BTC$80,471.01 ETH$2,319.15 SOL$93.66 XRP$1.43 SPX18 markets Elon71 markets NBA64 markets NFL46 markets EPL18 markets FOMC12 markets Weather44 cities Hyperliquid4 perps
Live Polymarket Feed · 171 active markets

Crypto Spot Price Pairing for Weather Derivatives Traders

Backtest Polymarket strategies with Crypto Spot Price Pairing data — Crypto Spot Price Pairing for weather derivatives. Daily orderbook depth on Polymarket weather contracts.

Depth Chart Crypto Spot Price Pairing
Mid: 0.5450 BIDS ASKS
Bids Asks
171 Live Markets
793.2M Snapshots Captured
20 Hz Capture Rate
7 Categories

Crypto Spot Price Pairing for Weather Derivatives Traders

Weather derivatives traders access Resolved Markets to monitor continuous orderbook snapshots for 30 cities' daily weather prediction contracts on Polymarket. The platform captures full bid/ask depth across temperature, precipitation, and condition markets with millisecond-precision timestamps, enabling traders to identify probability shifts before major weather systems move. With 11.4M+ historical snapshots and 20Hz capture rates, traders can model weather sentiment evolution, detect hedging flows from agricultural and energy participants, and correlate prediction market repricing with commodity futures. The unified API provides seamless integration with commodities, energy, and agriculture portfolios, making Resolved Markets essential infrastructure for weather derivative strategy implementation.

Crypto Spot Price Pairing from Resolved Markets pairs Polymarket weather markets with structured orderbook depth. 20Hz capture against live crypto spot prices delivers daily snapshots of BTC up/down tokens, ETH 1h settlements, SOL daily markets, giving weather desks a parallel pricing source for hedging and speculation.

Live snapshot: Resolved Markets is currently tracking 171 active Polymarket contracts and has captured 793.2M orderbook snapshots. Latest update: 2026-05-09 03:14:12.061.

Data challenges Weather Derivatives Traders run into

Crypto Spot Price Pairing from Resolved Markets is built around the data gaps Weather Derivatives Traders hit when they try to work with raw Polymarket feeds.

01

Weather forecasts from meteorological services lack market pricing insights

Traditional weather data comes from meteorological services (NWS, NOAA) providing probabilistic forecasts: '70% chance of rain.' But these forecasts ignore how market participants actually value weather outcomes. A 70% rain forecast might translate to 40% odds in derivative markets if precipitation would help crops (bullish for farmers) but only 20% if it would damage already-wet fields. Resolved Markets shows the market's true pricing via Polymarket orderbooks, revealing sophisticated participants' risk assessments you can trade against.

02

Delayed hedging flow detection from agricultural and energy markets

Agricultural hedgers and energy traders react to weather prediction changes hours or days before those changes appear in meteorological models. Polymarket weather prediction markets represent early sentiment about weather development. When major hedge funds start buying 'warm tomorrow' contracts, they're detecting climate pattern shifts before forecasters. Resolved Markets' 20Hz capture in crypto markets shows microsecond-scale sentiment shifts; weather markets reveal similar timing in macro sentiment. Traders who detect these hedging flows first gain edge.

03

Difficulty quantifying uncertainty in weather outcomes across multiple timeframes

Single-point probability estimates (70% rain) oversimplify reality. Weather outcomes have distributions: 'Most likely 2-3 inches, but 10% tail risk of 6+ inches.' Orderbook structure reveals this: dense clustering at certain temperature/precipitation levels indicates consensus, while wide spreads at extreme outcomes indicate uncertainty. Resolved Markets provides full depth arrays showing exactly where the market clusters conviction and where tail risk is priced. This distribution view is impossible from point forecasts.

04

Limited history of prediction market prices for weather-driven derivatives

Most weather derivative platforms don't maintain historical price data. Your models can't backtest strategies using prediction market repricing patterns, because those patterns aren't archived. Resolved Markets maintains 11.4M+ snapshots across all tracked weather markets. Train models on how orderbook depth evolved before major storms, how spreads expanded during uncertainty windows, and how quickly consensus formed as outcomes crystallized.

