Files
momentum devandClaude Fable 5 af8137dfd7 delete: dead DDL (10 tables), dead projections, pinned dead code; README/pyproject prune
pg_schema.sql: drop CREATE TABLE for 10 zero-reference tables (operator DROP
list in plans/002-deletions.log — production tables untouched until run).
projections.py: remove 4 zero-consumer query functions.
Clear all 'plan 002' ruff pins from the CI gate (files now F-clean);
api/main.py:F821 pin remains for plan 007. README repo-map/test-count fixed;
pydantic-settings removed (zero imports). Full receipts: plans/002-deletions.log

Suite: 351 passed (16 schwab/dead-module tests removed), 15 failures = the
known WSL-loopback dashboard set only.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-13 21:09:35 -04:00

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# Momentum
Event-sourced small-cap **momentum day-trading** system (Ross Cameron–style
gap-and-go / opening-range breakout). It screens the day's top overnight
gappers — the year-scale-validated population: **$2–20, static open gap
10–35%, real volume**, plus a volume-verified **>150% squeeze exception** —
arms an opening-range-breakout trigger the moment the range forms, fires a
bracket order on the live cross (regular session only), and manages the exit
with a breakeven ratchet + trailing profit-lock ladder. Execution runs on an
**Alpaca paper** account over the **SIP consolidated feed**; everything is
recorded in a **PostgreSQL** append-only event store and replayable.
```
Alpaca SIP bars ─► research DBs (minute+daily) ─► screen gappers ─► ArmedTriggerBook
(1-min, live) │ live price
▼ crosses trigger
PostgreSQL event store ◄────────────────────── TradingExecutionService ─► Alpaca paper
(append-only: signals, orders, │ bracket (entry+stop+target)
fills, account, risk events) ▼
▲ LiveExitManager ─► trail stop ↑ / flatten
└──────────── AlpacaPaperSync ◄──────── (account / positions / orders)
```
Every read path (dashboard, journal, monitoring board) is a pure **projection**
over the event store, so any session can be replayed and audited.
## Quick start (paper trading)
```bash
pip install -r requirements.txt
cp .env.example .env # fill in ALPACA_API_KEY / ALPACA_SECRET_KEY + DATABASE_URL
# PostgreSQL is the datastore. Point DATABASE_URL at your instance, e.g.
# DATABASE_URL=postgresql://user:pass@127.0.0.1:5432/momentum
python run_live_paper.py # full loop (+ embedded dashboard)
```
No keys? `python run_live_paper.py --once` runs a single dry pass to verify wiring.
## Deployment
Three supported shapes — **Docker Compose is canonical** (production runs the
full stack self-contained on TrueNAS SCALE: postgres, loop, dashboard :8765,
admin panel :8767, telegram bot, transcripts, nightly scheduler). Local
systemd units remain the development shape; a Helm refresh is planned.
**See [deploy/README.md](deploy/README.md)** for all three, including the
behavior flags every deployment must set explicitly.
## Commands
Everything is driven from the repo root. The `./momentum` wrapper runs the
inspection CLI in the project venv; the analysis scripts are plain `python`.
### Live trading loop — `run_live_paper.py`
| Command | What it does |
|---------|--------------|
| `python run_live_paper.py` | Full live loop: screen → arm → fire → manage exits → EOD flatten, with the embedded dashboard. |
| `python run_live_paper.py --no-dashboard` | Same, headless (how it runs in production / under a process manager). |
| `python run_live_paper.py --once` | One pass then exit — smoke-test the wiring. |
| `python run_live_paper.py --auto-approve` | Auto-arm brackets instead of waiting for dashboard approval (`TRADING_AUTO_APPROVE=1`). |
| `python run_live_paper.py --symbols AAPL,SNDL` | Force specific symbols onto the watchlist. |
### Monitoring & inspection — `./momentum`
| Command | What it does |
|---------|--------------|
| `./momentum watch` | Live monitoring board (armed triggers, ready signals, **today's trades + day P&L**, risk events). Refreshes every 3s. |
| `./momentum watch --once` | Render one frame and exit (for logging / a cron snapshot). |
| `./momentum journal` | Today's trade journal — every round-trip (ET times), broker-authoritative day P&L (`matched · open`), win rate. The 16:02 close capture. |
| `./momentum doctor` | Health check across each pipeline stage (DB reachable, ingest fresh, broker sync, loop heartbeat). |
| `./momentum inspect events` | Tail the raw event stream. |
| `./momentum inspect bars SYM` | Today's minute bars for a symbol. |
| `./momentum inspect discovery` | What the screener surfaced. |
| `./momentum inspect criteria SYM` | Per-criterion pass/fail for one symbol (why it is/isn't a setup). |
| `./momentum inspect signals` | Recent ready signals. |
### Analysis, backtest & tuning
| Command | What it does |
|---------|--------------|
| `python eod_replay.py [YYYY-MM-DD]` | End-of-day whole-market replay: run **today's logic** over every qualifying gapper (not just the ~20 watched live) + a perfect-hindsight line. Also **grows the stored dataset** for future verification. Defaults to today. |
| `python backtest_cli.py` | Intraday backtests over stored sessions. |
| `python sweep_exits.py` | Sweep managed-exit variants (trail / breakeven / profit-lock tiers), train/test split. |
| `python sweep_filters.py` | Sweep entry-filter variants (gap / rvol / price / liquidity). |
| `python diagnose_entries.py` | Entry-quality analysis — what the losers had in common. |
| `python nightly_tune.py` | Self-tune params into `data/learned_params.json` (applied on next boot). |
| `python research_cli.py` | Ad-hoc: session symbols, gapper scan, RSS news pull. |
| `python milestone3_verify.py` | Schwab integration health walk-through. |
### Data ingestion
| Command | What it does |
|---------|--------------|
| `python fetch_minute_bars.py` | Ad-hoc minute-bar ingestion. |
| `python backfill_history.py` | Backfill daily/minute history for the universe. |
### Scheduled jobs (cron wrappers)
The `.sh` wrappers set the venv + cwd so cron can call them directly:
```cron
2 16 * * 1-5 /path/momentum/journal.sh # capture the close trade journal
5 16 * * 1-5 /path/momentum/eod_replay.sh # whole-market replay (grows dataset)
