: 0.0005
-  liquid_largecap_min_entry_dollar_volume: 50000000.0
-  liquid_largecap_min_avg_dollar_vol_30d: 2000000000.0
-  liquid_largecap_max_entropy_20d: 0.87
-universe:
-  source: broad
-  min_price: 10.0
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-  pre_screen_threshold: 0.02
-cache:
-  enabled: true
-  dir: data/cache/intraday
-output:
-  dir: runs/intraday
-  verbose: false

configs/intraday/strategies/orb_gainers_v23_safe.yaml

@@ -1,116 +0,0 @@
-_meta:
-  id: 29
-  name: "ORB Gainers V23 Safe"
-  status: experimental
-  parent: orb_gainers_v23
-  description: >
-    V23 파생 전략 — "안전 투자자" 버전. 수익률을 희생해서 손실을 최소화하는 것이 목표.
-    V23 대비 5가지 방향으로 보수화:
-
-    1. 레짐 필터 강화: QQQ 갭 0.15% → 0.30% (더 강한 상승 장세만 진입)
-    2. 진입 품질 상향: min_rvol 1.5→2.0, min_candidate_breadth 0.60→0.70
-    3. 포지션 크기 축소: risk_per_trade 5%→3%, max_simultaneous 3→2
-    4. 손실 governor 강화: rolling_loss -7%→-3%, drawdown_governor 2.5%→1.5%
-    5. 일일 손실 컷: daily_max_loss 5%→3%, max_stops_per_day 5→3
-
-    streak_sizing 비활성화 (승리 시 포지션 키우지 않음 — 안전 우선)
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: gainers_leader
-  live_readiness: experimental
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 45
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-
-  # === SAFE CHANGE: higher rvol requirement (was 1.5) ===
-  min_rvol: 2.0
-  # === SAFE CHANGE: slightly higher gap floor (was 0.02) ===
-  min_abs_gap_pct: 0.025
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-
-  # === SAFE CHANGE: higher breadth requirement (was 0.60) ===
-  min_candidate_breadth: 0.70
-  # === SAFE CHANGE: stronger QQQ regime required (was 0.0015 = 0.15%) ===
-  market_regime_spy_threshold: 0.003
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  # === SAFE CHANGE: stop much sooner on bad streaks (was -0.07) ===
-  rolling_loss_threshold: -0.03
-  # === SAFE CHANGE: max 2 simultaneous positions (was 3) ===
-  max_simultaneous_entries: 2
-  min_breakout_rel_vol: 1.2
-
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  partial_exit_at_r: 99.0
-  partial_exit_pct: 0.50
-
-  # === SAFE CHANGE: smaller position risk (was 0.05) ===
-  risk_per_trade_pct: 0.03
-  max_position_pct: 0.70
-  # === SAFE CHANGE: cut daily losses sooner (was 0.05) ===
-  daily_max_loss_pct: 0.03
-  # === SAFE CHANGE: stop the day after 3 stops (was 5) ===
-  max_stops_per_day: 3
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  # === SAFE CHANGE: tighter portfolio DD governor (was 0.025) ===
-  drawdown_governor_threshold: 0.015
-  drawdown_governor_min_scale: 0.30
-
-  # === SAFE CHANGE: no streak sizing boost (was bonus=0.70, max=2.5) ===
-  streak_sizing_win_bonus: 0.0
-  streak_sizing_max: 1.0
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/orb_gainers_v23_safe_v2.yaml

@@ -1,124 +0,0 @@
-_meta:
-  id: 30
-  name: "ORB Gainers V23 Safe v2"
-  status: validated
-  parent: orb_gainers_v23
-  description: >
-    V23 파생 전략 — "안전 투자자" v2. v1(+5.16%, DD -13.49%)보다 DD를 줄이는 것이 목표.
-
-    핵심 발견 (v1 분석):
-    - V23 손실일의 QQQ 갭: +0.3%~+3.4% → QQQ 임계값 강화는 효과 없음
-    - 손실은 QQQ 방향이 아닌 개별 종목 실패에서 발생
-    - DD는 손실 클러스터(Oct/Sep 2025)에서 집중 발생
-
-    v2 접근법:
-    1. Rolling loss governor 강화: 손실 직후 즉시 거래 중단 (-2% threshold)
-    2. Partial exit 활성화: 1R(0.75ATR) 도달시 50% 이익 실현 → 많은 거래를 "무조건 수익"으로
-    3. 포지션 축소: risk 5%→2% (손실 기회당 절대액 감소)
-    4. 동시 포지션: 3→2 (손실 클러스터링 방지)
-    5. QQQ 레짐: 유지 (효과 없음이 증명됨 — 더 강화해도 소용없음)
-    6. Streak sizing 비활성화 (안전 우선)
-
-    200d 검증 결과 (2025-07-03 → 2026-04-20):
-    - 수익: +36.67% (V23 +109.32% 대비)
-    - Max DD: -11.54% (고점 대비, 그러나 시작 자본 이하 0일!)
-    - Sharpe: 2.24
-    - 시작 자본($10k) 이하: 0일 (최저점 $10,017 on 2025-07-09)
-    - 최악의 하루: -$344 (V23 -$981 대비)
-    - 거래일: 49/200, 거래: 154건
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: gainers_leader
-  live_readiness: experimental
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 45
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.02
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  rolling_loss_days: 5
-  # === KEY CHANGE: stop IMMEDIATELY after $200 loss (was -7%) ===
-  rolling_loss_threshold: -0.02
-  # === CHANGE: max 2 simultaneous (was 3) ===
-  max_simultaneous_entries: 2
-  min_breakout_rel_vol: 1.2
-
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  # === KEY CHANGE: lock in 50% at 1R (was disabled at 99R) ===
-  partial_exit_at_r: 1.0
-  partial_exit_pct: 0.50
-
-  # === CHANGE: smaller per-trade risk (was 0.05) ===
-  risk_per_trade_pct: 0.02
-  max_position_pct: 0.70
-  # === CHANGE: tighter daily loss cut (was 0.05) ===
-  daily_max_loss_pct: 0.02
-  max_stops_per_day: 3
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  # === CHANGE: tighter portfolio governor (was 0.025) ===
-  drawdown_governor_threshold: 0.015
-  drawdown_governor_min_scale: 0.50
-
-  # === CHANGE: no streak sizing (was bonus=0.70, max=2.5) ===
-  streak_sizing_win_bonus: 0.0
-  streak_sizing_max: 1.0
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/orb_gainers_v23_safe_v3.yaml

@@ -1,112 +0,0 @@
-_meta:
-  id: 31
-  name: "ORB Gainers V23 Safe v3"
-  status: experimental
-  parent: orb_gainers_v23_safe_v2
-  description: >
-    V23 Safe v3 — "안전 투자자" 최적화.
-
-    v2 분석 결과 (200d):
-    - +36.67%, DD -11.54%, 시작 자본 이하: 0일 (최저 $10,017)
-    - Max DD 원인: Nov-Dec 2025 손실 클러스터
-      11/21(-$321) 후 rolling window(5일)가 만료되어 12월에 다시 거래 시작
-      → COHR, TSLA, LITE, VST, CYTK 등 연속 손실
-
-    v3 변경:
-    1. rolling_loss_days: 5→10 (손실 기억 기간 연장 → Nov 손실 후 Dec 재진입 방지)
-    2. rolling_loss_threshold: -0.02→-0.015 (더 빠른 중단: $150 누적 손실시 정지)
-    3. 나머지는 v2 동일 (partial_exit@1R, risk=2%, max_entries=2)
-
-    목표: 고점 대비 DD를 -8% 이하로 줄이면서 시작 자본 이하 0일 유지
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: gainers_leader
-  live_readiness: experimental
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 45
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.02
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  # === KEY CHANGE: longer loss memory (was 5) ===
-  rolling_loss_days: 10
-  # === KEY CHANGE: stop sooner — $150 loss triggers pause (was -0.02) ===
-  rolling_loss_threshold: -0.015
-  max_simultaneous_entries: 2
-  min_breakout_rel_vol: 1.2
-
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  # 50% partial exit at 1R (lock in gains early)
-  partial_exit_at_r: 1.0
-  partial_exit_pct: 0.50
-
-  risk_per_trade_pct: 0.02
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.02
-  max_stops_per_day: 3
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  drawdown_governor_threshold: 0.015
-  drawdown_governor_min_scale: 0.50
-
-  streak_sizing_win_bonus: 0.0
-  streak_sizing_max: 1.0
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/orb_gainers_v23_safe_v9.yaml

@@ -1,107 +0,0 @@
-_meta:
-  id: 37
-  name: "ORB Gainers V23 Safe v9"
-  status: validated_200d_only
-  parent: orb_gainers_v23_safe_v8
-  description: >
-    V23 Safe v9 — v8 + streak_sizing_win_bonus: 0.70 (V23 level streak sizing).
-    VALIDATED champion of the Safe family on 200d window ONLY (2026-04-21).
-    주의: 400d에서는 V23이 모든 지표에서 완전히 우월 — +146% vs +101%, DD -13.7% vs -17.2%.
-    v9는 200d 단기 보수적 대안으로만 유효. 실전 배포 기준은 V23.
-
-    Safe v8 결과: +82.36%, DD -7.72%, Sharpe 3.14 — V23 Sharpe(3.01)보다 높고 DD는 5pp 낮음.
-    단, 수익은 V23(+109.32%)보다 27pp 낮음. 차이 원인: V23의 streak sizing(win_bonus=0.70).
-    V23에서 streak_sizing은 핵심 수익 증폭기 (V19→V21 승진에 기여).
-
-    v9 가설: v8 safe mechanisms(partial_exit + rolling_loss-2% + max_sim=2) + V23의
-    streak_sizing(0.70) = +100%+ 수익 AND DD < V23 -12.91%?
-
-    200d 결과 (2025-07-03→2026-04-20): +101.25%, DD -7.62%, WR 58.06%, Sharpe 3.34
-      worst_day -$324, trade_days 46/200, 124 trades.
-    400d 결과 (2024-09-13→2026-04-20): +101.01%, DD -17.20%, WR 57.08%, Sharpe 1.99
-      profit_factor 1.77, worst_day -6.11%, 226 trades, 93 trade days.
-    400d gate: DD -17.20% ≤ -18% ✓ AND return +101% ≥ +90% ✓ → PROMOTED.
-    V23 대비 (200d): DD -5.29pp 개선 (-7.62% vs -12.91%); Sharpe +0.33 우위;
-    수익은 -8pp 낮음 (-101.25% vs +109.32%).
-
-    *** 2026-04-21 UPDATE: V23 TRUE 400d result confirmed with correct pipeline ***
-    V23 400d TRUE: +146.09%, DD -13.66%, Sharpe 2.33 (vs v9: +101.01%, DD -17.20%, Sharpe 1.99)
-    V23 STRICTLY DOMINATES Safe v9 on 400d in return (+45pp), DD (+3.5pp better), and Sharpe.
-    "Risk-adjusted superior" claim is ONLY valid on 200d window. On 400d, V23 is also safer.
-    V23 is the absolute champion. v9 remains valid as 200d conservative alternative only.
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: gainers_leader
-  live_readiness: experimental
-  orb_minutes: 5
-  sim_bar_minutes: 5
-  entry_direction: long_only
-  order_timeout_minutes: 45
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.02
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  rolling_loss_threshold: -0.02
-  max_simultaneous_entries: 2
-  min_breakout_rel_vol: 1.2
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-  partial_exit_at_r: 1.0
-  partial_exit_pct: 0.50
-  risk_per_trade_pct: 0.05
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.02
-  max_stops_per_day: 3
-  exit_minutes_before_close: 5
-  slippage_bps: 5.0
-  initial_capital: 10000
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-  drawdown_governor_threshold: 0.015
-  drawdown_governor_min_scale: 0.50
-  # === KEY CHANGE: enable streak sizing (V23 level) ===
-  streak_sizing_win_bonus: 0.70
-  streak_sizing_max: 2.5
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/orb_gainers_v24_1_candidate_entrycap.yaml

@@ -1,16 +1,13 @@
 _meta:
-  id: 34
+  id: 105
-  name: "ORB Gainers V23 Safe v6"
+  name: "ORB Gainers V24.1 Candidate Entry Cap"
-  status: experimental
+  status: research
-  parent: orb_gainers_v23_safe_v4
+  live_readiness: experimental
+  parent: orb_gainers_v24_quality_overlay
   description: >
-    V23 Safe v6 — v4 + risk_per_trade_pct 2%→3%.
+    Narrow candidate for V24.1. Keeps V24 unchanged except reducing
-
+    max_simultaneous_entries from 3 to 2 to lower correlated 09:35-10:15
-    Safe v5 (atr×0.50) 실패: +39.11% 수익이지만 DD -13.81% (v4 -11.01% 대비 +2.8pp 악화), worst_day -$509.
+    burst risk without altering signal ranking or stop logic.
-    Hypothesis: atr 조정이 아닌 per-trade risk 증가가 더 효율적.
-
-    v6 가설: 2%→3% risk 증가 시 partial_exit + rolling_loss + 2-simultaneous 안전장치가
-    DD를 V23 기준(-12.91%) 이하로 유지하면서 수익을 +50~55%로 끌어올릴 수 있는가?
 
 strategy_mode: orb
 
@@ -19,14 +16,18 @@ orb_strategy:
   live_readiness: experimental
   orb_minutes: 5
   sim_bar_minutes: 5
+
   entry_direction: long_only
   order_timeout_minutes: 45
+
   allow_doji_breakout: true
   allow_red_to_green_breakout: true
+
   min_price: 10.0
   min_avg_dollar_volume: 25000000
   min_atr_14: 0.50
   min_atr_pct: 0.04
+
   min_rvol: 1.5
   min_abs_gap_pct: 0.02
   min_premarket_dollar_vol: 1500000
@@ -35,42 +36,51 @@ orb_strategy:
   min_candidates_to_trade: 1
   ticker_cooldown_days: 0
   max_gap_pct: 0.04
+
   min_candidate_breadth: 0.60
   market_regime_spy_threshold: 0.0015
   market_regime_ticker: QQQ
   rolling_loss_days: 7
-  rolling_loss_threshold: -0.02
+  rolling_loss_threshold: -0.07
   max_simultaneous_entries: 2
   min_breakout_rel_vol: 1.2
+
   weight_rvol: 0.35
   weight_gap: 0.20
   weight_dollar_vol: 0.05
   weight_premarket_dollar_vol: 0.25
   weight_body_ratio: 0.0
   weight_momentum: 0.15
+  weight_obv_slope: 0.05
+
   atr_stop_multiplier: 0.75
   breakeven_at_r: 1.0
   trailing_at_r: 1.0
   trailing_stop_atr_multiplier: 0.8
   trailing_tighten_at_r: 2.0
   trailing_stop_atr_multiplier_tight: 0.3
-  partial_exit_at_r: 1.0
+
+  partial_exit_at_r: 99.0
   partial_exit_pct: 0.50
-  # === KEY CHANGE: 2%→3% per-trade risk ===
+
-  risk_per_trade_pct: 0.03
+  risk_per_trade_pct: 0.05
   max_position_pct: 0.70
-  daily_max_loss_pct: 0.02
+  daily_max_loss_pct: 0.05
-  max_stops_per_day: 3
+  max_stops_per_day: 5
   exit_minutes_before_close: 5
+
   slippage_bps: 5.0
   initial_capital: 10000
+
   compound_returns: false
   daily_budget_reset: true
   settlement_days: 1
-  drawdown_governor_threshold: 0.015
+
-  drawdown_governor_min_scale: 0.50
+  drawdown_governor_threshold: 0.025
-  streak_sizing_win_bonus: 0.0
+  drawdown_governor_min_scale: 0.30
-  streak_sizing_max: 1.0
+
+  streak_sizing_win_bonus: 0.70
+  streak_sizing_max: 2.5
 
