On 2026-10-02 the trader died 5 times (13:15-15:05 ET). It left no traceback, and
each death came within the task's 5-min re-fire window, which fits its console
window being closed (as on 2026-09-29) while the PC was in use. Every relaunch popped
a new window.
- Task Scheduler now launches it with pythonw: no console window to close. Under
pythonw, stdout/stderr go to data/judge/logs/live_<date>.log, so a real crash
still leaves its traceback.
- A relaunched trader re-loads every symbol today's earlier runs were watching (from
the journal's "add" rows). It used to know only the names still passing the
scanner, so it stopped deciding on the others and never saved their ticks; the
review then had nothing to compare CABO and APLX against.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B3PXXn2tHBzdv6rYtGPz86
research/daily_report.py, run by Task Scheduler "Momentum\DailyReport" at 16:25 ET
on weekdays, writes data/reports/daily_<date>.md with ALERTS on top:
- the live opening-range bot's frozen 80-trade test: verdict, mean R with CI,
P&L, equity headroom over the floor, today's trades, open deviations, settings
drift;
- the judge v2 paper trial: judge.review for every counted day, cumulative
paper-vs-sim execution parity, today's flagged trades, trader errors and
restarts;
- the old-vs-new exit A/B (alerts at 50 pairs);
- stack health: down at the open, silent gaps of 10+ min, the press-release
recorder.
Read-only everywhere (PG_SKIP_SCHEMA=1, SELECTs only). Replayed on 2026-09-30 it
flags that day's real problems: the judge error loop, the paper stack down until
13:51, and a 25-min gap.
judge/PAPER_TRIAL.md, written before any counted trade: trades count from
2026-10-02. At 60 trades the paper trial must show execution parity with the
simulator (paper minus sim >= -0.15R) before a 150-trade performance read. Real
money is only considered after that, and only with the owner's go-ahead.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B3PXXn2tHBzdv6rYtGPz86
It sells as soon as any trade prints at or through the stop, or below the 6% trail
once +1R, walking the new prints in order exactly as the validated simulator does.
Whichever acts first wins: the broker stop or this one.
Why: Alpaca's paper engine filled triggered stops 6-60 s late on 2026-09-30 (CMCT,
PWCM; judge.review), which makes the trial look worse than the simulation for reasons
that are not the strategy's. Brokers also run no stop orders outside regular hours,
so any premarket trading needs this.
JUDGE_SOFT_STOP=0 turns it off. judge.review treats soft_stop/soft_trail as
stop/trail.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B3PXXn2tHBzdv6rYtGPz86
For a paper day, every order is lined up with what the validated simulator does on
the same recorded ticks: the sim exit from the real fill (stop, 6% trail after +1R,
20-min time stop, sell at the bid 300 ms after the trigger) vs the paper exit,
plus the sim R of orders that did not fill. Trades are flagged when R differs by
more than 0.3R, the exit reason differs, or the entry slipped. The report goes to
data/judge/reviews/<date>.md.
On 2026-09-30: paper -8.25R vs sim -3.97R on the same six fills. The gap is two
trades where Alpaca's paper engine filled a triggered stop 6-60 s late (CMCT,
PWCM; PWCM's own exit was also blocked by the stop-id bug fixed in f3c8be1).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B3PXXn2tHBzdv6rYtGPz86
On 2026-09-30 PWCM's stop was moved, and Alpaca's replace returns a NEW order id.
The trader kept the dead id, so reconcile treated the stop as gone and tried to
arm another one (refused with 403, shares held) about 20 times in 80 s, and the
trail exit could not sell because it cancelled the stale id.
- Adopt the id returned by replace. Reconcile follows replaced_by, and before
arming it adopts any working sell stop already at the broker.
- Exits cancel every open order on the symbol before close_position.
- If the price is already through the stop, close instead of arming a stop the
broker would reject.
- tests/unit/test_judge_live_exits.py covers these cases and the 2026-09-29 ones.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B3PXXn2tHBzdv6rYtGPz86
On 2026-09-29 the trader's console was killed at 10:21 ET (exit 0xC000013A) and
it sat dead for the rest of the day. The scheduled task now re-fires every 5 min
from 08:10 to 15:00 local, and IgnoreNew makes that a no-op while the trader is
running. It also catches up if the machine was off at 08:10.
A relaunched trader now picks up where the dead one left off:
- positions still held at the broker are adopted, with the entry, original
stop, fill time and high-water taken from today's journal and the backfilled
tape, so the trail, time stop and 15:55 flat still apply. The working stop leg
is reused; if none is working a new one is armed. A position with no known
stop is closed rather than guessed at.
- the per-symbol order count is rebuilt from the journal, so the cap holds
across restarts.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B3PXXn2tHBzdv6rYtGPz86
Day 1 of the paper trial (2026-09-29) exposed two exit bugs:
- When the broker stop had already filled, a trail/time exit tried to cancel the
filled leg, got a 422, returned without clearing the position, and retried
every second forever (BKYI). The leg-filled check sat after a `continue` and
never ran.
- A partial fill whose parent was cancelled took its OTO stop leg with it,
leaving the shares unprotected (MSGY, 82 of 133 filled).
Now every 5 s, and after any failed exit or stop move, the trader checks the stop
leg and the broker position: a filled stop or a flat position is recorded as the
exit, and held shares with no working stop get a standalone stop. Partial
fills get their stop re-armed straight away. Failed exits retry every 5 s instead
of every second.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
A gradient-boosted model scores burst / micro-pullback / whole-dollar signals on
squeeze stocks from tick data, and only its top-scored regular-hours signals
are traded. Validated in data/ticksim before any live use:
- v1 on a fresh 600-day sample: real ranking (AUC 0.63), thin edge. FAIL.
- v2 (trained on Jun-Jul of samples 1+2), pre-registered, on 500 NEW Aug-Sep
symbol-days: +1.11%/trade after the spread (day-block 90% lo +0.54%),
n=332 over 38 days. PASS. It held at 2 s latency and +0.2% extra cost.
- judge/engine.py: the validated signals, execution gates and features, as one
shared source.
- judge/model.py: trains and freezes v2 (cutoff = the training top 20%).
- judge/decide.py: pure decision logic.
- judge/replay.py: a live-style replay of recorded days. Parity: 40 of 41 research
trades matched with identical model scores.
- judge/live.py: the paper trader. Watchlist from the snapshot scan with
backfill, SIP trade/quote websocket, decisions each second, a limit at the ask
with a broker OTO stop (cancelled if unfilled in 3 s), trail 6% after +1R,
20-min time stop, flat by 15:55. $20 risk and $1,000 max notional per trade.
Everything is journalled and the day's ticks are kept for paper-vs-simulation
review. Weekends and holidays exit.
- Runs from the workstation (Task Scheduler, weekdays 09:10 ET) with the
research venv. Paper only.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01E3S5EFKThFVrjmN4HHsHMN
