Late Entry Time Sweep

Lab Report
Strategy
Experiment Late Entry Time Sweep
Date Mar 2, 2026
Dataset 250 days · 4.8M bars · 215 symbols
Verdict Rejected

Hypothesis

39% of YELLOW days upgrade to GREEN by 10:00 AM. If we detect the upgrade and enter late, we could capture additional P/L on days we'd otherwise sit out — without increasing risk, since the regime has confirmed GREEN conditions.

Baseline

V3 GREEN-only — Entry 09:35, 15bps slippage
115 days · 364 trades · +$1,360 P/L · 53% day WR · 48% trade WR · Sharpe 0.24

Dataset

250 trading days (March 2025 – March 2026). 4,848,591 five-minute bars across 215 symbols. All candidates are tickers that appeared in the morning scan on YELLOW-at-open days (60 qualifying days with tradeable candidates).

Procedure

Sweep 7 entry times from 09:45 to 10:35. For each checkpoint:

  1. Reconstruct regime at check_time using SPY gap, VWAP slope, intraday return, and breadth (4 of 6 regime signals)
  2. If YELLOW→GREEN upgrade detected, enter all scan candidates at the entry_time bar close
  3. Run V3 exits: ATR disaster floor (2×ATR₄, 3% minimum, 09:45 grace, 2-bar confirm) + 15:20 time exit
  4. Apply 15bps round-trip slippage to all trades

Results

Check Entry Upgrades Trades P/L Day WR Trade WR Sharpe Max DD
09:4009:451960-$1,73437%42%-1.57$6,196
09:4509:502382-$5543%46%-0.04$6,221
09:5009:552895-$4,52543%43%-3.21$6,842
09:5510:002585-$6,82940%35%-5.36$6,829
10:0010:052787-$7,13241%33%-5.85$7,666
10:1510:202268-$5,89032%31%-5.50$6,790
10:3010:352275-$11,48418%25%-14.03$11,845

Total P/L by Entry Time

Every entry time produces a net loss. The later the entry, the worse the outcome.

Win Rate Decay

Trade win rate degrades from 48% (baseline at open) to 25% (10:35 entry). The edge is at the open.

Conclusion

Hypothesis rejected. Late entries on YELLOW→GREEN upgrade days lose money at every tested time. The more upgrades detected (later checks find more), the more money lost — proving these are survivors of the first fade, not future winners.

Win rate degrades monotonically from 48% to 25%. Sharpe ratio goes from 0.24 (baseline) to -14.03 (worst case). Max drawdown exceeds $11k at the latest entry.

Implications

  • Keep 9:30:01 entry. The gap-and-go edge is concentrated at the open. Delayed entry misses the initial momentum burst.
  • --late-entry stays notification-only. The flag triggers a watching message and 10:00 AM re-check, but does not auto-execute. Manual confirmation preserved as a safety gate.
  • YELLOW sit-out is correct. Even when YELLOW days upgrade to GREEN, the late entry destroys value. The regime filter works — trust it.
  • Shadow tracker validates. Continue logging would-be P/L on sit-out days via core/shadow_tracker.py for ongoing confirmation.

Next Experiments

  • Sector-specific late entry: Do certain sectors (biotech, crypto) hold momentum longer than others after late entry?
  • Partial position late entry: Would entering with 50% size on upgrades reduce drawdown enough to be profitable?
  • ORB filter on late entries: If we wait for an opening range breakout before entering on upgrade days, does the signal quality improve?
  • Exit optimization by entry time: V3 uses a fixed 15:20 time exit — do later entries need earlier exits?

References

  • LeBeau, C. — Chandelier Exit: ATR-based trailing stop methodology, basis for V3 disaster floor
  • Clenow, A. (2019) — Trading Evolved: Systematic momentum strategy design and regime filtering
  • Internal: sim_late_entry_sweep.py — full simulation source (250-day backtest, 7 time slots, V3 exits)
  • Internal: core/regime.py — 6-signal traffic light gate (GREEN/YELLOW/RED)