Climate & Weather Trader

This is a template.
The default signal is keyword discovery + NOAA/weather API data alignment — remix it with ForecastEx climate oracle feeds, satellite NDVI data for agriculture, or ensemble weather model outputs.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Climate prediction markets are one of the fastest-growing underserved categories. Polymarket has 151+ active climate markets but most are basic. This skill captures alpha on:

• Temperature extremes — record highs, heatwaves, frost events
• Natural catastrophes — hurricane counts, earthquake magnitudes, wildfire acreage
• Climate milestones — CO2 ppm thresholds, Arctic sea ice minimums
• Agricultural impacts — wheat yields, drought-driven crop failures, water allocations

Climate markets are uniquely suited for quantitative trading: the data sources are public, verifiable, and highly structured (NOAA, ECMWF, NASA).

Signal Logic

Default Signal: Conviction-Based Sizing with Seasonal Bias

1. Discover active climate/weather markets on Polymarket
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply season_bias() multiplier based on current month and event type in the question
4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAX_POSITION
5. Skip markets with spread > MAX_SPREAD or fewer than MIN_DAYS to resolution

Seasonal Bias (built-in, no API required)

Climate events follow documented seasonal cycles. season_bias() boosts conviction when the current month aligns with peak season, and dampens it off-season:

Example: a hurricane market at 25% in October → conviction 34% × 1.4x bias = 48% → $12 position. Same market in January → 34% × 0.6x = 20% → $5 (floor).

Remix Ideas

• ECMWF ensemble: Replace market.current_probability with model consensus probability — trade the divergence between forecast and market
• NOAA ENSO index: Feed ONI values directly to boost/reduce season_bias() for El Niño markets
• Insurance cat bond pricing: Use ILS spreads as implied probability benchmarks for hurricane markets
• Copernicus climate data: Real-time European climate services for local/regional temperature markets

Market Categories Tracked

KEYWORDS = [
    'hurricane', 'tropical storm', 'cyclone', 'tornado', 'flood',
    'drought', 'wildfire', 'earthquake', 'CO2', 'sea ice', 'Arctic',
    'El Niño', 'La Niña', 'ENSO', 'snowfall', 'heatwave', 'heat wave',
    'temperature record', 'crop yield', 'wheat', 'harvest', 'glacier',
    'rainfall', 'water shortage', 'climate', 'emissions', 'carbon',
]

Risk Parameters

Key Data Sources

• NOAA Climate Data Online: https://www.ncdc.noaa.gov/cdo-web/
• Open-Meteo API: https://open-meteo.com/ (free, no key required)
• Copernicus C3S: https://cds.climate.copernicus.eu/
• ForecastEx: https://forecastex.com/

Installation & Setup

clawhub install polymarket-climate-trader

Requires: SIMMER_API_KEY environment variable. Optional: OPENMETEO_API_KEY.

Cron Schedule

Runs every 30 minutes (*/30 * * * *). Weather data updates every 1–6 hours; no need to poll faster.

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only execute when --live is passed explicitly.

The automaton cron is set to null — it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.

Required Credentials

Tunables (Risk Parameters)

All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes. They use SIMMER_-prefixed env vars so apply_skill_config() can load them securely.

Dependency

simmer-sdk is published on PyPI by Simmer Markets. - PyPI: https://pypi.org/project/simmer-sdk/ - GitHub: https://github.com/SpartanLabsXyz/simmer-sdk - Publisher: [email protected]

Review the source before providing live credentials if you require full auditability.