alteregoeth-ai
128 lines
4.2 KiB
Markdown
128 lines
4.2 KiB
Markdown
# 🌤 WeatherBet — Polymarket Weather Trading Bot
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Automated weather market trading bot for Polymarket. Finds mispriced temperature outcomes using real forecast data from multiple sources across 20 cities worldwide.
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No SDK. No black box. Pure Python.
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---
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## Versions
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### `bot_v1.py` — Base Bot
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The foundation. Scans 6 US cities, fetches forecasts from NWS using airport station coordinates, finds matching temperature buckets on Polymarket, and enters trades when the market price is below the entry threshold.
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No math, no complexity. Just the core logic — good for understanding how the system works.
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### `weatherbet.py` — Full Bot (current)
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Everything in v1, plus:
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- **20 cities** across 4 continents (US, Europe, Asia, South America, Oceania)
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- **3 forecast sources** — ECMWF (global), HRRR/GFS (US, hourly), METAR (real-time observations)
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- **Expected Value** — skips trades where the math doesn't work
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- **Kelly Criterion** — sizes positions based on edge strength
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- **Stop-loss + trailing stop** — 20% stop, moves to breakeven at +20%
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- **Slippage filter** — skips markets with spread > $0.03
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- **Self-calibration** — learns forecast accuracy per city over time
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- **Full data storage** — every forecast snapshot, trade, and resolution saved to JSON
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---
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## How It Works
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Polymarket runs markets like "Will the highest temperature in Chicago be between 46–47°F on March 7?" These markets are often mispriced — the forecast says 78% likely but the market is trading at 8 cents.
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The bot:
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1. Fetches forecasts from ECMWF and HRRR via Open-Meteo (free, no key required)
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2. Gets real-time observations from METAR airport stations
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3. Finds the matching temperature bucket on Polymarket
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4. Calculates Expected Value — only enters if the math is positive
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5. Sizes the position using fractional Kelly Criterion
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6. Monitors stops every 10 minutes, full scan every hour
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7. Auto-resolves markets by querying Polymarket API directly
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---
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## Why Airport Coordinates Matter
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Most bots use city center coordinates. That's wrong.
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Every Polymarket weather market resolves on a specific airport station. NYC resolves on LaGuardia (KLGA), Dallas on Love Field (KDAL) — not DFW. The difference between city center and airport can be 3–8°F. On markets with 1–2°F buckets, that's the difference between the right trade and a guaranteed loss.
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| City | Station | Airport |
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|------|---------|---------|
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| NYC | KLGA | LaGuardia |
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| Chicago | KORD | O'Hare |
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| Miami | KMIA | Miami Intl |
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| Dallas | KDAL | Love Field |
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| Seattle | KSEA | Sea-Tac |
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| Atlanta | KATL | Hartsfield |
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| London | EGLC | London City |
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| Tokyo | RJTT | Haneda |
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| ... | ... | ... |
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---
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## Installation
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```bash
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git clone https://github.com/alteregoeth-ai/weatherbot
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cd weatherbot
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pip install requests
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```
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Create `config.json` in the project folder:
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```json
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{
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"balance": 10000.0,
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"max_bet": 20.0,
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"min_ev": 0.05,
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"max_price": 0.45,
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"min_volume": 2000,
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"min_hours": 2.0,
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"max_hours": 72.0,
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"kelly_fraction": 0.25,
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"max_slippage": 0.03,
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"scan_interval": 3600,
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"calibration_min": 30,
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"vc_key": "YOUR_VISUAL_CROSSING_KEY"
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}
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```
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Get a free Visual Crossing API key at visualcrossing.com — used to fetch actual temperatures after market resolution.
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---
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## Usage
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```bash
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python weatherbet.py # start the bot — scans every hour
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python weatherbet.py status # balance and open positions
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python weatherbet.py report # full breakdown of all resolved markets
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```
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---
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## Data Storage
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All data is saved to `data/markets/` — one JSON file per market. Each file contains:
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- Hourly forecast snapshots (ECMWF, HRRR, METAR)
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- Market price history
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- Position details (entry, stop, PnL)
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- Final resolution outcome
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This data is used for self-calibration — the bot learns forecast accuracy per city over time and adjusts position sizing accordingly.
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---
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## APIs Used
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| API | Auth | Purpose |
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|-----|------|---------|
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| Open-Meteo | None | ECMWF + HRRR forecasts |
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| Aviation Weather (METAR) | None | Real-time station observations |
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| Polymarket Gamma | None | Market data |
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| Visual Crossing | Free key | Historical temps for resolution |
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---
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## Disclaimer
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This is not financial advice. Prediction markets carry real risk. Run the simulation thoroughly before committing real capital.
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