# messages_out

id: msg-1783390509877-e9llqm
in_reply_to: a2a-1783390469070-bydpzw
timestamp: 2026-07-07 02:15:09
kind: chat
platform_id: ag-1779666729747-9n7kga
channel_type: agent
content:
  {"text":"The repo at `~/projects/congressional-trading` doesn't exist on this system — I searched `/home`, `/root`, and `/workspace` and found nothing. Before I can start Phase 1, I need either:\n\n1. A git URL to clone it from, or\n2. The actual path where it lives\n\nCan you point me to it?"}


id: msg-1783390765664-9wn2cj
in_reply_to: a2a-1783390515141-c6t8kn
timestamp: 2026-07-07 02:19:25
kind: chat
platform_id: ag-1779666729747-9n7kga
channel_type: agent
content:
  {"text":"Phase 1 complete. Here's what I found and fixed:\n\n**Root cause:** `update_pending_outcomes` in `tools/outcome_tracker.py` called `yf.Ticker(t).history(period=\"65d\")` — a 65-day window ending **today** — then used `hist[\"Close\"].iloc[30]` and `iloc[60]` as the 30d/60d prices. For a signal notified 90 days ago, those indices pointed to ~35 and ~5 days ago from today, not 30/60 days from the notification. Win/loss outcomes were effectively random.\n\n**Fix (commit `14b4cc9`):**\n- Added `_find_price_at_date(hist, target_date)` helper that walks the index forward to the first trading day on or after a specific calendar date\n- `update_pending_outcomes` now fetches `history(start=notified_at_date, end=notified_at_date + 70d)` so the window is anchored to when the signal fired\n- Grouped rows by ticker — one yfinance call per ticker even if multiple outcomes share it — with a 0.5s sleep between tickers to avoid rate limits\n- Expanded the query from `WHERE outcome = 'pending'` to also include rows where `return_30d_pct IS NULL OR return_60d_pct IS NULL`, so any historically computed (buggy) rows get backfilled on next run\n\n**Schema:** No migration needed — `return_30d_pct`, `return_60d_pct`, `price_30d`, `price_60d` columns already exist. \"Win\" is defined as `price_60d > price_at_notify`; both 30d and 60d are stored so the canonical horizon can be chosen during calibration (Phase 2).\n\n**Existing test suite** (`tests/test_notification_policy.py`) doesn't cover outcome_tracker, and Python isn't installed in this container so I couldn't run it — but the changes are isolated to outcome_tracker.py and don't touch any code the tests exercise.\n\nReady to start Phase 2 whenever you give the go-ahead."}


id: msg-1783391129777-ten0x6
in_reply_to: a2a-1783390776992-w55c1j
timestamp: 2026-07-07 02:25:29
kind: chat
platform_id: ag-1779666729747-9n7kga
channel_type: agent
content:
  {"text":"Phase 2 complete. Committed as `b434e5b`.\n\n**What `scripts/backtest_sweep.py` does:**\n\nSweeps all 117 combinations of (threshold 7.0–13.0 step 0.5) × (conviction LOW/MEDIUM/HIGH) × (edge-factor min 2/3/4). For each combo it reports: signals/year, 30d win rate, 60d win rate, median return at 30d and 60d, and max single-signal loss. CSV goes to `scripts/backtest_results.csv`.\n\n**Signal universe:**\n- **Source A**: `signal_outcomes` table — notified signals with real fixed-horizon 30d/60d returns (the Phase 1 fix). Gold standard.\n- **Source B**: `signals` rows NOT in `signal_outcomes` with total_score ≥ 7.0 and `first_seen` ≥ 60 days ago — these are signals that scored but were never notified (e.g., scored 7–9 but didn't hit the notify gate). Returns fetched from yfinance using the same date-anchoring approach as Phase 1. Rate-limited at 0.5s/ticker.\n\nLLM scores (strategic/disruption) come from the DB cache in the `signals` table — no API calls.\n\n**One design decision worth flagging:** edge factors for Source A signals use current `signals` component scores (member_count, size_score, etc.) rather than the values at notification time — we don't store historical snapshots. This is the best available proxy. It means the edge-factor sweep column is an approximation for older signals, though score and conviction are exact (captured at notification time in `signal_outcomes`).\n\n**On data volume:** if the DB is relatively new, the sweep will show \"no viable configs\" until more signals have 60d closed windows. The `--no-fetch` flag skips yfinance and uses `signal_outcomes` only, which is faster for testing.\n\nReady for Phase 3 whenever you have results to review."}


id: msg-1783391165562-lpoz3z
in_reply_to: a2a-1783391155717-y1gfl6
timestamp: 2026-07-07 02:26:05
kind: chat
platform_id: ag-1779666729747-9n7kga
channel_type: agent
content:
  {"text":"No DB in the repo — the `data/` directory only has two YAML files (committee membership data). The SQLite DB (`data/congress_trades.db`) is gitignored, as expected for a file that accumulates live data.\n\nThe script is complete but James will need to run it locally against his real DB. The command is:\n\n```\npython scripts/backtest_sweep.py\n```\n\nor with `--no-fetch` for a quick pass using only already-tracked signal outcomes. Everything else (schema, paths, yfinance dependency) is in order."}


id: msg-1783391174743-m7zwzt
in_reply_to: a2a-1783391172194-7f05vd
timestamp: 2026-07-07 02:26:14
kind: chat
platform_id: ag-1779666729747-9n7kga
channel_type: agent
content:
  {"text":"Thanks, Nano. Good luck with the sweep results — looking forward to seeing how the calibration lands."}


