Momentum

Event-sourced small-cap momentum day-trading system (Ross Cameron–style): gap-and-go / bull-flag setups on 1-minute bars, with paper execution on Alpaca and a live-broker integration for Schwab.

Important rebuild note. This codebase was reconstructed from scratch against the original architecture and interfaces after the original source files became unrecoverable in the working environment. Diff it against your local copy before discarding anything — module layout and public interfaces were preserved, but implementations are fresh. See RUNBOOK.md for what changed and why.

What this system does

Alpaca IEX bars ──► research/market.duckdb ──► Watcher ──► signal_ready
   (1-min, live)        (minute + daily)          │
                                                  ▼
Dashboard (approve/reject) ◄── approval queue ◄── TradingExecutionService
        │                                          │
        ▼                                          ▼
   exit orders ─────────────────────────► Alpaca paper account
                                                  │
                            AlpacaPaperSync ◄─────┘
                       (account/positions/orders → event store → dashboard)

Everything observable flows through a single append-only event store (data/momentum.duckdb): symbol discovery, criteria scores, signals, approval requests, orders, fills, account snapshots, broker health. The dashboard and all read paths are pure projections over those events, so any session can be replayed and audited.

Milestones

#	Scope	Status
M1	Strategy logic — setup evaluation, structure detection, quality, backtest	✅ strategy/
M2	Event store + projections	✅ storage/
M3	Schwab integration — OAuth, market data, positions/orders, health	✅ schwab/ (python milestone3_verify.py)
M4	Watcher + live paper execution	✅ runtime/, alpaca_paper/, trading_execution.py, run_live_paper.py
M5	Dashboard UI + API	✅ api/, dashboard_api.py

Quick start (paper trading)

pip install -r requirements.txt
cp .env.example .env        # fill in ALPACA_API_KEY / ALPACA_SECRET_KEY

python run_live_paper.py    # full loop + dashboard at http://127.0.0.1:8010

Signals appear in the dashboard's Approval Queue; click Approve to send the bracket order to your Alpaca paper account (or start with --auto-approve / TRADING_AUTO_APPROVE=1). Use the Exit button on a position to close it at market.

No keys? python run_live_paper.py --once still runs in dry mode so you can verify wiring.

Dashboard (control room)

The dashboard is a single self-contained page (no build step) that streams live state over Server-Sent Events and falls back to polling if the stream drops. It shows:

• P&L strip — realized, unrealized, total, win rate, average R, and open/closed trade counts for the session.
• Live sparkline charts on every ready signal and open position, drawn from 1-minute bars with dashed entry (blue) and stop (red) reference lines.
• Pre-trade risk preview in the approval queue — dollar risk, share count, notional, and stop distance before you approve.
• Click-to-expand criteria on any watched symbol — all nine setup criteria as pass / fail / not-evaluated, so a "blocked" symbol is legible at a glance.
• Activity feed of submissions and fills, plus the full order lifecycle.
• Audio + toast alerts when a new signal goes ready (toggle the sound button, or press S).
• Manual symbol injection — type a ticker (or press /) to force it onto the watchlist mid-session.
• Keyboard shortcuts — A approve / R reject the top of the queue, S toggle sound, / focus the add-symbol box, ? help.

Repository map

strategy/            pure strategy engine: evaluation, structure, backtest
storage/             event schema, event store, DuckDB schema, projections
runtime/             watcher state machine + provider registry
research/            research DBs, ingestion (bars, RSS, gappers), providers
alpaca_paper/        Alpaca paper client, executor, account sync
schwab/              Schwab OAuth, market data, positions/orders, health
trading_execution.py signal → sizing → approval → order pipeline
run_live_paper.py    the orchestrator (M4 end-to-end)
api/                 dashboard JSON API + static UI
dashboard_api.py     standalone read-only dashboard server
tests/               unit + integration suite (pytest)

CLI utilities: fetch_minute_bars.py (ad-hoc bar ingestion), backtest_cli.py (intraday backtests over stored sessions), research_cli.py (session symbols / gapper scan / RSS news), milestone3_verify.py (Schwab health walk-through).

Tests

python -m pytest          # 60 tests: strategy, storage, watcher, execution,
                          # schwab, api, research, end-to-end pipeline

Security

data/schwab_tokens.json (and all of data/) is git-ignored and written with 0600 permissions. If tokens were ever committed to your repository history, revoke and re-issue them at Schwab — see RUNBOOK.md.