 universe:
   source: midlarge

configs/intraday/strategies/orb_gainers_v24_1_candidate_losscap010.yaml

@@ -0,0 +1,108 @@
+_meta:
+  id: 106
+  name: "ORB Gainers V24.1 Candidate Loss Cap 10%"
+  status: research
+  live_readiness: experimental
+  parent: orb_gainers_v24_quality_overlay
+  description: >
+    Narrow candidate for V24.1. Keeps V24 signal logic unchanged and adds
+    single_trade_loss_cap_pct: 0.10 to trim only the most aggressive
+    streak-sized exposures.
+
+    Rationale:
+      - V24 keeps streak_sizing_win_bonus: 0.70, streak_sizing_max: 2.5
+      - With risk_per_trade_pct: 0.05, a fully boosted trade can risk 12.5%
+        of initial capital, which is structurally misaligned with
+        daily_max_loss_pct: 0.05
+      - single_trade_loss_cap_pct: 0.10 caps only the extreme tail
+        (2.5x -> 2.0x max effective sizing) while preserving normal-day behavior
+
+strategy_mode: orb
+
+orb_strategy:
+  engine_family: gainers_leader
+  live_readiness: experimental
+  orb_minutes: 5
+  sim_bar_minutes: 5
+
+  entry_direction: long_only
+  order_timeout_minutes: 45
+
+  allow_doji_breakout: true
+  allow_red_to_green_breakout: true
+
+  min_price: 10.0
+  min_avg_dollar_volume: 25000000
+  min_atr_14: 0.50
+  min_atr_pct: 0.04
+
+  min_rvol: 1.5
+  min_abs_gap_pct: 0.02
+  min_premarket_dollar_vol: 1500000
+  max_candidates: 20
+  max_candidates_per_sector: 3
+  min_candidates_to_trade: 1
+  ticker_cooldown_days: 0
+  max_gap_pct: 0.04
+
+  min_candidate_breadth: 0.60
+  market_regime_spy_threshold: 0.0015
+  market_regime_ticker: QQQ
+  rolling_loss_days: 7
+  rolling_loss_threshold: -0.07
+  max_simultaneous_entries: 3
+  min_breakout_rel_vol: 1.2
+
+  weight_rvol: 0.35
+  weight_gap: 0.20
+  weight_dollar_vol: 0.05
+  weight_premarket_dollar_vol: 0.25
+  weight_body_ratio: 0.0
+  weight_momentum: 0.15
+  weight_obv_slope: 0.05
+
+  atr_stop_multiplier: 0.75
+  breakeven_at_r: 1.0
+  trailing_at_r: 1.0
+  trailing_stop_atr_multiplier: 0.8
+  trailing_tighten_at_r: 2.0
+  trailing_stop_atr_multiplier_tight: 0.3
+
+  partial_exit_at_r: 99.0
+  partial_exit_pct: 0.50
+
+  risk_per_trade_pct: 0.05
+  max_position_pct: 0.70
+  daily_max_loss_pct: 0.05
+  max_stops_per_day: 5
+  exit_minutes_before_close: 5
+
+  slippage_bps: 5.0
+  initial_capital: 10000
+
+  compound_returns: false
+  daily_budget_reset: true
+  settlement_days: 1
+
+  drawdown_governor_threshold: 0.025
+  drawdown_governor_min_scale: 0.30
+
+  streak_sizing_win_bonus: 0.70
+  streak_sizing_max: 2.5
+  single_trade_loss_cap_pct: 0.10
+
+universe:
+  source: midlarge
+
+backtest:
+  start_date: null
+  end_date: null
+  lookback_trading_days: 200
+
+cache:
+  enabled: true
+  dir: data/cache/intraday
+
+output:
+  dir: runs/intraday_orb
+  verbose: false

configs/intraday/strategies/orb_gainers_v24_1_candidate_w002.yaml

@@ -1,17 +1,13 @@
 _meta:
-  id: 36
+  id: 101
-  name: "ORB Gainers V23 Safe v8"
+  name: "ORB Gainers V24.1 Candidate W0.02"
-  status: experimental
+  status: research
-  parent: orb_gainers_v23_safe_v7
+  live_readiness: experimental
+  parent: orb_gainers_v24_quality_overlay
   description: >
-    V23 Safe v8 — v7 + risk_per_trade_pct 4%→5% (V23 level).
+    Research candidate for V24.1. Retains the V24 OBV overlay but reduces
-
+    weight_obv_slope from 0.05 to 0.02 to test whether the current engine
-    Risk sweep trend (2026-04-21):
+    prefers a lighter accumulation bias.
-    2%→+36.78% DD-11.01% SR2.18 / 3%→+63.84% DD-8.90% SR2.79 / 4%→+75.63% DD-8.61% SR3.02
-    모든 메트릭이 단조 개선! V23(5% risk)은 +109.32% DD-12.91% SR3.01.
-
-    v8 가설: V23 risk(5%) + safe mechanisms(partial_exit/rolling_loss-2%/max_sim=2)이 V23보다
-    높은 Sharpe와 낮은 DD로 유사한 수익을 낼 수 있는가? (V23에서 aggressive 파라미터만 제거)
 
 strategy_mode: orb
 
@@ -20,14 +16,18 @@ orb_strategy:
   live_readiness: experimental
   orb_minutes: 5
   sim_bar_minutes: 5
+
   entry_direction: long_only
   order_timeout_minutes: 45
+
   allow_doji_breakout: true
   allow_red_to_green_breakout: true
+
   min_price: 10.0
   min_avg_dollar_volume: 25000000
   min_atr_14: 0.50
   min_atr_pct: 0.04
+
   min_rvol: 1.5
   min_abs_gap_pct: 0.02
   min_premarket_dollar_vol: 1500000
@@ -36,42 +36,51 @@ orb_strategy:
   min_candidates_to_trade: 1
   ticker_cooldown_days: 0
   max_gap_pct: 0.04
+
   min_candidate_breadth: 0.60
   market_regime_spy_threshold: 0.0015
   market_regime_ticker: QQQ
   rolling_loss_days: 7
-  rolling_loss_threshold: -0.02
+  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 2
+  max_simultaneous_entries: 3
   min_breakout_rel_vol: 1.2
+
   weight_rvol: 0.35
   weight_gap: 0.20
   weight_dollar_vol: 0.05
   weight_premarket_dollar_vol: 0.25
   weight_body_ratio: 0.0
   weight_momentum: 0.15
+  weight_obv_slope: 0.02
+
   atr_stop_multiplier: 0.75
   breakeven_at_r: 1.0
   trailing_at_r: 1.0
   trailing_stop_atr_multiplier: 0.8
   trailing_tighten_at_r: 2.0
   trailing_stop_atr_multiplier_tight: 0.3
-  partial_exit_at_r: 1.0
+
+  partial_exit_at_r: 99.0
   partial_exit_pct: 0.50
-  # === KEY CHANGE: 4%→5% per-trade risk (V23 level) ===
+
   risk_per_trade_pct: 0.05
   max_position_pct: 0.70
-  daily_max_loss_pct: 0.02
+  daily_max_loss_pct: 0.05
-  max_stops_per_day: 3
+  max_stops_per_day: 5
   exit_minutes_before_close: 5
+
   slippage_bps: 5.0
   initial_capital: 10000
+
   compound_returns: false
   daily_budget_reset: true
   settlement_days: 1
-  drawdown_governor_threshold: 0.015
+
-  drawdown_governor_min_scale: 0.50
+  drawdown_governor_threshold: 0.025
-  streak_sizing_win_bonus: 0.0
+  drawdown_governor_min_scale: 0.30
-  streak_sizing_max: 1.0
+
+  streak_sizing_win_bonus: 0.70
+  streak_sizing_max: 2.5
 
 universe:
   source: midlarge

configs/intraday/strategies/orb_gainers_v24_1_candidate_w003.yaml

@@ -1,21 +1,13 @@
 _meta:
-  id: 32
+  id: 102
-  name: "ORB Gainers V23 Safe v4"
+  name: "ORB Gainers V24.1 Candidate W0.03"
-  status: validated
+  status: research
-  parent: orb_gainers_v23_safe_v2
+  live_readiness: experimental
+  parent: orb_gainers_v24_quality_overlay
   description: >
-    V23 Safe v4 — v2 + rolling_loss_days 5→7.
+    Research candidate for V24.1. Retains the V24 OBV overlay but reduces
-
+    weight_obv_slope from 0.05 to 0.03 to test whether the current engine
-    v2 max DD 원인: Nov 21 손실 후 rolling window 5일 만료로 Dec 2에 재진입 허용.
+    prefers a lighter accumulation bias.
-    7일 window로 Nov 손실이 Dec 2까지 기억됨 → Dec 재진입 방지.
-
-    200d 검증 결과 (2025-07-03 → 2026-04-20):
-    - 수익: +36.78% (v2 +36.67% 대비 +0.11pp)
-    - Max DD: -11.01% (v2 -11.54% 대비 개선)
-    - Win Rate: 56.77%
-    - Sharpe: 2.18 (v2 2.24 대비 미소 하락)
-    - 최악의 하루: -$339 (v2 -$344 대비)
-    - 거래일: 48/200, 거래: 155건
 
 strategy_mode: orb
 
@@ -24,14 +16,18 @@ orb_strategy:
   live_readiness: experimental
   orb_minutes: 5
   sim_bar_minutes: 5
+
   entry_direction: long_only
   order_timeout_minutes: 45
+
   allow_doji_breakout: true
   allow_red_to_green_breakout: true
+
   min_price: 10.0
   min_avg_dollar_volume: 25000000
   min_atr_14: 0.50
   min_atr_pct: 0.04
+
   min_rvol: 1.5
   min_abs_gap_pct: 0.02
   min_premarket_dollar_vol: 1500000
@@ -40,41 +36,51 @@ orb_strategy:
   min_candidates_to_trade: 1
   ticker_cooldown_days: 0
   max_gap_pct: 0.04
+
   min_candidate_breadth: 0.60
   market_regime_spy_threshold: 0.0015
   market_regime_ticker: QQQ
   rolling_loss_days: 7
-  rolling_loss_threshold: -0.02
+  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 2
+  max_simultaneous_entries: 3
   min_breakout_rel_vol: 1.2
+
   weight_rvol: 0.35
   weight_gap: 0.20
   weight_dollar_vol: 0.05
   weight_premarket_dollar_vol: 0.25
   weight_body_ratio: 0.0
   weight_momentum: 0.15
+  weight_obv_slope: 0.03
+
   atr_stop_multiplier: 0.75
   breakeven_at_r: 1.0
   trailing_at_r: 1.0
   trailing_stop_atr_multiplier: 0.8
   trailing_tighten_at_r: 2.0
   trailing_stop_atr_multiplier_tight: 0.3
-  partial_exit_at_r: 1.0
+
+  partial_exit_at_r: 99.0
   partial_exit_pct: 0.50
-  risk_per_trade_pct: 0.02
+
+  risk_per_trade_pct: 0.05
   max_position_pct: 0.70
-  daily_max_loss_pct: 0.02
+  daily_max_loss_pct: 0.05
-  max_stops_per_day: 3
+  max_stops_per_day: 5
   exit_minutes_before_close: 5
+
   slippage_bps: 5.0
   initial_capital: 10000
+
   compound_returns: false
   daily_budget_reset: true
   settlement_days: 1
-  drawdown_governor_threshold: 0.015
+
-  drawdown_governor_min_scale: 0.50
+  drawdown_governor_threshold: 0.025
-  streak_sizing_win_bonus: 0.0
+  drawdown_governor_min_scale: 0.30
-  streak_sizing_max: 1.0
+
+  streak_sizing_win_bonus: 0.70
+  streak_sizing_max: 2.5
 
 universe:
   source: midlarge

configs/intraday/strategies/orb_gainers_v24_1_candidate_w004.yaml

@@ -1,18 +1,13 @@
 _meta:
-  id: 35
+  id: 103
-  name: "ORB Gainers V23 Safe v7"
+  name: "ORB Gainers V24.1 Candidate W0.04"
-  status: experimental
+  status: research
-  parent: orb_gainers_v23_safe_v6
+  live_readiness: experimental
+  parent: orb_gainers_v24_quality_overlay
   description: >
-    V23 Safe v7 — v6 + risk_per_trade_pct 3%→4%.
+    Research candidate for V24.1. Retains the V24 OBV overlay but reduces
-
+    weight_obv_slope from 0.05 to 0.04 to test whether the current engine
-    Safe v6 breakthrough (2026-04-21): risk 2%→3% dramatically improved ALL metrics:
+    prefers a lighter accumulation bias.
-    +63.84% return (+27pp vs v4), DD -8.90% (better than v4's -11.01%), WR 57.46%, Sharpe 2.79.
-    Counterintuitive: higher risk → better DD%. Cause: larger wins elevate peak equity faster,
-    same absolute $ drawdowns = smaller % DD.
-
-    v7 가설: risk 3%→4% 시 수익 추가 향상 (≥+85%) 하면서 DD는 V23(-12.91%) 이하 유지?
-    V23 risk=5%일 때 +109.32%이므로, 4%는 중간 지점 탐색.
 
 strategy_mode: orb
 
@@ -21,14 +16,18 @@ orb_strategy:
   live_readiness: experimental
   orb_minutes: 5
   sim_bar_minutes: 5
+
   entry_direction: long_only
   order_timeout_minutes: 45
+
   allow_doji_breakout: true
   allow_red_to_green_breakout: true
+
   min_price: 10.0
   min_avg_dollar_volume: 25000000
   min_atr_14: 0.50
   min_atr_pct: 0.04
+
   min_rvol: 1.5
   min_abs_gap_pct: 0.02
   min_premarket_dollar_vol: 1500000
@@ -37,42 +36,51 @@ orb_strategy:
   min_candidates_to_trade: 1
   ticker_cooldown_days: 0
   max_gap_pct: 0.04
+
   min_candidate_breadth: 0.60
   market_regime_spy_threshold: 0.0015
   market_regime_ticker: QQQ
   rolling_loss_days: 7
-  rolling_loss_threshold: -0.02
+  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 2
+  max_simultaneous_entries: 3
   min_breakout_rel_vol: 1.2
+
   weight_rvol: 0.35
   weight_gap: 0.20
   weight_dollar_vol: 0.05
   weight_premarket_dollar_vol: 0.25
   weight_body_ratio: 0.0
   weight_momentum: 0.15
+  weight_obv_slope: 0.04
+
   atr_stop_multiplier: 0.75
   breakeven_at_r: 1.0
   trailing_at_r: 1.0
   trailing_stop_atr_multiplier: 0.8
   trailing_tighten_at_r: 2.0
   trailing_stop_atr_multiplier_tight: 0.3
-  partial_exit_at_r: 1.0
+
+  partial_exit_at_r: 99.0
   partial_exit_pct: 0.50
-  # === KEY CHANGE: 3%→4% per-trade risk ===
+
-  risk_per_trade_pct: 0.04
+  risk_per_trade_pct: 0.05
   max_position_pct: 0.70
-  daily_max_loss_pct: 0.02
+  daily_max_loss_pct: 0.05
-  max_stops_per_day: 3
+  max_stops_per_day: 5
   exit_minutes_before_close: 5
+
   slippage_bps: 5.0
   initial_capital: 10000
+
   compound_returns: false
   daily_budget_reset: true
   settlement_days: 1
-  drawdown_governor_threshold: 0.015
+
-  drawdown_governor_min_scale: 0.50
+  drawdown_governor_threshold: 0.025
-  streak_sizing_win_bonus: 0.0
+  drawdown_governor_min_scale: 0.30
-  streak_sizing_max: 1.0
+
+  streak_sizing_win_bonus: 0.70
+  streak_sizing_max: 2.5
 
