Introduction
# Polymarket Trader
Maintain a profitable **BTC 1h Up/Down** strategy by anchoring decisions to **Binance BTCUSDT** (the resolution source) and enforcing anti-churn/risk rules.
## Workflow (use this order)
1) **Confirm the market type** - This skill is optimized for `bitcoin-up-or-down-*` 1h markets (Binance 1H open vs close).
2) **Compute the anchor signal (Binance)** - Fetch 1m closes + the 1h open for the relevant hour. - Compute volatility (sigma) and time-to-expiry. - Convert to **fair probability** for Up/Down.
3) **Trade only when there is measurable edge** - Enter only if `edge = fair_prob - market_price` exceeds a threshold. - Add a directional guardrail: do not bet against the sign of the move when |z| is non-trivial.
4) **Exit using the right logic for the entry mode** - Model entries: exit on **edge decay / model flip**; hold to preclose when confidence is extreme. - Mean-reversion entries: exit on **reversion targets** (not model-tp), with strict churn limits.
5) **Validate with logs** - Every suspected “nonsense trade” must be explained via: - `reason` / `entry_mode` - Binance-derived fair probability + z - whether the correct exit block fired
## Bundled scripts
All scripts are designed to be run from the OpenClaw workspace.
### 1) Fetch Binance klines - `{baseDir}/scripts/binance_klines.py` - Pulls klines and prints JSON.
### 2) Dump/stabilization and regime metrics - `{baseDir}/scripts/binance_regime.py` - Computes ret5/ret15/slope10 + simple “stabilized” boolean.
### 3) Explain fills (events.jsonl) with Binance context - `{baseDir}/scripts/explain_fills.py` - Reads paperbot `events.jsonl` and prints a concise table for the last N fills: - side/outcome/px/reason - estimated fair_up + z - “against trend?” flag
## References
- `{baseDir}/references/strategy.md` — the math model, parameters, and tuning checklist.