From the multi-agent audit (ship-now, low-overfit-risk cluster):
INGESTION RESILIENCY
- client._request: 429/5xx now retry with Retry-After + exponential backoff
(previously hard-failed, feeding silent-stale ingest).
- SIP backfill feed (settings.backfill_feed='sip'): live realtime stays IEX, but
backtest/backfill ingestion uses the full consolidated tape — IEX sees only
~2-5% of true volume (verified: AAPL 22,797 vs 452,704), which was silently
corrupting every rvol/$-volume decision and backtest. eod_replay wired to it.
- step_ingest freshness watchdog: emits a STALE event + board note when the
newest bar is older than INGEST_STALE_SECONDS during RTH (45% of passes
historically returned 0 rows with no error). Optional hard arm-block
(INGEST_STALE_BLOCK, off by default).
RISK
- Portfolio gross-notional cap (TRADING_MAX_GROSS_NOTIONAL_PCT=0.60): both sizing
paths now cap each entry to the remaining gross budget, so 6 x 16% can't pile
the book into ~96% gross of correlated small-caps. Blocks/shrinks late entries.
- Fixed the duplicate TRADING_MAX_CONCURRENT_POSITIONS in .env.example.
MONITORING (UI)
- Naked/unprotected-position alarm: _unprotected_positions joins the latest
position + order snapshots (order sync now flattens legs) and the TUI board
shows a red UNPROTECTED banner the instant a held long lacks stop coverage —
the exact blind spot when APWC/NOWL went naked. Verified it flags today's
3 overnight positions.
Tests: gross-notional cap blocks when budget full; 50 pass.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
_daily_gappers selected each symbol's LATEST daily bar (always the most recent
date in the table) and skipped the symbol unless that bar == the session date.
So replaying ANY past date saw rows[0] != sess and skipped every symbol —
silently reporting "no qualifying gappers" for all history. Multi-day
backtesting was impossible; the dataset looked empty when it was not.
Bound the query to bars ON OR BEFORE the session date so rows[0] is the session
day and rows[1] the prior trading day. Verified: June 17 now finds 11 gappers,
June 16 finds 8, etc. — and a 6-day / 24-trade replay shows the clean strategy
is +11.6R, 75% win, +0.48R/trade (the live losses were execution bugs, since
fixed; no entry-rule tweak robustly beats baseline on this sample).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
eod_replay.py: after the close, pull the day's 100 most-active names (vs ~20
watched live), daily-screen the $1-5 gappers, minute-backfill only those, and
replay TODAY'S logic (entry filters + ORB + managed exits) over each — reporting
what it would have traded + est P&L + perfect-hindsight (biggest catchable
runs). Daily-first screening keeps it fast. Every run also grows the stored
dataset for the tuner/verification.
On 2026-06-17 it showed the new logic would have been +3.7R (~+$3.5k, 3 trades
100% win) vs the -$2.6k actually lost — the filters exclude exactly the losers
($7+ ICCM, blow-offs) that the old config traded.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