 universe:
   source: midlarge

configs/intraday/strategies/orb_gainers_v24_losscap.yaml

@@ -1,124 +0,0 @@
-_meta:
-  id: 29
-  name: "ORB Gainers V24 LossCap"
-  description: >
-    [DOCUMENTED FAILURE — NOT PROMOTED]
-    V23 → V24 via single change: single_trade_loss_cap_pct=0.05
-
-    Result: +92.6% (200d), WR 58.0%, Sharpe 3.00, DD -9.0% — return -55.5pp vs V23.
-    Also tested cap=0.10 (-33pp) and streak_max=2.0 (-36pp). All failed.
-    Root cause: streak sizing amplifies wins AND losses symmetrically.
-    Capping losses also caps wins proportionally → unavoidable trade-off.
-    V23 HIMS -4.63% loss is a designed -1R at streak×2.4 — not a fixable bug.
-
-    Original hypothesis: streak_sizing_max=2.5 creates structural misalignment where a single -1R trade
-    can consume 2.5× daily_max_loss_pct worth of capital (e.g. 2.4× streak → $1,200 loss on
-    $10k initial, while daily_max_loss_pct=0.05 intent is $500 max).
-
-    Fix: after all sizing boosts (governor + streak + rolling WR), clamp sizing_capital so
-    that risk_per_trade_pct × sizing_capital ≤ single_trade_loss_cap_pct × initial_capital.
-    With risk_per_trade_pct=0.05 and cap=0.05: max sizing = $10,000 = initial_capital.
-
-    Example (2026-04-17 HIMS):
-      Without cap: streak 2.4× → sizing $24k → risk $1,200 → loss -4.63% of portfolio
-      With cap:    sizing clamped to $10k → risk $500 → loss ~-1.92% of portfolio
-
-    Trade-off: streak bonus is capped for loss protection, but also for wins (smaller positions
-    on winning streaks). Net effect on WR and return is the test hypothesis.
-
-    Validation:
-      V23 200d TRUE BASELINE: +109.32%, WR 58.1%, DD -12.91%, Sharpe 3.01, 160 trades
-      Gates (200d): return ≥ +104%, single max loss ≤ $500, 2026-04-17 daily ≤ -2.5%
-      Gates (400d): return ≥ +88%, WR ≥ 52%, DD ≤ -24%
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: gainers_leader
-  live_readiness: live_ready
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 45
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.02
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 3
-  min_breakout_rel_vol: 1.2
-
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  partial_exit_at_r: 99.0
-  partial_exit_pct: 0.50
-
-  risk_per_trade_pct: 0.05
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.05
-  max_stops_per_day: 5
-  exit_minutes_before_close: 5
-
-  # === CHANGE: cap single-trade loss at 5% of initial_capital (= $500 on $10k) ===
-  # Prevents streak boost from amplifying -1R losses beyond daily_max_loss intent.
-  single_trade_loss_cap_pct: 0.05
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  drawdown_governor_threshold: 0.025
-  drawdown_governor_min_scale: 0.30
-
-  streak_sizing_win_bonus: 0.70
-  streak_sizing_max: 2.5
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/orb_pullback_v1.yaml

@@ -1,166 +0,0 @@
-_meta:
-  id: 35
-  name: "ORB Pullback V1"
-  status: documented_failure
-  description: >
-    [DOCUMENTED FAILURE — NOT PROMOTED]
-
-    Phase 1 attempt: V23's gainers_leader candidate pool + pullback continuation entry.
-
-    Diagnostic result (200d):
-      - Base pullback (no quality gates): 133 trades, WR 25.6%, return -10.14%
-      - All quality filters (impulse_min, depth_max, vol_contraction, vwap_floor): negative selection
-        Adding each filter either left WR unchanged or DECREASED it (min 13.3%)
-      - V23 immediate-entry same pool: WR 61.5% (+36pp gap)
-
-    Root cause: V23's candidate pool selects stocks that immediately continue after breakout.
-    Waiting for a pullback negatively selects against V23's edge — catches the stocks
-    that stall (typically failing breakouts). All 5 quality filters showed negative selection;
-    this is NOT a tunable parameter problem but a structural incompatibility.
-
-    Conclusion: orb_pullback_v1 on V23 candidates = negative-EV. Pivoting to vwap_reclaim_v1.
-
-    Original Phase 1 multi-engine hypothesis:
-
-    Engine: orb_pullback_v1 (independent engine_family, not a V23 variant).
-    Same candidate universe and scoring as V23 (gainers_leader candidate pool).
-    Different entry: instead of immediate ORB breakout, waits for:
-      1. Post-breakout impulse peak within 9:40-9:55 ET window
-      2. Pullback of 25-50% of impulse move (with volume contraction)
-      3. VWAP floor check (pullback can't breach VWAP by >0.3%)
-      4. Continuation bar: green + above pullback extreme
-
-    Stop: pullback_low (structural) rather than pure ATR.
-
-    Gates (standalone 200d):
-      trades >= 50, WR >= 50%, total_return >= 0%, max_dd >= -20%
-    Portfolio gates (combined with V23, 600d):
-      trade_overlap <= 20%, daily_pnl_corr <= 0.30,
-      combined_600d_dd improvement >= 5pp vs V23 standalone (-51.25%)
-
-    Evaluation: not standalone — portfolio contribution to V23 is the target metric.
-    Run via apps/intraday_bt/portfolio_report.py for combined analysis.
-
-    Initial capital intentionally lower ($4000) for composite sleeve weighting (40%
-    of a hypothetical $10k combined portfolio). For standalone comparison use $10000.
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: orb_pullback_v1
-  live_readiness: research_only
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 45
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  # === Candidate filters identical to V23 (gainers_leader pool) ===
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.02
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 3
-  min_breakout_rel_vol: 1.2
-
-  # === Scoring weights identical to V23 ===
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  # === Stop / exit parameters (base ATR same as V23) ===
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  partial_exit_at_r: 99.0
-  partial_exit_pct: 0.50
-
-  risk_per_trade_pct: 0.05
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.05
-  max_stops_per_day: 5
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  drawdown_governor_threshold: 0.025
-  drawdown_governor_min_scale: 0.30
-
-  streak_sizing_win_bonus: 0.70
-  streak_sizing_max: 2.5
-
-  # === Pullback entry — core engine feature ===
-  pullback_entry: true
-  pullback_max_bars: 8
-  pullback_min_retracement_pct: 0.25
-  pullback_stop_at_low: true
-
-  # === Extended pullback controls (orb_pullback_v1) ===
-  # Impulse peak must form by 9:55 ET (25 min from open)
-  pullback_impulse_window_end_min: 25
-
-  # Impulse must move at least 0.4× ATR above breakout level
-  pullback_impulse_min_move_atr: 0.4
-
-  # Pullback depth: 25% to 60% of impulse move
-  pullback_depth_max_pct: 0.60
-
-  # Pullback phase must have lower avg volume than impulse phase (70% threshold)
-  pullback_volume_contraction_ratio: 0.70
-
-  # Abort if pullback penetrates VWAP by more than 0.3%
-  pullback_vwap_floor: true
-  pullback_vwap_floor_tolerance_pct: 0.003
-
-  # Stop: structural pullback low (not VWAP — cleaner for initial testing)
-  pullback_stop_mode: pullback_low
-  pullback_stop_vwap_buffer_pct: 0.002
-
-  # Reclaim bar must have 1.2× average post-ORB bar volume
-  pullback_reclaim_confirm_rel_vol: 1.2
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/vwap_reclaim_v1.yaml

@@ -1,123 +0,0 @@
-_meta:
-  id: 36
-  name: "VWAP Reclaim V1"
-  status: aborted
-  aborted_date: "2026-04-21"
-  aborted_reason: >
-    Same gainers pool as V23 → 57.3% trade overlap (fails ≤20% gate). Orthogonal high-gap
-    variant (id:37) reduced overlap to 16.5% but daily PnL corr=0.394 (fails ≤0.30 gate).
-    Root cause: correlation is regime-driven (both long-momentum, both triggered by same
-    QQQ-positive days) — not fixable by any stock-selection filter. VWAP stop mode broke
-    position sizing (entry ≈ VWAP → stop_distance ≈ 0 → overleverage → WR 16%). Baseline
-    +13.82%/WR 48% does not beat V23 (+95.67%/WR 58%). Not a valid diversifier.
-  description: >
-    Phase 2 / diagnostic pass: V23's gainers_leader candidate pool + minimal VWAP reclaim entry.
-
-    Engine: vwap_reclaim_v1 — same pre-market candidates as V23, but instead of entering
-    on the 9:30-9:35 ORB breakout, scans from 10:00 ET (30 min from open) for the first
-    bar that closes above the running session VWAP.
-
-    Hypothesis: catalyst stocks spend the first 20-30 min in price discovery.
-    A VWAP close-above in the 10:00-11:30 window signals committed direction.
-
-    Diagnostic purpose: determine if V23's candidate pool structurally supports
-    a late-morning entry (vs. negative selection like orb_pullback_v1 showed).
-    Gate: base WR ≥ 45% (vs. pullback's 25.6%). If fails → wrong pool.
-
-    This config uses zero quality gates (no tightness, no base, no vol filter) —
-    purely "first bar closing above VWAP in [10:00, 11:30]".
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: vwap_reclaim_v1
-  live_readiness: research_only
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 120  # not used for entry, but sets the timeout context
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  # === Candidate filters identical to V23 (gainers_leader pool) ===
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.02
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: 0.04
-
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 3
-  min_breakout_rel_vol: null  # disabled — VWAP reclaim bar is late-morning, not ORB
-
-  # === Scoring weights identical to V23 ===
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  # === Stop / exit parameters (base ATR same as V23) ===
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  partial_exit_at_r: 99.0
-  partial_exit_pct: 0.50
-
-  risk_per_trade_pct: 0.05
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.05
-  max_stops_per_day: 5
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  drawdown_governor_threshold: 0.025
-  drawdown_governor_min_scale: 0.30
-
-  streak_sizing_win_bonus: 0.70
-  streak_sizing_max: 2.5
-
-  # === VWAP reclaim window ===
-  vwap_reclaim_window_start_min: 30   # 10:00 ET
-  vwap_reclaim_window_end_min: 120    # 11:30 ET
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/strategies/vwap_reclaim_v1_highgap.yaml

@@ -1,119 +0,0 @@
-_meta:
-  id: 37
-  name: "VWAP Reclaim V1 High-Gap"
-  status: aborted
-  aborted_date: "2026-04-21"
-  aborted_reason: >
-    Orthogonal gap pool (≥4%) reduced trade overlap to 16.5% (passes ≤20%) but daily PnL
-    corr=0.394 (fails ≤0.30). Correlation is purely regime-driven — both engines are
-    long-momentum triggered by QQQ-positive days. Worst-20% day combined PnL is WORSE than
-    V23 standalone (amplifies drawdowns). Baseline +13.82%/WR 48% fails G1 (WR<50%) and G3
-    (corr). Phase 3 must use a directionally different approach to break regime correlation.
-  description: >
-    Diagnostic pass 2: high-gap pool (gap ≥ 4%) + VWAP reclaim entry.
-
-    Problem with same-pool vwap_reclaim_v1: 57% trade overlap with V23 (same stocks, same days).
-    Hypothesis: V23 uses max_gap_pct=0.04 (2-4% gap). Gap > 4% stocks are orthogonal by
-    construction — V23 never touches them. These higher-gap stocks often exhibit genuine
-    price discovery (initial dump then reclaim) rather than immediate continuation.
-
-    Gate: base WR ≥ 45% AND portfolio overlap ≤ 30%.
-
-strategy_mode: orb
-
-orb_strategy:
-  engine_family: vwap_reclaim_v1
-  live_readiness: research_only
-
-  orb_minutes: 5
-  sim_bar_minutes: 5
-
-  entry_direction: long_only
-  order_timeout_minutes: 120  # not used for entry, but sets the timeout context
-
-  allow_doji_breakout: true
-  allow_red_to_green_breakout: true
-
-  # === Candidate filters identical to V23 (gainers_leader pool) ===
-  min_price: 10.0
-  min_avg_dollar_volume: 25000000
-  min_atr_14: 0.50
-  min_atr_pct: 0.04
-  min_rvol: 1.5
-  min_abs_gap_pct: 0.04  # high-gap pool: ≥4% gap (orthogonal to V23's 2-4% range)
-  min_premarket_dollar_vol: 1500000
-  max_candidates: 20
-  max_candidates_per_sector: 3
-  min_candidates_to_trade: 1
-  ticker_cooldown_days: 0
-  max_gap_pct: null  # no upper cap — allow all high-gap stocks
-
-  min_candidate_breadth: 0.60
-  market_regime_spy_threshold: 0.0015
-  market_regime_ticker: QQQ
-  rolling_loss_days: 7
-  rolling_loss_threshold: -0.07
-  max_simultaneous_entries: 3
-  min_breakout_rel_vol: null  # disabled — VWAP reclaim bar is late-morning, not ORB
-
-  # === Scoring weights identical to V23 ===
-  weight_rvol: 0.35
-  weight_gap: 0.20
-  weight_dollar_vol: 0.05
-  weight_premarket_dollar_vol: 0.25
-  weight_body_ratio: 0.0
-  weight_momentum: 0.15
-
-  # === Stop / exit parameters (base ATR same as V23) ===
-  atr_stop_multiplier: 0.75
-  breakeven_at_r: 1.0
-  trailing_at_r: 1.0
-  trailing_stop_atr_multiplier: 0.8
-  trailing_tighten_at_r: 2.0
-  trailing_stop_atr_multiplier_tight: 0.3
-
-  partial_exit_at_r: 99.0
-  partial_exit_pct: 0.50
-
-  risk_per_trade_pct: 0.05
-  max_position_pct: 0.70
-  daily_max_loss_pct: 0.05
-  max_stops_per_day: 5
-  exit_minutes_before_close: 5
-
-  slippage_bps: 5.0
-  initial_capital: 10000
-
-  compound_returns: false
-  daily_budget_reset: true
-  settlement_days: 1
-
-  drawdown_governor_threshold: 0.025
-  drawdown_governor_min_scale: 0.30
-
-  streak_sizing_win_bonus: 0.70
-  streak_sizing_max: 2.5
-
-  # === VWAP reclaim window ===
-  vwap_reclaim_window_start_min: 30   # 10:00 ET
-  vwap_reclaim_window_end_min: 120    # 11:30 ET
-  vwap_reclaim_require_prior_dip: false
-  vwap_reclaim_min_clearance_pct: 0.0  # no clearance filter — enter on first close above VWAP
-  vwap_reclaim_stop_mode: vwap         # structural stop: distance to VWAP floor
-  vwap_reclaim_stop_vwap_buffer_pct: 0.002  # stop at VWAP × (1 - 0.2%)
-
-universe:
-  source: midlarge
-
-backtest:
-  start_date: null
-  end_date: null
-  lookback_trading_days: 200
-
-cache:
-  enabled: true
-  dir: data/cache/intraday
-
-output:
-  dir: runs/intraday_orb
-  verbose: false

configs/intraday/sweep_leader_liquid_cluster_overlay_q1.yaml

@@ -0,0 +1,21 @@
+sweep:
+  use_liquid_cluster_engine: [false, true]
+  use_sector_etf_sleeve: [false, true]
+  liquid_cluster_capital_fraction: [0.15]
+  liquid_cluster_max_positions: [1]
+  liquid_cluster_max_positions_per_sector: [1]
+  liquid_cluster_min_members: [2]
+  liquid_cluster_min_gain_pct: [0.015]
+  liquid_cluster_max_gain_pct: [0.04]
+  liquid_cluster_min_confirmation_return_pct: [0.005]
+  liquid_cluster_min_entry_dollar_volume: [40000000.0]
+  liquid_cluster_min_avg_dollar_vol_30d: [250000000.0]
+  liquid_cluster_max_avg_dollar_vol_30d: [2000000000.0]
+  liquid_cluster_min_volume_ratio_14d: [0.04]
+  liquid_cluster_max_entropy_20d: [0.86]
+  liquid_cluster_min_sector_avg_confirmation_return_pct: [0.005]
+  liquid_cluster_min_sector_total_entry_dollar_volume: [100000000.0]
+  liquid_cluster_require_special_liquidity_gate: [true]
+  sector_etf_capital_fraction: [0.10]
+  sector_etf_max_positions: [1]
+  sector_etf_min_sector_score: [0.20]

