Polymarket Climate Trader

Trades Polymarket prediction markets on weather extremes, climate milestones, natural disasters, and agricultural outcomes. Use when you want to capture alpha on temperature records, hurricane seasons, flood events, and CO2 threshold markets using meteorological data signals.

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:

Event type	Peak season	In-season multiplier	Off-season multiplier
Hurricane / cyclone	June–November	1.4x	0.6x
Sea ice / Arctic	July–September	1.4x	0.7x
El Niño / La Niña / ENSO	December–February	1.3x	0.9x
Wildfire / fire season	July–October	1.3x	0.8x
Heatwave / drought	June–September	1.3x	0.8x
Snowfall / blizzard	November–March	1.3x	0.7x

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

python

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

Parameter	Default	Notes
Max position size	$20 USDC	Per market
Min market volume	$3,000	Climate markets are less liquid
Max bid-ask spread	12%	Wider allowed for niche markets
Min days to resolution	14	Weather requires sufficient lead time
Max open positions	8	Diversify across events

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

bash

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.

Scenario	Mode	Financial risk
python trader.py	Paper (sim)	None
Cron / automaton	Paper (sim)	None
python trader.py --live	Live (polymarket)	Real USDC

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

Variable	Required	Notes
SIMMER_API_KEY	Yes	Trading authority — keep this credential private. Do not place a live-capable key in any environment where automated code could call --live.

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.

Variable	Default	Purpose
SIMMER_MAX_POSITION	25	Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_VOLUME	3000	Min market volume filter (USD)
SIMMER_MAX_SPREAD	0.12	Max bid-ask spread (0.12 = 12%)
SIMMER_MIN_DAYS	14	Min days until market resolves
SIMMER_MAX_POSITIONS	8	Max concurrent open positions
SIMMER_YES_THRESHOLD	0.38	Buy YES if market price ≤ this value
SIMMER_NO_THRESHOLD	0.62	Sell NO if market price ≥ this value
SIMMER_MIN_TRADE	5	Floor for any trade (min USDC regardless of conviction)

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: [e-mail]

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