Built for quantitative work on Crypto Spot Price Pairing

Orderbook-level prediction-market data that doesn't exist anywhere else.

01

Millisecond-precision tracking of weather outcome probabilities across 30 cities

Meteorological forecasts update every 6-12 hours. Resolved Markets updates every snapshot (variable frequency for weather, but continuous monitoring). When a major weather system intensifies unexpectedly, prediction markets often detect it within hours via orderbook shifts. Temperature and precipitation contracts reprices as sophisticated participants (agricultural hedgers, energy traders) update expectations. Your algorithms detect these repricing patterns minutes or hours before official forecast updates, enabling edge on derivative positioning.

02

Full bid/ask depth reveals market consensus and tail risk distribution shapes

The orderbook depth distribution reveals risk perception. When rain probability contracts show tight clustering at 60-65% odds with sparse offers below 40%, the market has consensus that rain is likely, but tail risks (severe drought) are severely underpriced by consensus and overpriced by hedgers. This shape is invisible in point estimates. Resolved Markets' depth arrays let you engineer features on spread shape, concentration, and tail density—precise tools for weather risk pricing.

03

11.4M+ historical snapshots enable weather pattern prediction model development

Train machine learning models on 11.4M+ snapshots to predict weather market repricing patterns. Sequences like 'temperatures rising from 72F to 75F likelihood, precipitation falling from 35% to 25%, and volatility expanding' predict specific outcomes in the next 24 hours. Backtest across diverse weather seasons (winter storms, summer droughts, hurricane season) to build models robust to regime changes. Deploy live predictions via WebSocket to detect similar patterns in real-time.

04

Early hedging flow detection from agricultural and energy market participants

Commodity futures (corn, wheat, crude oil, natural gas) are driven substantially by weather. When Polymarket weather derivatives for agricultural regions suddenly reprice, sophisticated traders know commodity volatility is coming. Resolved Markets enables you to monitor all 30 weather cities simultaneously, detect probability shifts before commodity markets overreact, and position ahead of agricultural seasonal demand shifts. Cross-market awareness makes you smarter about weather-driven macro hedging.

Research Applications
Spread analysis and market making simulation
Liquidity depth profiling across categories
Implied probability vs realized outcomes
Market microstructure and order flow analysis
Weather derivative research across 44 cities
Cross-category correlation studies

How Weather Derivatives Traders use Crypto Spot Price Pairing

1
Hedge agricultural exposure using Crypto Spot Price Pairing on temperature prediction markets
2
Price climate risk for energy desks using Polymarket consensus
3
Generate weekly PDF reports on Crypto Spot Price Pairing for crypto fund LPs using nbconvert and matplotlib
4
Stream Crypto Spot Price Pairing into a Kafka topic for downstream consumers running Flink or Spark Structured Streaming
5
Use Crypto Spot Price Pairing as input features for a PyTorch transformer trained on hourly crypto direction labels

Seven categories, hundreds of markets

Prediction markets across crypto, sports, economics, weather, and more — live and historical orderbook data, all queryable through one API.

16 markets

Crypto

BTC, ETH, SOL, XRP — up/down markets every 5m to 1d.

18 markets

Equities

S&P 500 (SPX) daily open — up or down predictions.

71 markets

Social

Elon Musk tweet counts — weekly prediction ranges.

64 markets

Sports

NBA, NFL, EPL — game outcomes and season predictions.

12 markets

Economics

Fed decisions, jobs reports — FOMC meetings and macro data.

78 markets

Weather

44 cities daily — temperature, hurricanes, Arctic ice.

4 pairs

Hyperliquid

BTC, ETH, SOL, XRP perp orderbooks — 1/sec sampling.

Tick-level orderbook snapshots

Every snapshot includes full bid/ask depth, mid prices, spreads, and crypto spot price.

polymarket.snapshots_hf 793.2M rows
SideBidSizeAskSizeSpread
UP0.54001,2400.55001,1001.00%
UP0.53009800.56001,4503.00%
UP0.52001,5600.57008905.00%
UP0.51002,1000.58002,3007.00%
UP0.50001,8000.59001,7009.00%
UP0.49003,2000.60003,10011.00%
Schema 14 columns
cryptoLowCardinality(String)BTC
timeframeLowCardinality(String)5m
token_sideEnum8('UP','DOWN')UP
timestampDateTime64(3)2026-05-09 03:14:12.061
crypto_priceFloat64$80,471.01
best_bidFloat640.5400
best_askFloat640.5500
mid_priceFloat640.5450
spreadFloat640.0100
bidsArray(Tuple(F64,F64))[(0.54,1240),...]
asksArray(Tuple(F64,F64))[(0.55,1100),...]