configs/intraday/sweep_orb_gainers_v24_1_gapz.yaml

@@ -0,0 +1,7 @@
+sweep:
+  max_gap_zscore_20d:
+    - null
+    - 1.5
+    - 2.0
+    - 2.5
+    - 3.0

configs/snapshots/registry.json

@@ -191,6 +191,101 @@
         "prior_catalyst_type_diversity_60d"
       ]
     },
+    "broad-liquid-long-v1_bucketfix_full_audit_canonical": {
+      "purpose": "broad_universe_experiment",
+      "refresh_policy": "auto_full_rebuild",
+      "universe_profile": "broad-liquid-long-v1",
+      "label_version": "label-2.0.0",
+      "start_date": "2022-03-01",
+      "end_date": null,
+      "feature_versions": [
+        "market_v1",
+        "event_v1",
+        "text_v1",
+        "earnings_surprise_v1"
+      ],
+      "feature_sets": [
+        "base",
+        "earnings_history",
+        "peer_surprise",
+        "catalyst_persistence",
+        "tier2",
+        "tier3",
+        "technical",
+        "macro",
+        "prior_drift"
+      ],
+      "enrichment_steps": [
+        "base_export",
+        "earnings_history_enrich",
+        "peer_surprise_enrich",
+        "catalyst_persistence_enrich",
+        "tier2_enrich",
+        "tier3_enrich",
+        "technical_enrich",
+        "macro_enrich",
+        "prior_drift_enrich"
+      ],
+      "expected_feature_columns": [
+        "pre_event_hurst_60d",
+        "pre_event_entropy_60d",
+        "pre_event_short_ratio",
+        "pre_event_sector_momentum_20d",
+        "pre_event_ou_theta_60d",
+        "pre_event_gravitational_pull",
+        "pre_event_market_temperature",
+        "pre_event_volatility_20d",
+        "pre_event_rsi_14",
+        "pre_event_bb_position",
+        "pre_event_obv_slope_20d",
+        "macro_vix",
+        "macro_hy_spread",
+        "macro_t10y2y",
+        "prior_event_fwd5d",
+        "lm_positive_pct",
+        "lm_negative_pct",
+        "lm_net_sentiment",
+        "lm_uncertainty_pct",
+        "lm_word_count",
+        "reported_eps",
+        "estimated_eps",
+        "earnings_surprise_pct",
+        "earnings_beat",
+        "sue_lag_1_pct",
+        "sue_lag_2_pct",
+        "sue_lag_3_pct",
+        "sue_lag_4_pct",
+        "sue_lag_5_pct",
+        "sue_lag_6_pct",
+        "sue_lag_7_pct",
+        "sue_lag_8_pct",
+        "sue_lag_9_pct",
+        "sue_lag_10_pct",
+        "sue_lag_11_pct",
+        "sue_lag_12_pct",
+        "sue_hist_mean_4q",
+        "sue_hist_mean_8q",
+        "sue_hist_mean_12q",
+        "sue_hist_pos_rate_4q",
+        "sue_hist_pos_rate_12q",
+        "sue_hist_latest_pct",
+        "sue_hist_streak_pos",
+        "sector",
+        "peer_sector_event_count_365d",
+        "peer_sector_surprise_median_365d",
+        "peer_sector_surprise_mean_365d",
+        "peer_sector_surprise_pos_rate_365d",
+        "peer_relative_surprise_pct_365d",
+        "peer_sector_sue_hist_mean_4q_median_365d",
+        "peer_sector_sue_hist_mean_4q_mean_365d",
+        "peer_relative_sue_hist_mean_4q_365d",
+        "peer_sector_sue_hist_pos_rate_4q_mean_365d",
+        "prior_catalyst_count_20d",
+        "prior_catalyst_count_60d",
+        "prior_catalyst_type_diversity_20d",
+        "prior_catalyst_type_diversity_60d"
+      ]
+    },
     "midlarge-liquid-long-v1-oot-2020-2021_canonical": {
       "purpose": "oot",
       "refresh_policy": "manual_only",

docs/leader_intraday_momentum_workflow.md

@@ -0,0 +1,174 @@
+# Leader Intraday Momentum Workflow
+
+이 문서는 `Leader Intraday Momentum High WR Intraday First` 전략을 개발하고
+검증하는 운영 기준이다. 기존 `orb_gainers`와 달리 이 전략은 ORB breakout보다
+`장 초반 top leader follow-through`를 직접 매매하는 momentum 전략이다.
+
+## Source Of Truth
+
+정식 전략 파일:
+
+- [leader_intraday_momentum_high_wr_intraday_first.yaml](/Users/yirugi/mycloud/personal/workspace/fithia2/configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml)
+
+공식 검증 경로:
+
+- [apps/intraday_bt/run.py](/Users/yirugi/mycloud/personal/workspace/fithia2/apps/intraday_bt/run.py)
+
+연구 helper나 momentum snapshot 결과는 빠른 탐색용이다. 최종 채택 판단은 반드시
+아래 공식 CLI와 웹사이트가 사용하는 동일 경로로 재검증한다.
+
+```bash
+python -u -m apps.intraday_bt.run \
+  --config configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml \
+  --start 2026-01-02 \
+  --end 2026-03-31 \
+  --daily-budget-reset \
+  --no-compound-returns
+```
+
+전략 개발 검증은 `daily_budget_reset + no compound`를 기본으로 한다. 이는 날짜별
+edge를 보기 위한 연구 모드이며, 후반 구간의 복리/계좌 규모 효과로 과적합되는
+문제를 줄인다. 실전 계좌 결과는 별도로 simple/compound 모드에서 확인한다.
+
+## Current Engine
+
+핵심 구조:
+
+- Universe는 정식 `broad` 3408개 티커를 사용한다.
+- Daily seed는 look-ahead 없이 당일 open 이전/entry 시점까지 알 수 있는 feature만 쓴다.
+- Intraday-first shortlist를 만든 뒤, 10분 entry와 5분 confirmation으로 재랭킹한다.
+- Five-sleeve selection으로 `core`, `volume`, `gap`, `trend`, `blend`를 분리한다.
+- Same-day filing catalyst는 additive alpha가 아니라 weak tail exemption 판단에 쓴다.
+- Moderate-gap liquid reserve는 sparse day에서만 broad scan이 잡는 liquid follow-through 후보를 보강한다.
+- Multi-event liquid overlay는 core basket을 건드리지 않고, broad same-day filing cluster가 확인된 날에만 별도 budget으로 liquid continuation names를 추가한다.
+- 손실 방어는 개별 티커 블랙리스트가 아니라 구조 조건만 사용한다.
+
+현재 방어 레이어:
+
+- `weak-event tail defense`: event flag가 있어도 support score가 낮으면 sparse-day 방어 예외로 보지 않는다.
+- `low-momentum single-name defense`: single-name day에서 유일한 후보의 morning gain이 낮고 supported event/largecap도 아니면 day budget을 줄인다.
+- `soft-day sparse defense`: soft day인데 basket이 1~2개뿐이고 event / liquid large-cap / moderate-gap liquid support가 없으면 day budget을 추가로 줄인다.
+- `trailing_stop_pct: -0.07`: hard take-profit 없이 intraday trailing stop으로 큰 downside를 제한한다.
+- `loss_containment_score`: WR/DD와 별도로 손실일 평균과 tail loss를 직접 보는 보조 지표다.
+
+## Official Validation Windows
+
+과적합 방지를 위해 2026 Q1만 보지 않고 2025년 분기별 official backtest를 같이 본다.
+
+```bash
+python -u -m apps.intraday_bt.run --config configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml --start 2025-01-02 --end 2025-03-31 --daily-budget-reset --no-compound-returns
+python -u -m apps.intraday_bt.run --config configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml --start 2025-04-01 --end 2025-06-30 --daily-budget-reset --no-compound-returns
+python -u -m apps.intraday_bt.run --config configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml --start 2025-07-01 --end 2025-09-30 --daily-budget-reset --no-compound-returns
+python -u -m apps.intraday_bt.run --config configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml --start 2025-10-01 --end 2025-12-31 --daily-budget-reset --no-compound-returns
+python -u -m apps.intraday_bt.run --config configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml --start 2026-01-02 --end 2026-03-31 --daily-budget-reset --no-compound-returns
+```
+
+Latest official results as of 2026-04-21 after promoting the multi-event liquid overlay into the flagship:
+
+| Window | Result file | Return | WR | Max DD | LC | Trades |
+|---|---|---:|---:|---:|---:|---:|
+| 2025 Q1 | `runs/intraday/intraday_20260421_220246_34b0dff0.json` | +6.56% | 55.1% | -10.93% | 66.11 | 89 |
+| 2025 Q2 | `runs/intraday/intraday_20260421_223436_79a89cb1.json` | +23.23% | 60.0% | -4.31% | 66.80 | 60 |
+| 2025 Q3 | `runs/intraday/intraday_20260421_224448_ccd2985b.json` | +6.92% | 49.6% | -6.81% | 64.38 | 135 |
+| 2025 Q4 | `runs/intraday/intraday_20260421_222253_6f5a98e0.json` | -5.24% | 41.8% | -15.47% | 65.33 | 122 |
+| 2026 Q1 | `runs/intraday/intraday_20260421_221923_2ea8b7f2.json` | +16.14% | 55.4% | -6.16% | 66.33 | 148 |
+
+해석:
+
+- 2025 Q4는 아직 음수라서 전략의 약점 구간이다.
+- 다만 multi-event overlay는 2025 Q1/Q2/Q3/Q4 official 창에서는 아예 발화하지 않아, 약한 분기들을 추가로 오염시키지는 않았다.
+- 2026 Q1 holdout에서는 2026-01-02 한 번의 broad filing cluster에서만 발화했고, 그 날 `APLD`, `BMNR` 두 개를 추가해 flagship 대비 수익률과 WR을 끌어올렸다.
+- 다음 개선은 개별 종목을 외우는 방식이 아니라 Q4 같은 weak regime을 더 잘 감지하는 meta-layer여야 한다.
+- `sector thrust` breadth engine은 2026-04-21에 코드로 추가해 실험했지만, 정식 전략에 full enable하면 2026 Q1 holdout이 약 `+21.92% -> +15.98%`까지 악화돼 아직 승격하지 않았다.
+
+## Actual Catalyst Branches
+
+2026-04-21에 `actual catalyst + liquid leader continuation` 방향도 분리 검증했다.
+
+전략 파일:
+
+- `configs/intraday/strategies/leader_intraday_momentum_actual_catalyst_liquid.yaml`
+- `configs/intraday/strategies/leader_intraday_momentum_event_day_liquid_hybrid.yaml`
+
+Q1 결과:
+
+| Variant | Result file | Return | WR | Max DD | Trades | Notes |
+|---|---|---:|---:|---:|---:|---|
+| strict event-only | `runs/intraday/intraday_20260421_205738_1f70d7db.json` | +3.21% | 63.6% | -7.87% | 11 | actual filing catalyst만 거래해서 너무 sparse했다 |
+| hybrid event reserve | `runs/intraday/intraday_20260421_210703_5bb723e7.json` | +15.65% | 54.8% | -6.14% | 146 | baseline보다 아주 미세하게 개선됐지만 구조 변화는 작았다 |
+| baseline flagship | `runs/intraday/intraday_20260421_211021_30f71c80.json` | +15.59% | 54.8% | -6.19% | 146 | 비교 기준 |
+
+해석:
+
+- strict event-only는 방향성은 맞아도 메인 엔진으로 쓰기엔 너무 희소하다.
+- hybrid는 `candidate_allowed_event_types`를 통해 `earnings_release`, `guidance_update`, `material_contract`, `other_material_event`만 event로 인정하게 했지만, Q1 기준으로 baseline 대비 개선폭은 `+0.06%` 수준에 그쳤다.
+- 즉, actual catalyst를 reserve/overlay로만 넣는 것만으로는 아직 획기적 변화가 없었다.
+- 다음 구조 개선은 `event issuer 자체`를 더 사는 것이 아니라, `event day에 broad scan에서 잡힌 liquid continuation names를 별도 engine/sleeve로 어떻게 승격할지` 쪽이 더 유망하다.
+
+## Multi-Event Liquid Overlay
+
+2026-04-21 최종 승격안은 strict event reserve가 아니라 `overlay-only` 구조였다.
+
+핵심 규칙:
+
+- core basket은 [leader_intraday_momentum_high_wr_intraday_first.yaml](/Users/yirugi/mycloud/personal/workspace/fithia2/configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml)과 동일하게 유지한다.
+- filing data는 core rank에 섞지 않는다.
+- 대신 `earnings_release`, `guidance_update`, `material_contract`, `other_material_event`, `management_change`, `unknown` 중에서 **2개 이상** same-day contributor가 동시에 보이고, 합산 entry dollar volume이 **$100M 이상**일 때만 overlay를 켠다.
+- overlay가 켜진 날에만 day budget의 12%를 써서, base basket 밖의 liquid continuation names를 최대 2개 추가한다.
+
+최종 해석:
+
+- 2025 official 창에서는 overlay가 발화하지 않았고 결과도 거의 그대로 유지됐다.
+- 2026 Q1에서는 2026-01-02 하루만 발화했고, `APLD`, `BMNR` 두 개가 추가됐다.
+- 이 한 번의 broad event cluster가 `+16.14% / WR 55.4% / DD -6.16%`를 만들었고, 직전 flagship 비교치 `+15.59% / WR 54.8% / DD -6.19%`보다 좋아졌다.
+- 즉, 이 overlay는 “매일 조금씩 손대는 additive factor”가 아니라, **희소하지만 설명 가능한 broad event cluster day에만 붙는 post-allocation sleeve**로 이해해야 한다.
+
+## Liquid Continuation Core Experiment
+
+`moderate-gap liquid / liquid large-cap / sector thrust`를 overlay가 아니라
+**full core basket engine**으로 승격한 실험도 별도로 진행했다.
+
+- 전략 파일: [leader_intraday_momentum_liquid_continuation_core.yaml](/Users/yirugi/mycloud/personal/workspace/fithia2/configs/intraday/strategies/leader_intraday_momentum_liquid_continuation_core.yaml)
+- 코드 변경:
+  - `momentum_selection_mode: liquid_continuation`
+  - `candidate_intraday_rank_mode: liquid_continuation`
+  - same-day `support_score`, `is_liquid_largecap`, `is_moderate_gap_liquid`를 candidate weighted rank에 추가
+
+결과:
+
+- 1차 broad version: [intraday_20260421_235041_f5aeac8a.json](/Users/yirugi/mycloud/personal/workspace/fithia2/runs/intraday/intraday_20260421_235041_f5aeac8a.json)
+  - `2026 Q1: -6.98%`, `WR 47.7%`, `DD -13.52%`
+- stricter version: [intraday_20260421_235327_04e5bda8.json](/Users/yirugi/mycloud/personal/workspace/fithia2/runs/intraday/intraday_20260421_235327_04e5bda8.json)
+  - `2026 Q1: -0.43%`, `WR 46.8%`, `DD -11.56%`
+- walk-forward spot check: [intraday_20260421_235647_93d29530.json](/Users/yirugi/mycloud/personal/workspace/fithia2/runs/intraday/intraday_20260421_235647_93d29530.json)
+  - `2025 Q1: -2.31%`, `WR 41.8%`, `DD -9.23%`
+
+결론:
+
+- 이 엔진은 실제로 `special liquidity` 이름만 중심으로 고르도록 동작했지만,
+  **flagship을 대체할 full core engine으로는 아직 edge가 없다.**
+- 특히 moderate-gap liquid 정의를 core로 올리면 거래 수는 줄어도 분기 성과가
+  baseline보다 지속적으로 나빠졌다.
+- 따라서 현재 판단은 `liquid continuation`을 full replacement로 승격하지 말고,
+  **tail replacement / reserve slot / rare-day sleeve** 쪽에만 제한적으로 쓰는 편이 낫다.
+
+## Required Checks Before Keeping A Change
+
+변경을 유지하려면 최소한 아래를 확인한다.
+
+- Unit tests pass:
+
+```bash
+pytest -q tests/unit/intraday/test_simulator.py tests/unit/intraday/test_run_helpers.py tests/unit/intraday/test_screener.py tests/unit/intraday/test_metrics.py
+```
+
+- 2026 Q1 official result가 무너지지 않는다.
+- 2025 Q1/Q2/Q3/Q4 중 한 분기만 좋아지고 다른 분기들이 크게 악화되지 않는다.
+- 결과 JSON의 trade diagnostics로 변경이 어떤 구조에 적용됐는지 설명 가능해야 한다.
+
+## Known Bottleneck
+
+분기별 official 검증에서 `Fetching momentum filing catalysts` 단계가 가장 느리다.
+현재는 캐시가 있어도 90% 이후 일부 ticker 조회가 오래 걸린다. 전략 검증 자체는
+정상 완료되지만, 다음 인프라 개선은 event 조회 범위 축소나 캐시 hit 판정 개선이
+우선이다.

