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

BTC Up Token Depth Charts for Quantitative Researchers

Backtest Polymarket strategies with BTC Up Token Depth Charts data — BTC Up Token Depth Charts as a structured dataset for quant research. ClickHouse + pandas ready. 7 prediction-market categories.

Depth Chart BTC Up Token Depth Charts
Mid: 0.5450 BIDS ASKS
Bids Asks
171 Live Markets
793.2M Snapshots Captured
20 Hz Capture Rate
7 Categories

BTC Up Token Depth Charts for Quantitative Researchers

Resolved Markets provides quantitative researchers with unprecedented access to 11.4M+ prediction market orderbook snapshots, enabling rigorous analysis of market microstructure, price discovery mechanisms, and information cascades across crypto, sports, economics, and weather categories. The platform's ClickHouse-backed historical storage allows rapid queries across months of full bid/ask depth data with millisecond timestamps, supporting hypothesis testing without the sampling bias of traditional prediction market datasets. Researchers benefit from WebSocket streaming for live capture and REST APIs for batch analysis, enabling both real-time market observations and deep historical investigations into how information propagates through Polymarket.

Quant teams reach for BTC Up Token Depth Charts when they need orderbook microstructure that public datasets don't expose. Resolved Markets provides 20Hz capture against live crypto spot prices across BTC up/down tokens, ETH 1h settlements, SOL daily markets, with documented methodology and reproducible exports — the building blocks of empirical microstructure research.

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 Quantitative Researchers run into

BTC Up Token Depth Charts from Resolved Markets is built around the data gaps Quantitative Researchers hit when they try to work with raw Polymarket feeds.

01

Prediction market datasets typically lack orderbook depth information

Published prediction market datasets (Manifold, CPMM datasets) provide only aggregate trade volumes or final outcomes, omitting the rich orderbook structure that reveals price discovery mechanisms. Researchers cannot analyze bid/ask spreads, order accumulation patterns, or market depth changes—the very microstructure that reveals when informed traders enter markets. Resolved Markets captures complete depth arrays, enabling investigation of information asymmetry and market efficiency questions that remain unanswerable with standard datasets.

02

Millisecond-precision timestamps unavailable from alternative sources

Academic research on prediction markets requires precise timing to correlate information arrivals with price movements. Standard prediction market APIs provide second-level or day-level timestamps, obscuring the millisecond-scale price discovery process. Resolved Markets' millisecond-precision timestamps enable sophisticated event-study methodologies, allowing researchers to measure how quickly Polymarket incorporates external information (news, sports outcomes, economic reports) into prediction prices.

03

Cross-category market analysis requires manual data fusion

Prediction market dynamics vary dramatically across crypto, sports, economics, and weather—but assembling a unified dataset requires independently scraping each category or using fragmented APIs. Manual data fusion introduces inconsistencies in timestamp precision, orderbook representation, and market coverage. Resolved Markets provides standardized orderbook snapshots across all 100+ tracked markets, eliminating data integration work and enabling cross-category analysis of market efficiency and herding behavior.

04

Real-time and historical data require separate infrastructure

Traditional research workflows separate real-time observation (for validating hypotheses on live markets) from historical analysis (for deep investigations). This split requires maintaining two separate data pipelines. Resolved Markets unifies real-time WebSocket streams and historical batch queries into a single API, allowing researchers to seamlessly transition from exploratory analysis of live markets to rigorous backtesting against months of historical orderbook data.

Built for quantitative work on BTC Up Token Depth Charts

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

01

Investigate price discovery mechanisms at millisecond resolution

Price discovery happens at the orderbook level—before trades execute, bids and asks reveal trader intentions. With full depth arrays and millisecond timestamps, you can track how orders accumulate before price moves, quantify bid/ask asymmetry changes, and measure how quickly informed orders push prices toward fair value. Analyze moments when sudden order cancellations precede price reversals, revealing strategic order placement and information cascades invisible in trade-level data.

02

Analyze orderbook microstructure across 100+ markets simultaneously

Prediction markets exhibit distinct microstructure across categories: crypto markets show high-frequency trading dynamics, sports markets experience demand surges near game time, economics markets react to scheduled data releases. Resolved Markets captures cross-category orderbook data with consistent timestamping, enabling comparative studies of information flow and market maturity. Quantify whether crypto prediction markets are more efficient than sports or economics markets by analyzing order speed, spread compression, and depth changes.