Comprehensive market coverage

Prediction markets across multiple categories, captured continuously with high-frequency precision.

7
Categories
Crypto Sports Economics Weather
171
Active Markets
BTC ETH SOL XRP + sports, econ, weather
44
Weather Cities
Daily prediction-market capture across global cities.
20 Hz
Capture Rate
Crypto 20 Hz Sports 2 Hz Econ 1 Hz

Crypto Spot Price Pairing ships with

Real-time orderbook streaming for 30-city weather prediction markets via WebSocket
Full bid/ask depth showing temperature, precipitation, and condition forecasts with millisecond timestamps
Historical weather prediction snapshots for backtesting and pattern analysis
Cross-correlation analysis between weather prediction repricing and commodity futures moves
Weather event probability extraction from prediction market consensus
Portfolio integration tools for hedging agricultural and energy positions

What Weather Derivatives Traders build with Crypto Spot Price Pairing

Hurricane probability tracking through Crypto Spot Price Pairing
Arctic ice and climate outcome research
Order flow toxicity scoring (VPIN) on Polymarket crypto contracts
PnL attribution separating spread capture from inventory risk in market-making sims
Backtests of stat-arb pairs trades between BTC and ETH prediction markets

Up and running in minutes

Three steps from signup to live Crypto Spot Price Pairing in your application.

1

Get Your API Key

Generate a free API key instantly. No credit card. Just click and go.

Sign Up Free
2

Explore the API

Browse 11 endpoints with live examples. Test requests directly from the docs.

API Reference
3

Start Building

Integrate live Crypto Spot Price Pairing into your research pipeline, trading bot, or analytics platform.

fetch('/v1/markets/live', { headers: { 'X-API-Key': key } })
1
Get a free API key at resolvedmarkets.com
2
List weather markets: curl -H 'X-API-Key: rm_xxx' 'https://api.resolvedmarkets.com/v1/markets/live' | jq '.[] | select(.category=="weather")'
3
Pull daily Crypto Spot Price Pairing snapshots for relevant cities
4
Stream updates over WebSocket during storm events
5
Bulk download historical Crypto Spot Price Pairing: rm-api download --category weather --days 90

Wiring Crypto Spot Price Pairing into your workflow

Weather desks integrate Crypto Spot Price Pairing via REST for daily snapshot pulls, WebSocket for live storm-event tracking, and the CLI for historical seasonal studies.

  • Native ClickHouse connector via JDBC/ODBC for direct SQL queries against historical Crypto Spot Price Pairing
  • Kafka Connect sink for piping Crypto Spot Price Pairing into your existing event-streaming infrastructure
  • pip install resolvedmarkets — one-line Python SDK with async iterators for Crypto Spot Price Pairing streams

Why Weather Derivatives Traders pick Crypto Spot Price Pairing

  • 30-city weather prediction market coverage with full orderbook depth reveals market consensus and tail risk distributions impossible to see in point forecasts
  • 20Hz-equivalent capture rates and millisecond timestamps enable detection of hedging flows and sentiment shifts hours before meteorological forecast updates
  • 11.4M+ historical snapshots with temperature, precipitation, and condition outcomes enable training of weather market repricing prediction models
  • Unified API enables correlation analysis between weather prediction repricing and commodity futures, unlocking cross-asset hedging strategies

Why Crypto Spot Price Pairing matters

Crypto Spot Price Pairing matters for weather trading because physical exposure needs a parallel pricing source. 20Hz capture against live crypto spot prices on BTC up/down tokens, ETH 1h settlements, SOL daily markets delivers exactly that, in a structured daily feed.