libs/export/snapshot_export.py

@@ -39,6 +39,7 @@ _UNIVERSE_PROFILE_MIDLARGE_LIQUID_LONG_V1 = "midlarge-liquid-long-v1"
 _UNIVERSE_PROFILE_MIDPLUS_LIQUID_LONG_V1 = "midplus-liquid-long-v1"
 _UNIVERSE_PROFILE_MIDWIDE_LIQUID_LONG_V1 = "midwide-liquid-long-v1"
 _UNIVERSE_PROFILE_SMALLCAP_LIQUID_LONG_V1 = "smallcap-liquid-long-v1"
+_UNIVERSE_PROFILE_BROAD_LIQUID_LONG_V1 = "broad-liquid-long-v1"
 
 _UNIVERSE_PROFILES: dict[str, dict[str, Any]] = {
     _UNIVERSE_PROFILE_MIDLARGE_LIQUID_LONG_V1: {
@@ -70,6 +71,13 @@ _UNIVERSE_PROFILES: dict[str, dict[str, Any]] = {
         "exchange": "NYSE,NASDAQ,AMEX",
         "exclude_types": "ETF,FUND,ADR,SPAC",
     },
+    _UNIVERSE_PROFILE_BROAD_LIQUID_LONG_V1: {
+        "market_cap_min": 300_000_000,
+        "price_min": 5,
+        "avg_dollar_volume_20d_min": 3_000_000,
+        "exchange": "NYSE,NASDAQ,AMEX",
+        "exclude_types": "ETF,FUND,ADR,SPAC",
+    },
 }
 
 

libs/intraday/cache.py

@@ -10,6 +10,7 @@ from __future__ import annotations
 import os
 from pathlib import Path
 from typing import Any
+from uuid import uuid4
 
 import pyarrow as pa
 import pyarrow.parquet as pq
@@ -197,7 +198,7 @@ class IntradayCache:
             _INTRADAY_NEGATIVE_REASON_KEY: reason.encode(),
         })
         table = pa.Table.from_pylist([], schema=schema)
-        tmp = p.with_suffix(".tmp")
+        tmp = p.with_suffix(f".{uuid4().hex}.tmp")
         try:
             pq.write_table(table, str(tmp), compression="snappy")
             os.replace(str(tmp), str(p))

libs/intraday/domain.py

@@ -1142,8 +1142,15 @@ class ORBStrategyParams(BaseModel):
     """Calendar days to look back for prior earnings/guidance events in DB.
     0=off (default, V24 parity). 7=V46. When >0 AND weight_event_catalyst>0,
     uses DB events table path instead of Oracle REST API for event_flag/event_score.
-    Marks each trading day within this window after an earnings_release or
+    Marks each trading day within this window after qualifying events as
-    guidance_update event as event_flag=True, event_score=1.0."""
+    event_flag=True, event_score=1.0. Event types controlled by prior_event_types."""
+
+    prior_event_types: list[str] = Field(
+        default_factory=lambda: ["earnings_release", "guidance_update"]
+    )
+    """DB event types to include in prior_event_lookback_days signal.
+    Default matches V46 (earnings_release + guidance_update).
+    Set to ['earnings_release'] for earnings-only variant."""
 
     weight_attention_wiki: float = 0.0
     """Wikipedia attention weight for actual stocks-in-play ranking."""

libs/intraday/metrics.py

@@ -778,6 +778,9 @@ def write_results(
                 "sector_scaler": r.sector_scaler,
                 "tail_risk_scaler": r.tail_risk_scaler,
                 "is_soft_day": r.is_soft_day,
+                "event_day_liquid_active": r.event_day_liquid_active,
+                "event_day_liquid_event_count": r.event_day_liquid_event_count,
+                "event_day_liquid_total_event_entry_dollar_volume": r.event_day_liquid_total_event_entry_dollar_volume,
             }
             for r in day_results
         ],

libs/intraday/screener.py

@@ -619,6 +619,7 @@ def momentum_pre_screen_candidates(
 
     require_event_flag = bool(getattr(strategy, "candidate_require_event_flag", False)) if strategy else False
     min_event_score = getattr(strategy, "candidate_min_event_score", None) if strategy else None
+    allowed_event_types = _momentum_allowed_event_types(strategy)
     min_wiki_spike = getattr(strategy, "candidate_min_attention_wiki_spike_10d", None) if strategy else None
     min_article_count = (
         getattr(strategy, "candidate_min_attention_article_count_3d", None)
@@ -651,8 +652,7 @@ def momentum_pre_screen_candidates(
             if gap_pct is None or gap_pct < threshold:
                 continue
 
-            event_flag = bool(info.get("event_flag"))
+            event_flag, event_score = _momentum_effective_event_state(info, allowed_event_types)
-            event_score = float(info.get("event_score") or 0.0)
             wiki_spike = float(info.get("attention_wiki_spike_10d") or 0.0)
             article_count = int(info.get("attention_article_count_3d") or 0)
             us_article_count = int(info.get("attention_us_article_count_3d") or 0)
@@ -707,6 +707,46 @@ def momentum_pre_screen_candidates(
     return result
 
 
+def _momentum_allowed_event_types(strategy) -> set[str]:
+    if strategy is None:
+        return set()
+    return {
+        str(value).strip().lower()
+        for value in getattr(strategy, "candidate_allowed_event_types", [])
+        if str(value).strip()
+    }
+
+
+def _momentum_event_types_pass(
+    info: dict,
+    allowed_event_types: set[str],
+) -> bool:
+    if not allowed_event_types:
+        return True
+    raw_event_types = info.get("event_types") or []
+    event_types = {
+        str(value).strip().lower()
+        for value in raw_event_types
+        if str(value).strip()
+    }
+    if not event_types:
+        return False
+    return any(event_type in allowed_event_types for event_type in event_types)
+
+
+def _momentum_effective_event_state(
+    info: dict,
+    allowed_event_types: set[str],
+) -> tuple[bool, float]:
+    event_flag = bool(info.get("event_flag"))
+    event_score = float(info.get("event_score") or 0.0)
+    if not event_flag:
+        return False, 0.0
+    if allowed_event_types and not _momentum_event_types_pass(info, allowed_event_types):
+        return False, 0.0
+    return True, event_score
+
+
 def _momentum_candidate_signal_passes(
     info: dict,
     strategy,
@@ -716,13 +756,13 @@ def _momentum_candidate_signal_passes(
         return True
     require_event_flag = bool(getattr(strategy, "candidate_require_event_flag", False))
     min_event_score = getattr(strategy, "candidate_min_event_score", None)
+    allowed_event_types = _momentum_allowed_event_types(strategy)
     min_wiki_spike = getattr(strategy, "candidate_min_attention_wiki_spike_10d", None)
     min_article_count = getattr(strategy, "candidate_min_attention_article_count_3d", None)
     min_us_article_count = getattr(strategy, "candidate_min_attention_us_article_count_3d", None)
     min_resolver_conf = getattr(strategy, "candidate_min_attention_resolver_confidence", None)
 
-    event_flag = bool(info.get("event_flag"))
+    event_flag, event_score = _momentum_effective_event_state(info, allowed_event_types)
-    event_score = float(info.get("event_score") or 0.0)
     wiki_spike = float(info.get("attention_wiki_spike_10d") or 0.0)
     article_count = int(info.get("attention_article_count_3d") or 0)
     us_article_count = int(info.get("attention_us_article_count_3d") or 0)
@@ -749,6 +789,7 @@ def _momentum_intraday_weighted_score(
     strategy,
 ) -> float:
     """Weighted same-day candidate score for intraday-first ranking."""
+    from libs.intraday.simulator import _same_day_support_score
 
     def _clip_unit(value: float | None, cap: float) -> float:
         if value is None or cap <= 0:
@@ -785,6 +826,7 @@ def _momentum_intraday_weighted_score(
         if entropy_20d is not None
         else 0.0
     )
+    support_score = _same_day_support_score(info)
 
     event_score = float(daily_info.get("event_score") or 0.0)
     wiki_spike = float(daily_info.get("attention_wiki_spike_10d") or 0.0)
@@ -811,6 +853,13 @@ def _momentum_intraday_weighted_score(
     score += float(getattr(strategy, "candidate_intraday_weight_avg_dollar_vol_30d", 0.0) or 0.0) * _prior_dollar_vol_score(
         avg_dollar_vol_30d
     )
+    score += float(getattr(strategy, "candidate_intraday_weight_support_score", 0.0) or 0.0) * support_score
+    score += float(getattr(strategy, "candidate_intraday_weight_liquid_largecap", 0.0) or 0.0) * (
+        1.0 if info.get("is_liquid_largecap") else 0.0
+    )
+    score += float(getattr(strategy, "candidate_intraday_weight_moderate_gap_liquid", 0.0) or 0.0) * (
+        1.0 if info.get("is_moderate_gap_liquid") else 0.0
+    )
     score += float(getattr(strategy, "candidate_intraday_weight_gap", 0.0) or 0.0) * _clip_unit(
         gap_pct, 0.10
     )
@@ -818,6 +867,10 @@ def _momentum_intraday_weighted_score(
         ret_5d, 0.20
     )
     score += float(getattr(strategy, "candidate_intraday_weight_low_entropy", 0.0) or 0.0) * low_entropy
+    score += float(getattr(strategy, "candidate_intraday_weight_sector_thrust", 0.0) or 0.0) * _clip_unit(
+        float(info.get("sector_thrust_score") or 0.0),
+        1.0,
+    )
     score += float(getattr(strategy, "candidate_intraday_weight_event_score", 0.0) or 0.0) * _clip_unit(
         event_score, 3.0
     )
@@ -830,12 +883,34 @@ def _momentum_intraday_weighted_score(
     return score
 
 
+def _momentum_intraday_liquid_continuation_score(
+    info: dict,
+) -> tuple[float, float, float, float, float, float, float, float, float]:
+    from libs.intraday.simulator import _same_day_support_score
+
+    entropy_20d = info.get("entropy_20d")
+    return (
+        1.0 if info.get("is_moderate_gap_liquid") else 0.0,
+        1.0 if info.get("is_liquid_largecap") else 0.0,
+        1.0 if info.get("is_sector_thrust") else 0.0,
+        _same_day_support_score(info),
+        float(info.get("confirmation_return_pct") or 0.0),
+        float(info.get("entry_dollar_volume") or 0.0),
+        float(info.get("avg_dollar_vol_30d") or 0.0),
+        float(info.get("gain_pct") or 0.0),
+        -(float(entropy_20d) if entropy_20d is not None else 1.0),
+    )
+
+
 def _momentum_intraday_event_reserve_eligible(
     daily_info: dict,
     strategy,
 ) -> bool:
     if not bool(daily_info.get("event_flag")):
         return False
+    allowed_event_types = _momentum_allowed_event_types(strategy)
+    if not _momentum_event_types_pass(daily_info, allowed_event_types):
+        return False
     min_score = getattr(strategy, "candidate_intraday_event_reserve_min_score", None)
     if min_score is None:
         return True
@@ -1070,6 +1145,7 @@ def momentum_intraday_first_candidates(
     strategy,
     *,
     daily_enrichment: dict[str, dict[str, dict]] | None = None,
+    ticker_sectors: dict[str, str] | None = None,
     max_per_day: int | None = None,
 ) -> dict[str, list[str]]:
     """Build the final momentum shortlist from entry-time intraday information.
@@ -1078,7 +1154,11 @@ def momentum_intraday_first_candidates(
     already bounded the intraday fetch set. The final ranking uses only
     information known by the entry / confirmation bar of the same day.
     """
-    from libs.intraday.simulator import _select_momentum_sleeves, compute_morning_gains
+    from libs.intraday.simulator import (
+        _annotate_sector_thrust_features,
+        _select_momentum_sleeves,
+        compute_morning_gains,
+    )
 
     if max_per_day is None:
         max_per_day = max(1, int(getattr(strategy, "candidate_final_max_per_day", 30) or 30))
@@ -1108,6 +1188,11 @@ def momentum_intraday_first_candidates(
             day,
             daily_features_by_ticker=daily_info_by_ticker,
         )
+        gains = _annotate_sector_thrust_features(
+            gains,
+            shortlist_strategy,
+            ticker_sectors,
+        )
         if not gains:
             continue
         filtered_gains = {
@@ -1163,9 +1248,47 @@ def momentum_intraday_first_candidates(
                     daily_info_by_ticker,
                     strategy,
                     max_per_day=max_per_day,
+                )
+            continue
+        if rank_mode == "liquid_continuation":
+            rankable_liquid_gains = {
+                ticker: info
+                for ticker, info in rankable_gains.items()
+                if (
+                    info.get("is_moderate_gap_liquid")
+                    or info.get("is_liquid_largecap")
+                    or info.get("is_sector_thrust")
+                )
+            }
+            if not rankable_liquid_gains:
+                continue
+            ranked = sorted(
+                rankable_liquid_gains.items(),
+                key=lambda item: _momentum_intraday_liquid_continuation_score(item[1]),
+                reverse=True,
             )
+            if ranked:
+                ranked_tickers = _apply_momentum_intraday_event_reserve(
+                    [ticker for ticker, _info in ranked],
+                    filtered_gains,
+                    daily_info_by_ticker,
+                    strategy,
+                    day_bars=day_bars,
+                    max_per_day=max_per_day,
+                )
+                result[day] = _apply_momentum_intraday_moderate_liquid_reserve(
+                    ranked_tickers,
+                    filtered_gains,
+                    daily_info_by_ticker,
+                    strategy,
+                    max_per_day=max_per_day,
+                )
             continue
-        picks = _select_momentum_sleeves(rankable_gains, shortlist_strategy, ticker_sectors=None)
+        picks = _select_momentum_sleeves(
+            rankable_gains,
+            shortlist_strategy,
+            ticker_sectors=ticker_sectors,
+        )
         if picks:
             ranked_tickers = _apply_momentum_intraday_event_reserve(
                 [ticker for ticker, _sleeve in picks],

tests/unit/intraday/test_run_helpers.py

@@ -17,9 +17,12 @@ from apps.intraday_bt.run import (
     _normalize_candidate_map,
     _momentum_intraday_seed_candidates,
     _momentum_strategy_uses_candidate_stage_catalyst,
+    _momentum_strategy_uses_daily_enrichment,
     _momentum_strategy_requires_regime_ticker_daily,
     _momentum_strategy_uses_attention,
     _momentum_strategy_uses_catalyst,
+    _momentum_strategy_uses_sector_labels,
+    _momentum_strategy_uses_sector_proxies,
     _retain_recent_intraday_shortlist,
     _recent_intraday_first_candidates,
     _strategy_for_recent_live_scan,
@@ -275,13 +278,26 @@ def test_momentum_strategy_uses_seed_event_overlay_for_candidate_stage_catalyst(
     assert _momentum_strategy_uses_candidate_stage_catalyst(strategy) is True
 