30 17 * * 1-5 /path/momentum/nightly_tune.sh # retune params for tomorrow
```
### Tests
```bash
DATABASE_URL=postgresql://user:pass@host:5432/momentum python -m pytest
# ~365 tests: strategy, storage, triggers, execution (cooldown/re-entry/EOD
# flatten/naked-stop guards), exits, journal P&L, api, research.
```
Tests isolate via throwaway `mem_*` Postgres schemas; `tests/conftest.py` sweeps
them at session end.
## Configuration
All behavior is environment-driven — see **`.env.example`** for every key with
the *why*. The knobs that matter most:
- **Entry population** (year-scale validated 2026-07): `TRADING_PRICE_MIN/MAX`
(2–20), `TRADING_MIN_ENTRY_GAP_PCT` (0.10, static open gap), `TRIGGER_GAP_MAX`
(35 — the 35-150% band tested dead), `TRIGGER_GAP_SQUEEZE_MIN/RVOL` (150/5 —
re-admits real squeezes), `TRADING_MIN_DAY_VOLUME`, `TRADING_SESSION_ONLY`
(bars after-hours entries).
- **Sizing:** `TRADING_RISK_PER_TRADE_PCT` (1%), `TRADING_MAX_POSITION_PCT`,
`TRADING_LIQUIDITY_MAX_VOLUME_PCT` (size down thin names).
- **Exits:** `TRADING_EXIT_TRAIL_MODE=prior_low`, `TRADING_EXIT_TRAIL_AFTER_R`,
`TRADING_EXIT_BREAKEVEN_R`, `TRADING_EXIT_PROFIT_TIERS`.
- **Discipline:** `TRADING_BACKOUT_COOLDOWN_SECONDS`, `TRADING_BLOCK_REENTRY_AFTER_EXIT`
+ `TRADING_REENTRY_MIN_LOSS_PCT`, `TRADING_EOD_FLATTEN_TIME`.
- **Safety:** `TRADING_MAX_DAILY_LOSS_PCT` — **set to `0.03` before real-money
trading** (it ships loosened for testing).
## Database & performance
The single datastore is **PostgreSQL** (`DATABASE_URL`) — bars, events,
research tables, everything (the DuckDB era is over; `data/` holds only logs,
transcripts, and boot-time state). The event store is one append-only `events`
table that every projection reads.
**Hot-path index.** Projections overwhelmingly run
`WHERE event_type=? ORDER BY timestamp DESC LIMIT n` (latest snapshot of a type).
A composite index makes this an index seek regardless of how stale the type is —
without it, looking up the latest of an idle type backward-scans the whole table
(measured **373 ms → 0.018 ms** on 235k rows). It's created automatically by
`storage/event_store.py`:
```sql
CREATE INDEX idx_events_type_ts ON events (event_type, timestamp DESC);
```
**Plugins / extensions.** The big win here is the index above, not an extension.
For ongoing tuning:
- **`pg_stat_statements`** — enable (`shared_preload_libraries`, server restart)
to see which queries actually cost time. Diagnostic, not a speedup itself.
- **`pg_prewarm`** — warm the cache for the `events` table after a restart.
- **TimescaleDB** — only worth it if the event/bar volume grows large (hypertables
+ time partitioning + compression). Not required at current scale, and must be
installed on the server.
**Maintenance is automated.** The nightly job (scheduler service / systemd
timer) prunes diagnostic events older than 14 days, rotates logs, refreshes the
day's bars to SIP truth, and updates the float/dilution shadow caches.
Autovacuum is tuned per-table; run `ANALYZE` manually only after bulk imports.
## Repository map
```
run_live_paper.py the orchestrator: screen → arm → fire → manage → EOD flatten
momentum_cli.py the `momentum` CLI (watch / journal / doctor / inspect)
trading_execution.py signal → sizing → approval → bracket order; risk discipline
runtime/ triggers (ArmedTriggerBook), exit_manager, flatten helper
strategy/ pure strategy engine: evaluation, structure, exits, backtest
storage/ event schema + store (PostgreSQL), projections
research/ research DBs, ingestion (bars, RSS, gappers), screeners
alpaca_paper/ Alpaca paper client, executor, account/order sync
api/ + dashboard_api.py dashboard JSON API + static UI (:8765)
admin_api.py admin panel (:8767): health, config overrides, profiles, restarts
youtube_claims/ trader-video transcript -> claim extraction pipeline
controlroom/ NiceGUI control room (disabled by owner preference)
deploy/ compose (canonical) / systemd (local) / helm (planned)
eod_replay.py end-of-day whole-market replay
docs/history/ point-in-time plans from earlier eras — don't follow them
tests/ pytest suite (unit + integration)
```
## Security
`.env` and all of `data/` are git-ignored and
never committed; token files are written `0600`. The `.env` holds **live broker /
database / webhook credentials** — keep it local. If any secret was ever
committed to a repo's history, **rotate it** (re-issue Alpaca keys / re-run the
Schwab OAuth flow).