Crypto Spot Price Pairing in context

Weather derivatives have always been data-constrained. Crypto Spot Price Pairing from Resolved Markets adds prediction-market consensus to the modeling toolkit, with 20Hz capture against live crypto spot prices on BTC up/down tokens, ETH 1h settlements, SOL daily markets providing daily structured snapshots.

Frequently asked: Crypto Spot Price Pairing for Weather Derivatives Traders

  • How does Polymarket weather data compare to meteorological forecasts like NOAA?

    NOAA provides scientific forecasts ('65% chance of rain'), but doesn't price risk. Polymarket reveals how markets value that risk: maybe rain probability is priced at 40% despite NOAA's 65%, indicating sophisticated traders think NOAA is wrong. Or rain might be 80% in Polymarket while NOAA says 65%, showing hedgers are over-pricing tail risk. Resolved Markets gives you the market's probability estimate, which differs materially from scientific forecasts and creates trading opportunities.

  • Can we detect agricultural hedging flows through weather prediction markets?

    Yes, this is a primary use case. When farmers face drought risk, they buy rain probability contracts (they profit if rain falls). Large buys on rain outcomes signal hedging demand. Resolved Markets' orderbook snapshots show exactly when large buy orders appear, their sizes, and implied volume. You can model: 'Large buy orders appeared on rain outcomes for Midwest cities 2 days before corn futures rallied.' Detect these patterns in real-time to frontrun commodity moves.

  • What's the geographic coverage of the 30-city weather tracking?

    Our 30 cities span major agricultural regions (Midwest corn belt), energy production centers (Texas, Gulf Coast), population centers (NYC, LA, Chicago), and commodity exchange hubs. Coverage includes US dominance with strategic global cities. Each city has continuous prediction contracts for temperature ranges, precipitation probability, and weather conditions. The API allows you to query by city, region, or all 30 simultaneously. Custom coverage can be discussed for specific hedging portfolios.

  • How far in advance do weather prediction markets reprice ahead of storms?

    Historical data shows repricing typically accelerates 48-72 hours before major weather events, as meteorological models converge on potential outcomes. Polymarket participants start positioning as confidence increases. Resolved Markets' historical archive enables you to backtest: train models on the sequence of repricing patterns (spread widening, then narrowing as consensus forms) to detect emerging storms. In real-time, WebSocket streaming lets you track probability evolution, set alerts when repricing accelerates.

  • Can we correlate weather prediction repricing with commodity futures timing?

    Yes, our API supports batch queries across multiple markets. Query weather prediction orderbooks and export to join with commodity futures data (from your existing sources). The unified timestamp ensures precise alignment. Analyze: when did Polymarket weather predictions reprice? When did commodity futures subsequently move? Build lagged correlation models. Deploy live: stream Polymarket weather updates via WebSocket, monitor for repricing patterns, and execute hedge trades in commodity futures based on the lead-lag relationships.

  • Does Crypto Spot Price Pairing include historical weather seasons?

    Yes. ClickHouse history covers months of Crypto Spot Price Pairing, allowing weather desks to study seasonal patterns and replay prior storm seasons.

  • Which weather markets does Crypto Spot Price Pairing cover?

    Crypto Spot Price Pairing spans BTC up/down tokens, ETH 1h settlements, SOL daily markets — 30-city temperature ranges, hurricane probabilities, Arctic ice limits, and other climate-related Polymarket contracts.

  • How do weather traders use Crypto Spot Price Pairing for hedging?

    Traders compare implied probabilities from Crypto Spot Price Pairing against NOAA forecasts and physical weather exposure to size hedges and price climate risk.

  • Is there a Python SDK for Crypto Spot Price Pairing?

    Yes — `pip install resolvedmarkets` gives you `from resolvedmarkets import Client`. The SDK handles auth, retry, and reconnection for both REST and WebSocket. There's also a TypeScript SDK on npm and a Rust crate on crates.io.

  • Can I run Crypto Spot Price Pairing alongside my Hyperliquid feed?

    Yes, that's a common setup. Hyperliquid provides 1Hz perp orderbook snapshots and Resolved Markets provides 20Hz Polymarket prediction-market snapshots. Most quant teams subscribe to both and join on timestamp for cross-venue analysis.

Related orderbook datasets

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