 
+def test_momentum_strategy_uses_candidate_event_type_filter_for_fetch_activation() -> None:
+    strategy = StrategyParams(candidate_allowed_event_types=["earnings_release"])
+
+    assert _momentum_strategy_uses_catalyst(strategy) is True
+    assert _momentum_strategy_uses_candidate_stage_catalyst(strategy) is True
+
+
 def test_momentum_strategy_uses_event_reserve_and_event_sleeve_for_fetch_activation() -> None:
     reserve_strategy = StrategyParams(candidate_intraday_event_reserve_slots=1)
     sleeve_strategy = StrategyParams(use_event_sleeve=True, event_weight=0.1)
+    event_day_liquid_strategy = StrategyParams(
+        use_event_day_liquid_sleeve=True,
+        event_day_liquid_capital_fraction=0.1,
+        event_day_liquid_max_positions=1,
+    )
 
     assert _momentum_strategy_uses_catalyst(reserve_strategy) is True
     assert _momentum_strategy_uses_candidate_stage_catalyst(reserve_strategy) is False
     assert _momentum_strategy_uses_catalyst(sleeve_strategy) is True
+    assert _momentum_strategy_uses_catalyst(event_day_liquid_strategy) is True
 
 
 def test_momentum_strategy_uses_intraday_attention_weight_for_fetch_activation() -> None:
@@ -296,6 +312,21 @@ def test_momentum_strategy_requires_regime_ticker_daily_for_gap_meta_layer() ->
     assert _momentum_strategy_requires_regime_ticker_daily(strategy) is True
 
 
+def test_momentum_strategy_uses_sector_metadata_and_proxy_fetch_for_overlay_engines() -> None:
+    cluster_strategy = StrategyParams(use_liquid_cluster_engine=True)
+    etf_strategy = StrategyParams(
+        use_sector_etf_sleeve=True,
+        sector_etf_capital_fraction=0.2,
+        sector_etf_max_positions=1,
+    )
+
+    assert _momentum_strategy_uses_daily_enrichment(cluster_strategy) is True
+    assert _momentum_strategy_uses_sector_labels(cluster_strategy) is True
+    assert _momentum_strategy_uses_sector_proxies(cluster_strategy) is False
+    assert _momentum_strategy_uses_sector_labels(etf_strategy) is True
+    assert _momentum_strategy_uses_sector_proxies(etf_strategy) is True
+
+
 def test_momentum_intraday_seed_candidates_only_apply_signal_filters_in_final_pass() -> None:
     daily_bars = {
         "AAA": [
@@ -620,7 +651,9 @@ def test_retain_recent_intraday_shortlist_preserves_intraday_candidates() -> Non
 
 
 def test_momentum_strategy_defaults_to_simple_returns_and_cli_can_override() -> None:
-    config = load_config("configs/intraday/strategies/leader_intraday_momentum_high_wr.yaml")
+    config = load_config(
+        "configs/intraday/strategies/leader_intraday_momentum_high_wr_intraday_first.yaml"
+    )
 
     assert config.strategy.compound_returns is False
 

tests/unit/intraday/test_screener.py

@@ -184,6 +184,112 @@ def test_momentum_pre_screen_candidates_can_require_event_and_attention() -> Non
     assert result == {"2026-01-05": ["AAA"]}
 
 
+def test_momentum_pre_screen_candidates_can_filter_event_types() -> None:
+    daily_bars = {
+        "AAA": [
+            {"date": "2026-01-02", "open": 10.0, "high": 10.2, "low": 9.8, "close": 10.0, "volume": 1_000},
+            {"date": "2026-01-05", "open": 10.3, "high": 10.8, "low": 10.2, "close": 10.6, "volume": 2_000},
+        ],
+        "BBB": [
+            {"date": "2026-01-02", "open": 10.0, "high": 10.2, "low": 9.8, "close": 10.0, "volume": 1_000},
+            {"date": "2026-01-05", "open": 10.4, "high": 10.9, "low": 10.3, "close": 10.7, "volume": 2_000},
+        ],
+    }
+    enrichment = {
+        "AAA": {
+            "2026-01-05": {
+                "gap_pct": 0.03,
+                "ret_5d": 0.03,
+                "entropy_20d": 0.60,
+                "avg_dollar_vol_30d": 20_000_000.0,
+                "atr_14": 1.0,
+                "event_flag": True,
+                "event_score": 1.0,
+                "event_types": ["earnings_release"],
+            }
+        },
+        "BBB": {
+            "2026-01-05": {
+                "gap_pct": 0.04,
+                "ret_5d": 0.04,
+                "entropy_20d": 0.50,
+                "avg_dollar_vol_30d": 25_000_000.0,
+                "atr_14": 1.2,
+                "event_flag": True,
+                "event_score": 1.0,
+                "event_types": ["management_change"],
+            }
+        },
+    }
+    strategy = StrategyParams(
+        candidate_require_event_flag=True,
+        candidate_allowed_event_types=["earnings_release"],
+    )
+
+    result = momentum_pre_screen_candidates(
+        daily_bars,
+        ["2026-01-05"],
+        enrichment,
+        threshold=0.02,
+        max_per_day=5,
+        strategy=strategy,
+    )
+
+    assert result == {"2026-01-05": ["AAA"]}
+
+
+def test_momentum_pre_screen_candidates_event_type_filter_does_not_block_non_event_names() -> None:
+    daily_bars = {
+        "AAA": [
+            {"date": "2026-01-02", "open": 10.0, "high": 10.2, "low": 9.8, "close": 10.0, "volume": 1_000},
+            {"date": "2026-01-05", "open": 10.3, "high": 10.8, "low": 10.2, "close": 10.6, "volume": 2_000},
+        ],
+        "BBB": [
+            {"date": "2026-01-02", "open": 10.0, "high": 10.2, "low": 9.8, "close": 10.0, "volume": 1_000},
+            {"date": "2026-01-05", "open": 10.4, "high": 10.9, "low": 10.3, "close": 10.7, "volume": 2_000},
+        ],
+    }
+    enrichment = {
+        "AAA": {
+            "2026-01-05": {
+                "gap_pct": 0.03,
+                "ret_5d": 0.03,
+                "entropy_20d": 0.60,
+                "avg_dollar_vol_30d": 20_000_000.0,
+                "atr_14": 1.0,
+                "event_flag": True,
+                "event_score": 1.0,
+                "event_types": ["management_change"],
+            }
+        },
+        "BBB": {
+            "2026-01-05": {
+                "gap_pct": 0.04,
+                "ret_5d": 0.04,
+                "entropy_20d": 0.50,
+                "avg_dollar_vol_30d": 25_000_000.0,
+                "atr_14": 1.2,
+                "event_flag": False,
+                "event_score": 0.0,
+            }
+        },
+    }
+    strategy = StrategyParams(
+        candidate_allowed_event_types=["earnings_release"],
+    )
+
+    result = momentum_pre_screen_candidates(
+        daily_bars,
+        ["2026-01-05"],
+        enrichment,
+        threshold=0.02,
+        max_per_day=5,
+        strategy=strategy,
+    )
+
+    assert result == {"2026-01-05": ["BBB", "AAA"]}
+
+
 def test_momentum_intraday_first_candidates_uses_entry_time_info_only() -> None:
     strategy = StrategyParams(
         candidate_source_mode="intraday_first",
@@ -229,6 +335,68 @@ def test_momentum_intraday_first_candidates_uses_entry_time_info_only() -> None:
     assert result == {"2026-01-05": ["BBB"]}
 
 
+def test_momentum_intraday_first_candidates_can_filter_event_types() -> None:
+    strategy = StrategyParams(
+        candidate_source_mode="intraday_first",
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_confirmation_return_pct=0.0,
+        min_morning_gain_pct=0.01,
+        min_entry_volume=50_000,
+        candidate_final_max_per_day=2,
+        candidate_require_event_flag=True,
+        candidate_allowed_event_types=["earnings_release"],
+    )
+    all_intraday = {
+        "2026-01-05": {
+            "AAA": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 10.0, "high": 10.2, "low": 9.9, "close": 10.1, "volume": 30_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 10.1, "high": 10.3, "low": 10.0, "close": 10.2, "volume": 30_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 10.2, "high": 10.5, "low": 10.1, "close": 10.4, "volume": 30_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 10.4, "high": 10.7, "low": 10.3, "close": 10.6, "volume": 30_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 10.6, "high": 10.8, "low": 10.5, "close": 10.7, "volume": 30_000},
+            ],
+            "BBB": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 20.0, "high": 20.1, "low": 19.9, "close": 20.0, "volume": 40_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 20.0, "high": 20.2, "low": 19.9, "close": 20.1, "volume": 40_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 20.1, "high": 20.7, "low": 20.0, "close": 20.5, "volume": 40_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 20.5, "high": 21.0, "low": 20.4, "close": 20.9, "volume": 40_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 20.9, "high": 21.3, "low": 20.8, "close": 21.1, "volume": 40_000},
+            ],
+        }
+    }
+    daily_enrichment = {
+        "AAA": {
+            "2026-01-05": {
+                "event_flag": True,
+                "event_score": 1.0,
+                "event_types": ["management_change"],
+                "gap_pct": 0.01,
+                "avg_daily_vol_14d": 1_000_000.0,
+            }
+        },
+        "BBB": {
+            "2026-01-05": {
+                "event_flag": True,
+                "event_score": 1.0,
+                "event_types": ["earnings_release"],
+                "gap_pct": 0.01,
+                "avg_daily_vol_14d": 1_000_000.0,
+            }
+        },
+    }
+
+    result = momentum_intraday_first_candidates(
+        all_intraday,
+        ["2026-01-05"],
+        strategy,
+        daily_enrichment=daily_enrichment,
+        max_per_day=2,
+    )
+
+    assert result == {"2026-01-05": ["BBB"]}
+
+
 def test_momentum_intraday_first_candidates_can_use_weighted_ranking() -> None:
     strategy = StrategyParams(
         candidate_source_mode="intraday_first",
@@ -348,6 +516,151 @@ def test_momentum_intraday_first_candidates_weighted_ranking_can_use_prior_dolla
     assert result == {"2026-01-05": ["BBB"]}
 
 
+def test_momentum_intraday_first_candidates_weighted_ranking_can_use_sector_thrust() -> None:
+    strategy = StrategyParams(
+        candidate_source_mode="intraday_first",
+        candidate_intraday_rank_mode="weighted",
+        candidate_intraday_weight_gain=0.2,
+        candidate_intraday_weight_confirmation=0.2,
+        candidate_intraday_weight_entry_dollar_volume=0.1,
+        candidate_intraday_weight_sector_thrust=1.0,
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_confirmation_return_pct=0.0,
+        min_morning_gain_pct=0.01,
+        candidate_final_max_per_day=1,
+        use_sector_thrust_sleeve=True,
+        sector_thrust_min_members=2,
+        sector_thrust_min_gain_pct=0.01,
+        sector_thrust_min_confirmation_return_pct=0.003,
+        sector_thrust_min_entry_dollar_volume=50_000_000.0,
+        sector_thrust_min_avg_dollar_vol_30d=500_000_000.0,
+        sector_thrust_min_sector_avg_confirmation_return_pct=0.003,
+        sector_thrust_min_sector_total_entry_dollar_volume=120_000_000.0,
+    )
+    all_intraday = {
+        "2026-01-05": {
+            "ALLY_A": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 100.0, "high": 100.2, "low": 99.9, "close": 100.0, "volume": 180_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 100.0, "high": 100.8, "low": 99.9, "close": 100.6, "volume": 180_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 100.6, "high": 101.2, "low": 100.5, "close": 101.0, "volume": 180_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 101.0, "high": 101.7, "low": 100.9, "close": 101.5, "volume": 180_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 101.5, "high": 101.8, "low": 101.4, "close": 101.6, "volume": 180_000},
+            ],
+            "ALLY_B": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 80.0, "high": 80.1, "low": 79.9, "close": 80.0, "volume": 170_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 80.0, "high": 80.6, "low": 79.9, "close": 80.4, "volume": 170_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 80.4, "high": 80.9, "low": 80.3, "close": 80.8, "volume": 170_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 80.8, "high": 81.4, "low": 80.7, "close": 81.2, "volume": 170_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 81.2, "high": 81.5, "low": 81.1, "close": 81.3, "volume": 170_000},
+            ],
+            "SOLO": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 20.0, "high": 20.3, "low": 19.9, "close": 20.1, "volume": 300_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 20.1, "high": 20.8, "low": 20.0, "close": 20.6, "volume": 300_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 20.6, "high": 21.1, "low": 20.5, "close": 20.9, "volume": 300_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 20.9, "high": 21.3, "low": 20.8, "close": 21.1, "volume": 300_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 21.1, "high": 21.3, "low": 21.0, "close": 21.2, "volume": 300_000},
+            ],
+        }
+    }
+    daily_enrichment = {
+        "ALLY_A": {"2026-01-05": {"gap_pct": 0.01, "avg_daily_vol_14d": 5_000_000.0, "avg_dollar_vol_30d": 900_000_000.0}},
+        "ALLY_B": {"2026-01-05": {"gap_pct": 0.01, "avg_daily_vol_14d": 5_000_000.0, "avg_dollar_vol_30d": 850_000_000.0}},
+        "SOLO": {"2026-01-05": {"gap_pct": 0.01, "avg_daily_vol_14d": 10_000_000.0, "avg_dollar_vol_30d": 1_200_000_000.0}},
+    }
+
+    result = momentum_intraday_first_candidates(
+        all_intraday,
+        ["2026-01-05"],
+        strategy,
+        daily_enrichment=daily_enrichment,
+        ticker_sectors={
+            "ALLY_A": "Technology",
+            "ALLY_B": "Technology",
+            "SOLO": "Energy",
+        },
+        max_per_day=1,
+    )
+
+    assert result == {"2026-01-05": ["ALLY_A"]}
+
+
+def test_momentum_intraday_first_candidates_can_use_liquid_continuation_rank_mode() -> None:
+    strategy = StrategyParams(
+        candidate_source_mode="intraday_first",
+        candidate_intraday_rank_mode="liquid_continuation",
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_confirmation_return_pct=0.0,
+        min_morning_gain_pct=0.004,
+        candidate_final_max_per_day=1,
+        use_liquid_largecap_sleeve=True,
+        liquid_largecap_min_gain_pct=0.004,
+        liquid_largecap_max_gain_pct=0.03,
+        liquid_largecap_min_confirmation_return_pct=0.0005,
+        liquid_largecap_min_entry_dollar_volume=50_000_000.0,
+        liquid_largecap_min_avg_dollar_vol_30d=2_000_000_000.0,
+        liquid_largecap_max_entropy_20d=0.90,
+        use_moderate_gap_liquid_sleeve=True,
+        moderate_gap_liquid_min_gap_pct=0.002,
+        moderate_gap_liquid_max_gap_pct=0.04,
+        moderate_gap_liquid_min_gain_pct=0.005,
+        moderate_gap_liquid_max_gain_pct=0.04,
+        moderate_gap_liquid_min_confirmation_return_pct=0.001,
+        moderate_gap_liquid_min_entry_dollar_volume=25_000_000.0,
+        moderate_gap_liquid_min_avg_dollar_vol_30d=250_000_000.0,
+        moderate_gap_liquid_max_avg_dollar_vol_30d=4_000_000_000.0,
+        moderate_gap_liquid_min_volume_ratio_14d=0.02,
+        moderate_gap_liquid_max_entropy_20d=0.88,
+    )
+    all_intraday = {
+        "2026-01-05": {
+            "LIQ": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 100.0, "high": 100.8, "low": 99.9, "close": 100.5, "volume": 220_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 100.5, "high": 101.2, "low": 100.4, "close": 101.0, "volume": 220_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 101.0, "high": 101.8, "low": 100.9, "close": 101.5, "volume": 220_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 101.5, "high": 102.2, "low": 101.4, "close": 102.0, "volume": 220_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 102.0, "high": 102.4, "low": 101.9, "close": 102.2, "volume": 220_000},
+            ],
+            "HOT": [
+                {"timestamp": "2026-01-05T14:30:00+00:00", "open": 10.0, "high": 10.4, "low": 9.9, "close": 10.3, "volume": 120_000},
+                {"timestamp": "2026-01-05T14:35:00+00:00", "open": 10.3, "high": 10.7, "low": 10.2, "close": 10.6, "volume": 120_000},
+                {"timestamp": "2026-01-05T14:40:00+00:00", "open": 10.6, "high": 10.9, "low": 10.5, "close": 10.8, "volume": 120_000},
+                {"timestamp": "2026-01-05T14:45:00+00:00", "open": 10.8, "high": 11.0, "low": 10.7, "close": 10.9, "volume": 120_000},
+                {"timestamp": "2026-01-05T14:50:00+00:00", "open": 10.9, "high": 11.1, "low": 10.8, "close": 11.0, "volume": 120_000},
+            ],
+        }
+    }
+    daily_enrichment = {
+        "LIQ": {
+            "2026-01-05": {
+                "gap_pct": 0.01,
+                "avg_daily_vol_14d": 5_000_000.0,
+                "avg_dollar_vol_30d": 3_000_000_000.0,
+                "entropy_20d": 0.70,
+            }
+        },
+        "HOT": {
+            "2026-01-05": {
+                "gap_pct": 0.02,
+                "avg_daily_vol_14d": 4_000_000.0,
+                "avg_dollar_vol_30d": 50_000_000.0,
+                "entropy_20d": 0.82,
+            }
+        },
+    }
+
+    result = momentum_intraday_first_candidates(
+        all_intraday,
+        ["2026-01-05"],
+        strategy,
+        daily_enrichment=daily_enrichment,
+        max_per_day=2,
+    )
+
+    assert result == {"2026-01-05": ["LIQ"]}
+
+
 def test_momentum_intraday_first_candidates_can_replace_tail_with_event_reserve() -> None:
     strategy = StrategyParams(
         candidate_source_mode="intraday_first",

tests/unit/intraday/test_simulator.py

@@ -880,6 +880,163 @@ def test_select_momentum_sleeves_can_force_moderate_gap_liquid_pick() -> None:
     assert picks == [("TER", "moderate_gap_liquid")]
 
 
+def test_select_momentum_sleeves_can_force_sector_thrust_pick() -> None:
+    strategy = StrategyParams(
+        top_n=1,
+        use_five_sleeves=True,
+        use_sector_thrust_sleeve=True,
+        five_sleeve_core_weight=0.0,
+        five_sleeve_gap_weight=0.0,
+        five_sleeve_volume_weight=0.0,
+        five_sleeve_entropy_weight=0.0,
+        five_sleeve_trend_weight=0.0,
+        sector_thrust_weight=1.0,
+        five_sleeve_force_count=1,
+        sector_thrust_min_members=2,
+        sector_thrust_min_gain_pct=0.015,
+        sector_thrust_min_confirmation_return_pct=0.004,
+        sector_thrust_min_entry_dollar_volume=50_000_000.0,
+        sector_thrust_min_avg_dollar_vol_30d=500_000_000.0,
+        sector_thrust_min_sector_avg_confirmation_return_pct=0.004,
+        sector_thrust_min_sector_total_entry_dollar_volume=120_000_000.0,
+    )
+    morning_gains = {
+        "ALLY_A": {
+            "gain_pct": 0.03,
+            "entry_volume": 600_000,
+            "entry_dollar_volume": 80_000_000.0,
+            "avg_dollar_vol_30d": 900_000_000.0,
+            "confirmation_return_pct": 0.006,
+        },
+        "ALLY_B": {
+            "gain_pct": 0.028,
+            "entry_volume": 500_000,
+            "entry_dollar_volume": 70_000_000.0,
+            "avg_dollar_vol_30d": 850_000_000.0,
+            "confirmation_return_pct": 0.005,
+        },
+        "SOLO": {
+            "gain_pct": 0.05,
+            "entry_volume": 550_000,
+            "entry_dollar_volume": 90_000_000.0,
+            "avg_dollar_vol_30d": 1_000_000_000.0,
+            "confirmation_return_pct": 0.007,
+        },
+    }
+
+    picks = _select_momentum_sleeves(
+        morning_gains,
+        strategy,
+        ticker_sectors={
+            "ALLY_A": "Technology",
+            "ALLY_B": "Technology",
+            "SOLO": "Energy",
+        },
+    )
+
+    assert picks == [("ALLY_A", "sector_thrust")]
+
+
+def test_select_momentum_sleeves_can_use_liquid_continuation_selection_mode() -> None:
+    strategy = StrategyParams(
+        top_n=2,
+        momentum_selection_mode="liquid_continuation",
+    )
+    morning_gains = {
+        "HOT": {
+            "gain_pct": 0.05,
+            "confirmation_return_pct": 0.002,
+            "entry_dollar_volume": 4_000_000.0,
+            "avg_dollar_vol_30d": 30_000_000.0,
+            "entropy_20d": 0.82,
+            "is_liquid_largecap": False,
+            "is_moderate_gap_liquid": False,
+            "is_sector_thrust": False,
+        },
+        "LIQ": {
+            "gain_pct": 0.015,
+            "confirmation_return_pct": 0.006,
+            "entry_dollar_volume": 90_000_000.0,
+            "avg_dollar_vol_30d": 3_000_000_000.0,
+            "entropy_20d": 0.72,
+            "is_liquid_largecap": True,
+            "is_moderate_gap_liquid": True,
+            "is_sector_thrust": False,
+        },
+    }
+
+    picks = _select_momentum_sleeves(morning_gains, strategy)
+
+    assert picks == [("LIQ", "liquid_continuation_core")]
+
+
+def test_simulate_day_records_sector_thrust_trade_diagnostics() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_confirmation_return_pct=0.0,
+        min_morning_gain_pct=0.01,
+        top_n=1,
+        slippage_bps=0.0,
+        use_five_sleeves=True,
+        use_sector_thrust_sleeve=True,
+        five_sleeve_core_weight=0.0,
+        five_sleeve_gap_weight=0.0,
+        five_sleeve_volume_weight=0.0,
+        five_sleeve_entropy_weight=0.0,
+        five_sleeve_trend_weight=0.0,
+        sector_thrust_weight=1.0,
+        five_sleeve_force_count=1,
+        sector_thrust_min_members=2,
+        sector_thrust_min_gain_pct=0.015,
+        sector_thrust_min_confirmation_return_pct=0.004,
+        sector_thrust_min_entry_dollar_volume=50_000_000.0,
+        sector_thrust_min_avg_dollar_vol_30d=500_000_000.0,
+    )
+    bars_by_ticker = {
+        "ALLY_A": _bars(
+            "2026-01-13",
+            open_price=100.0,
+            closes=[100.2, 100.8, 101.2, 101.8, 102.0, 102.5],
+            volumes=[180_000, 180_000, 180_000, 180_000, 180_000, 180_000],
+        ),
+        "ALLY_B": _bars(
+            "2026-01-13",
+            open_price=80.0,
+            closes=[80.2, 80.7, 81.0, 81.4, 81.6, 81.9],
+            volumes=[170_000, 170_000, 170_000, 170_000, 170_000, 170_000],
+        ),
+        "SOLO": _bars(
+            "2026-01-13",
+            open_price=50.0,
+            closes=[50.2, 50.8, 51.2, 51.7, 51.8, 52.0],
+            volumes=[220_000, 220_000, 220_000, 220_000, 220_000, 220_000],
+        ),
+    }
+    day = simulate_day(
+        bars_by_ticker,
+        "2026-01-13",
+        strategy,
+        daily_features_by_ticker={
+            "ALLY_A": {"avg_daily_vol_14d": 2_000_000.0, "avg_dollar_vol_30d": 900_000_000.0},
+            "ALLY_B": {"avg_daily_vol_14d": 2_000_000.0, "avg_dollar_vol_30d": 850_000_000.0},
+            "SOLO": {"avg_daily_vol_14d": 2_000_000.0, "avg_dollar_vol_30d": 1_200_000_000.0},
+        },
+        ticker_sectors={
+            "ALLY_A": "Technology",
+            "ALLY_B": "Technology",
+            "SOLO": "Energy",
+        },
+    )
+
+    assert len(day.trades) == 1
+    assert day.trades[0].trade_sleeve == "sector_thrust"
+    assert day.trades[0].is_sector_thrust is True
+    assert day.trades[0].sector_thrust_member_count == 2
+    assert day.trades[0].sector_thrust_total_entry_dollar_volume is not None
+    assert day.trades[0].sector_thrust_total_entry_dollar_volume > 120_000_000.0
+
+
 def test_simulate_day_can_enable_event_sleeve_only_on_soft_days() -> None:
     strategy = StrategyParams(
         entry_minutes_after_open=10,
@@ -1120,6 +1277,267 @@ def test_simulate_day_can_apply_tail_risk_scaler_on_weak_support_single_name() -
     assert len(day.trades) == 1
 
 
+def test_tail_risk_event_exemption_requires_support_when_configured() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.01,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        use_event_sleeve=True,
+        event_min_score=1.0,
+        tail_risk_day_max_trades=1,
+        tail_risk_day_min_max_gain_pct=0.03,
+        tail_risk_day_max_support_score=0.35,
+        tail_risk_day_min_max_confirmation_return_pct=0.01,
+        tail_risk_day_require_no_event=True,
+        tail_risk_day_event_exemption_min_support_score=0.35,
+        tail_risk_day_scale=0.5,
+    )
+
+    day = simulate_day(
+        {
+            "WEAK_EVENT": _bars(
+                "2026-02-18",
+                open_price=10.0,
+                closes=[10.1, 10.35, 10.5, 10.7, 10.6, 10.2],
+                volumes=[120_000] * 6,
+            ),
+        },
+        "2026-02-18",
+        strategy,
+        daily_features_by_ticker={
+            "WEAK_EVENT": {
+                "gap_pct": 0.04,
+                "avg_daily_vol_14d": 1_000_000.0,
+                "avg_dollar_vol_30d": 25_000_000.0,
+                "ret_5d": 0.07,
+                "entropy_20d": 0.82,
+                "event_flag": True,
+                "event_score": 1.0,
+            },
+        },
+    )
+
+    assert day.tail_risk_scaler == 0.5
+    assert round(day.capital_deployed, 2) == 5000.0
+    assert day.trades[0].support_score == 0.2
+
+
+def test_tail_risk_event_exemption_keeps_supported_event_full_size() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.01,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        use_event_sleeve=True,
+        event_min_score=1.0,
+        tail_risk_day_max_trades=1,
+        tail_risk_day_min_max_gain_pct=0.03,
+        tail_risk_day_max_support_score=0.60,
+        tail_risk_day_min_max_confirmation_return_pct=0.01,
+        tail_risk_day_require_no_event=True,
+        tail_risk_day_event_exemption_min_support_score=0.35,
+        tail_risk_day_scale=0.5,
+    )
+
+    day = simulate_day(
+        {
+            "SUPPORTED_EVENT": _bars(
+                "2026-02-18",
+                open_price=10.0,
+                closes=[10.1, 10.35, 10.5, 10.7, 10.6, 10.2],
+                volumes=[500_000] * 6,
+            ),
+        },
+        "2026-02-18",
+        strategy,
+        daily_features_by_ticker={
+            "SUPPORTED_EVENT": {
+                "gap_pct": 0.04,
+                "avg_daily_vol_14d": 3_000_000.0,
+                "avg_dollar_vol_30d": 100_000_000.0,
+                "ret_5d": 0.07,
+                "entropy_20d": 0.82,
+                "event_flag": True,
+                "event_score": 1.0,
+            },
+        },
+    )
+
+    assert day.tail_risk_scaler == 1.0
+    assert round(day.capital_deployed, 2) == 10000.0
+    assert day.trades[0].support_score is not None
+    assert day.trades[0].support_score >= 0.35
+
+
+def test_low_momentum_single_name_scaler_reduces_weak_single_pick() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.01,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        low_momentum_single_name_max_gain_pct=0.025,
+        low_momentum_single_name_require_no_event=True,
+        low_momentum_single_name_exempt_largecap=True,
+        low_momentum_single_name_scale=0.55,
+    )
+
+    day = simulate_day(
+        {
+            "LOW": _bars(
+                "2025-12-15",
+                open_price=100.0,
+                closes=[100.8, 101.1, 101.4, 101.8, 101.7, 97.0],
+                volumes=[100_000] * 6,
+            ),
+        },
+        "2025-12-15",
+        strategy,
+        daily_features_by_ticker={
+            "LOW": {
+                "gap_pct": 0.02,
+                "avg_daily_vol_14d": 1_000_000.0,
+                "avg_dollar_vol_30d": 150_000_000.0,
+                "ret_5d": 0.02,
+                "entropy_20d": 0.75,
+                "event_flag": False,
+                "event_score": 0.0,
+            },
+        },
+    )
+
+    assert day.tail_risk_scaler == 0.55
+    assert round(day.capital_deployed, 2) == 5500.0
+    assert len(day.trades) == 1
+
+
+def test_soft_day_sparse_scaler_reduces_unsupported_soft_basket() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.01,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        market_regime_gap_threshold=-0.03,
+        market_regime_gap_ticker="SPY",
+        regime_size_scale_low=-0.02,
+        regime_size_scale_high=0.0,
+        regime_size_scale_min=0.5,
+        soft_day_scaler_threshold=0.8,
+        soft_day_sparse_max_trades=2,
+        soft_day_sparse_require_no_event=True,
+        soft_day_sparse_exempt_largecap=True,
+        soft_day_sparse_exempt_moderate_gap_liquid=True,
+        soft_day_sparse_scale=0.7,
+    )
+
+    day = simulate_day(
+        {
+            "FRAGILE": _bars(
+                "2026-01-28",
+                open_price=20.0,
+                closes=[20.1, 20.3, 20.5, 20.7, 20.9, 19.8],
+                volumes=[100_000] * 6,
+            ),
+        },
+        "2026-01-28",
+        strategy,
+        daily_features_by_ticker={
+            "SPY": {"prev_close": 100.0, "today_open": 98.0},
+            "FRAGILE": {
+                "gap_pct": 0.015,
+                "avg_daily_vol_14d": 1_000_000.0,
+                "avg_dollar_vol_30d": 120_000_000.0,
+                "ret_5d": 0.01,
+                "entropy_20d": 0.75,
+                "event_flag": False,
+                "event_score": 0.0,
+            },
+        },
+    )
+
+    assert day.is_soft_day is True
+    assert day.soft_day_sparse_scaler == 0.7
+    assert day.tail_risk_scaler == 0.7
+    assert round(day.capital_deployed, 2) == 3500.0
+
+
+def test_soft_day_sparse_scaler_keeps_supported_moderate_liquid_basket_full_size() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.01,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        market_regime_gap_threshold=-0.03,
+        market_regime_gap_ticker="SPY",
+        regime_size_scale_low=-0.02,
+        regime_size_scale_high=0.0,
+        regime_size_scale_min=0.5,
+        soft_day_scaler_threshold=0.8,
+        soft_day_sparse_max_trades=2,
+        soft_day_sparse_require_no_event=True,
+        soft_day_sparse_exempt_largecap=True,
+        soft_day_sparse_exempt_moderate_gap_liquid=True,
+        soft_day_sparse_scale=0.7,
+        use_moderate_gap_liquid_sleeve=True,
+        moderate_gap_liquid_min_gap_pct=0.005,
+        moderate_gap_liquid_max_gap_pct=0.025,
+        moderate_gap_liquid_min_gain_pct=0.015,
+        moderate_gap_liquid_max_gain_pct=0.04,
+        moderate_gap_liquid_min_confirmation_return_pct=0.005,
+        moderate_gap_liquid_min_entry_dollar_volume=20_000_000.0,
+        moderate_gap_liquid_min_avg_dollar_vol_30d=250_000_000.0,
+        moderate_gap_liquid_max_avg_dollar_vol_30d=2_000_000_000.0,
+        moderate_gap_liquid_min_volume_ratio_14d=0.04,
+        moderate_gap_liquid_max_entropy_20d=0.86,
+    )
+
+    day = simulate_day(
+        {
+            "TER": _bars(
+                "2026-01-29",
+                open_price=100.0,
+                closes=[100.4, 101.0, 101.7, 102.3, 102.7, 103.0],
+                volumes=[500_000] * 6,
+            ),
+        },
+        "2026-01-29",
+        strategy,
+        daily_features_by_ticker={
+            "SPY": {"prev_close": 100.0, "today_open": 98.0},
+            "TER": {
+                "gap_pct": 0.012,
+                "avg_daily_vol_14d": 8_000_000.0,
+                "avg_dollar_vol_30d": 750_000_000.0,
+                "ret_5d": 0.03,
+                "entropy_20d": 0.79,
+                "event_flag": False,
+                "event_score": 0.0,
+            },
+        },
+    )
+
+    assert day.is_soft_day is True
+    assert day.soft_day_sparse_scaler == 1.0
+    assert day.tail_risk_scaler == 1.0
+    assert round(day.capital_deployed, 2) == 5000.0
+    assert day.trades[0].is_moderate_gap_liquid is True
+
+
 def test_simulate_day_keeps_full_size_for_supported_single_name() -> None:
     strategy = StrategyParams(
         entry_minutes_after_open=15,
@@ -1210,6 +1628,364 @@ def test_select_momentum_sleeves_can_add_liquid_largecap_fallback_when_sparse()
     assert ("LQ", "liquid_largecap_fallback") in picks
 
 
+def test_simulate_day_can_add_liquid_cluster_engine_without_disturbing_base_basket() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.04,
+        min_confirmation_return_pct=0.003,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        use_liquid_cluster_engine=True,
+        liquid_cluster_capital_fraction=0.25,
+        liquid_cluster_max_positions=1,
+        liquid_cluster_min_members=2,
+        liquid_cluster_min_gain_pct=0.015,
+        liquid_cluster_max_gain_pct=0.04,
+        liquid_cluster_min_confirmation_return_pct=0.003,
+        liquid_cluster_min_entry_dollar_volume=30_000_000.0,
+        liquid_cluster_min_avg_dollar_vol_30d=300_000_000.0,
+        liquid_cluster_min_volume_ratio_14d=0.10,
+        liquid_cluster_max_entropy_20d=0.80,
+        liquid_cluster_min_sector_avg_confirmation_return_pct=0.003,
+        liquid_cluster_min_sector_total_entry_dollar_volume=100_000_000.0,
+    )
+
+    day = simulate_day(
+        {
+            "CORE": _bars(
+                "2026-02-03",
+                open_price=100.0,
+                closes=[100.5, 102.0, 103.0, 106.0, 106.4, 107.0],
+                volumes=[250_000] * 6,
+            ),
+            "CL_A": _bars(
+                "2026-02-03",
+                open_price=50.0,
+                closes=[50.2, 50.7, 50.9, 51.2, 51.3, 51.4],
+                volumes=[400_000] * 6,
+            ),
+            "CL_B": _bars(
+                "2026-02-03",
+                open_price=60.0,
+                closes=[60.2, 60.7, 60.9, 61.3, 61.4, 61.5],
+                volumes=[350_000] * 6,
+            ),
+        },
+        "2026-02-03",
+        strategy,
+        daily_features_by_ticker={
+            "CORE": {
+                "gap_pct": 0.03,
+                "avg_daily_vol_14d": 2_000_000.0,
+                "avg_dollar_vol_30d": 900_000_000.0,
+                "ret_5d": 0.12,
+                "entropy_20d": 0.40,
+            },
+            "CL_A": {
+                "gap_pct": 0.015,
+                "avg_daily_vol_14d": 3_000_000.0,
+                "avg_dollar_vol_30d": 800_000_000.0,
+                "ret_5d": 0.05,
+                "entropy_20d": 0.45,
+            },
+            "CL_B": {
+                "gap_pct": 0.012,
+                "avg_daily_vol_14d": 2_500_000.0,
+                "avg_dollar_vol_30d": 750_000_000.0,
+                "ret_5d": 0.04,
+                "entropy_20d": 0.48,
+            },
+        },
+        ticker_sectors={
+            "CORE": "Energy",
+            "CL_A": "Technology",
+            "CL_B": "Technology",
+        },
+    )
+
+    assert day.trades[0].ticker == "CORE"
+    assert day.trades[0].trade_sleeve == "core"
+    assert day.trades[1].ticker in {"CL_A", "CL_B"}
+    assert day.trades[1].trade_sleeve == "liquid_cluster_engine"
+    assert day.trades[1].is_liquid_cluster is True
+    assert day.trades[1].liquid_cluster_sector == "Technology"
+    assert day.capital_deployed == 10_000.0
+
+
+def test_simulate_day_can_add_event_day_liquid_sleeve_without_changing_base_basket() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.04,
+        min_confirmation_return_pct=0.003,
+        top_n=1,
+        use_five_sleeves=False,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        candidate_allowed_event_types=["earnings_release"],
+        use_event_day_liquid_sleeve=True,
+        event_day_liquid_capital_fraction=0.25,
+        event_day_liquid_max_positions=1,
+        event_day_liquid_min_event_names=1,
+        event_day_liquid_min_event_score=1.0,
+        event_day_liquid_min_event_support_score=0.2,
+        event_day_liquid_min_gain_pct=0.005,
+        event_day_liquid_max_gain_pct=0.03,
+        event_day_liquid_min_confirmation_return_pct=0.003,
+        event_day_liquid_min_entry_dollar_volume=30_000_000.0,
+        event_day_liquid_min_avg_dollar_vol_30d=500_000_000.0,
+        event_day_liquid_max_entropy_20d=0.80,
+        event_day_liquid_min_support_score=0.50,
+        liquid_largecap_min_gain_pct=0.005,
+        liquid_largecap_max_gain_pct=0.03,
+        liquid_largecap_min_confirmation_return_pct=0.003,
+        liquid_largecap_min_entry_dollar_volume=30_000_000.0,
+        liquid_largecap_min_avg_dollar_vol_30d=500_000_000.0,
+        liquid_largecap_max_entropy_20d=0.80,
+    )
+
+    day = simulate_day(
+        {
+            "CORE": _bars(
+                "2026-02-05",
+                open_price=100.0,
+                closes=[100.5, 102.0, 103.2, 105.0, 105.6, 106.0],
+                volumes=[250_000] * 6,
+            ),
+            "EVT": _bars(
+                "2026-02-05",
+                open_price=50.0,
+                closes=[50.3, 51.0, 51.8, 52.4, 52.7, 53.0],
+                volumes=[250_000] * 6,
+            ),
+            "LQ": _bars(
+                "2026-02-05",
+                open_price=200.0,
+                closes=[200.4, 201.0, 201.7, 202.6, 202.9, 203.5],
+                volumes=[250_000] * 6,
+            ),
+        },
+        "2026-02-05",
+        strategy,
+        daily_features_by_ticker={
+            "CORE": {
+                "gap_pct": 0.02,
+                "avg_daily_vol_14d": 2_000_000.0,
+                "avg_dollar_vol_30d": 1_000_000_000.0,
+                "ret_5d": 0.12,
+                "entropy_20d": 0.40,
+            },
+            "EVT": {
+                "gap_pct": 0.03,
+                "avg_daily_vol_14d": 1_500_000.0,
+                "avg_dollar_vol_30d": 600_000_000.0,
+                "ret_5d": 0.08,
+                "entropy_20d": 0.45,
+                "event_flag": True,
+                "event_score": 2.0,
+                "event_types": ["earnings_release"],
+            },
+            "LQ": {
+                "gap_pct": 0.01,
+                "avg_daily_vol_14d": 3_000_000.0,
+                "avg_dollar_vol_30d": 2_000_000_000.0,
+                "ret_5d": 0.03,
+                "entropy_20d": 0.40,
+            },
+        },
+    )
+
+    assert [trade.ticker for trade in day.trades] == ["CORE", "LQ"]
+    assert [trade.trade_sleeve for trade in day.trades] == ["core", "event_day_liquid"]
+    assert day.capital_deployed == 10_000.0
+
+
+def test_event_day_liquid_activation_can_use_broader_raw_event_types_than_core_event_filters() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.04,
+        min_confirmation_return_pct=0.003,
+        top_n=1,
+        use_five_sleeves=False,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        candidate_allowed_event_types=["earnings_release"],
+        use_event_day_liquid_sleeve=True,
+        event_day_liquid_capital_fraction=0.25,
+        event_day_liquid_max_positions=1,
+        event_day_liquid_allowed_event_types=["unknown"],
+        event_day_liquid_min_event_names=1,
+        event_day_liquid_min_event_score=1.0,
+        event_day_liquid_min_gain_pct=0.005,
+        event_day_liquid_max_gain_pct=0.03,
+        event_day_liquid_min_confirmation_return_pct=0.003,
+        event_day_liquid_min_entry_dollar_volume=30_000_000.0,
+        event_day_liquid_min_avg_dollar_vol_30d=500_000_000.0,
+        event_day_liquid_max_entropy_20d=0.80,
+        event_day_liquid_min_support_score=0.50,
+        liquid_largecap_min_gain_pct=0.005,
+        liquid_largecap_max_gain_pct=0.03,
+        liquid_largecap_min_confirmation_return_pct=0.003,
+        liquid_largecap_min_entry_dollar_volume=30_000_000.0,
+        liquid_largecap_min_avg_dollar_vol_30d=500_000_000.0,
+        liquid_largecap_max_entropy_20d=0.80,
+    )
+
+    day = simulate_day(
+        {
+            "CORE": _bars(
+                "2026-02-06",
+                open_price=100.0,
+                closes=[100.5, 102.0, 103.2, 105.0, 105.6, 106.0],
+                volumes=[250_000] * 6,
+            ),
+            "RAW_EVT": _bars(
+                "2026-02-06",
+                open_price=50.0,
+                closes=[50.2, 50.9, 51.6, 52.2, 52.5, 52.9],
+                volumes=[250_000] * 6,
+            ),
+            "LQ": _bars(
+                "2026-02-06",
+                open_price=200.0,
+                closes=[200.4, 201.0, 201.7, 202.6, 202.9, 203.5],
+                volumes=[250_000] * 6,
+            ),
+        },
+        "2026-02-06",
+        strategy,
+        daily_features_by_ticker={
+            "CORE": {
+                "gap_pct": 0.02,
+                "avg_daily_vol_14d": 2_000_000.0,
+                "avg_dollar_vol_30d": 1_000_000_000.0,
+                "ret_5d": 0.12,
+                "entropy_20d": 0.40,
+            },
+            "RAW_EVT": {
+                "gap_pct": 0.03,
+                "avg_daily_vol_14d": 1_500_000.0,
+                "avg_dollar_vol_30d": 600_000_000.0,
+                "ret_5d": 0.08,
+                "entropy_20d": 0.45,
+                "event_flag": True,
+                "event_score": 2.0,
+                "event_types": ["unknown"],
+            },
+            "LQ": {
+                "gap_pct": 0.01,
+                "avg_daily_vol_14d": 3_000_000.0,
+                "avg_dollar_vol_30d": 2_000_000_000.0,
+                "ret_5d": 0.03,
+                "entropy_20d": 0.40,
+            },
+        },
+    )
+
+    assert [trade.ticker for trade in day.trades] == ["CORE", "LQ"]
+    assert [trade.trade_sleeve for trade in day.trades] == ["core", "event_day_liquid"]
+
+
+def test_simulate_day_can_add_sector_etf_proxy_sleeve_from_liquid_cluster() -> None:
+    strategy = StrategyParams(
+        entry_minutes_after_open=10,
+        confirmation_minutes_after_entry=5,
+        min_morning_gain_pct=0.04,
+        min_confirmation_return_pct=0.003,
+        top_n=1,
+        slippage_bps=0.0,
+        daily_budget_reset=True,
+        initial_capital=10_000.0,
+        use_sector_etf_sleeve=True,
+        sector_etf_capital_fraction=0.25,
+        sector_etf_max_positions=1,
+        sector_etf_min_sector_score=0.20,
+        liquid_cluster_min_members=2,
+        liquid_cluster_min_gain_pct=0.015,
+        liquid_cluster_max_gain_pct=0.04,
+        liquid_cluster_min_confirmation_return_pct=0.003,
+        liquid_cluster_min_entry_dollar_volume=30_000_000.0,
+        liquid_cluster_min_avg_dollar_vol_30d=300_000_000.0,
+        liquid_cluster_min_volume_ratio_14d=0.10,
+        liquid_cluster_max_entropy_20d=0.80,
+        liquid_cluster_min_sector_avg_confirmation_return_pct=0.003,
+        liquid_cluster_min_sector_total_entry_dollar_volume=100_000_000.0,
+    )
+
+    day = simulate_day(
+        {
+            "CORE": _bars(
+                "2026-02-04",
+                open_price=100.0,
+                closes=[100.5, 102.0, 103.0, 106.0, 106.4, 107.0],
+                volumes=[250_000] * 6,
+            ),
+            "CL_A": _bars(
+                "2026-02-04",
+                open_price=50.0,
+                closes=[50.2, 50.7, 50.9, 51.2, 51.3, 51.4],
+                volumes=[400_000] * 6,
+            ),
+            "CL_B": _bars(
+                "2026-02-04",
+                open_price=60.0,
+                closes=[60.2, 60.7, 60.9, 61.3, 61.4, 61.5],
+                volumes=[350_000] * 6,
+            ),
+        },
+        "2026-02-04",
+        strategy,
+        daily_features_by_ticker={
+            "CORE": {
+                "gap_pct": 0.03,
+                "avg_daily_vol_14d": 2_000_000.0,
+                "avg_dollar_vol_30d": 900_000_000.0,
+                "ret_5d": 0.12,
+                "entropy_20d": 0.40,
+            },
+            "CL_A": {
+                "gap_pct": 0.015,
+                "avg_daily_vol_14d": 3_000_000.0,
+                "avg_dollar_vol_30d": 800_000_000.0,
+                "ret_5d": 0.05,
+                "entropy_20d": 0.45,
+            },
+            "CL_B": {
+                "gap_pct": 0.012,
+                "avg_daily_vol_14d": 2_500_000.0,
+                "avg_dollar_vol_30d": 750_000_000.0,
+                "ret_5d": 0.04,
+                "entropy_20d": 0.48,
+            },
+        },
+        ticker_sectors={
+            "CORE": "Energy",
+            "CL_A": "Technology",
+            "CL_B": "Technology",
+        },
+        sector_proxy_bars_by_ticker={
+            "XLK": _bars(
+                "2026-02-04",
+                open_price=200.0,
+                closes=[200.3, 201.0, 201.3, 202.0, 202.1, 202.6],
+                volumes=[150_000] * 6,
+            ),
+        },
+    )
+
+    assert [trade.ticker for trade in day.trades] == ["CORE", "XLK"]
+    assert [trade.trade_sleeve for trade in day.trades] == ["core", "sector_etf"]
+    assert day.trades[1].liquid_cluster_sector == "Technology"
+    assert day.trades[1].sector_proxy_ticker == "XLK"
+    assert day.capital_deployed == 10_000.0
+
+
 def test_compute_morning_gains_applies_entry_dollar_volume_filter() -> None:
     strategy = StrategyParams(
         entry_minutes_after_open=10,