03

Test market efficiency hypotheses with unbiased historical data

Published datasets introduce sampling bias—researchers often access only final outcomes or aggregate statistics, not the continuous orderbook snapshots that define true price paths. Resolved Markets' 11.4M+ snapshots covering months of data eliminate survivor bias and provide the complete information set available to market participants at any moment. Historical queries directly reveal when arbitrage opportunities existed, whether informed traders exploited them, and how quickly prices converged to fundamental values.

04

Publish reproducible research with timestamped, auditable datasets

Reproducible research requires datasets that can be audited and independently verified. Resolved Markets provides timestamped, immutable orderbook snapshots stored in ClickHouse with query-transparent access—you can export exact data used in analyses, enabling other researchers to validate findings or extend work. REST API batch exports include snapshot checksums, ensuring data integrity across research teams and publications.

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 Quantitative Researchers use BTC Up Token Depth Charts

1
Test informed-trading models by detecting order flow patterns inside BTC Up Token Depth Charts
2
Construct liquidity measures from full depth arrays exposed by BTC Up Token Depth Charts
3
Deploy a Cloudflare Worker that proxies BTC Up Token Depth Charts into your own custom JSON shape for downstream consumers
4
Run a Jupyter notebook study correlating BTC Up Token Depth Charts with on-chain metrics from Glassnode and Dune Analytics
5
Build a Telegram bot that pings you when Polymarket BTC up/down markets diverge from CoinGecko spot by more than 50 bps

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

BTC Up Token Depth Charts ships with

11.4M+ historical orderbook snapshots in ClickHouse
Full bid/ask depth arrays with millisecond timestamps
Cross-market analysis across 100+ Polymarket categories
REST API for exploratory data analysis
WebSocket streaming for real-time observations
Batch export functionality for research pipelines

What Quantitative Researchers build with BTC Up Token Depth Charts

Cross-market efficiency testing between prediction markets and traditional asset classes
Herding behavior detection through order clustering inside BTC Up Token Depth Charts
ML-based regime detection (trending vs ranging) using BTC Up Token Depth Charts order flow features
Whale order accumulation detection through anomalous depth growth at single price levels
Latency arbitrage measurement comparing BTC Up Token Depth Charts timestamps against centralized exchange tape

Up and running in minutes

Three steps from signup to live BTC Up Token Depth Charts 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 BTC Up Token Depth Charts into your research pipeline, trading bot, or analytics platform.

fetch('/v1/markets/live', { headers: { 'X-API-Key': key } })
1
Create a free API key at resolvedmarkets.com — researchers get extended history depth
2
Explore available markets: curl -H 'X-API-Key: rm_xxx' https://api.resolvedmarkets.com/v1/categories
3
Query historical BTC Up Token Depth Charts with time-range filters for your research window
4
Export datasets via CLI: rm-api download --crypto BTC --days 90 --format csv
5
Load into your analysis pipeline (Python/R/MATLAB) for statistical testing

Wiring BTC Up Token Depth Charts into your workflow

Quantitative researchers typically access BTC Up Token Depth Charts through the REST API for exploratory work, then switch to ClickHouse bulk exports for large-scale studies. The 14-column schema maps directly to pandas DataFrames and R data.frames. WebSocket streaming supports live observation of BTC Up Token Depth Charts when validating hypotheses in real time.

  • pip install resolvedmarkets — one-line Python SDK with async iterators for BTC Up Token Depth Charts streams
  • npm install resolved-markets — TypeScript SDK with full type definitions for the 14-column schema
  • cargo add resolved-markets — Rust crate for ultra-low-latency consumers

Why Quantitative Researchers pick BTC Up Token Depth Charts

  • Only academic-grade dataset capturing complete orderbook depth from 11.4M+ Polymarket snapshots with millisecond timestamps
  • ClickHouse-backed historical storage enables rapid hypothesis testing across months of data without sampling bias
  • Cross-category coverage (crypto, sports, economics, weather) reveals comparative market microstructure insights unavailable elsewhere
  • Unified real-time and historical APIs eliminate infrastructure fragmentation—observe live markets while backtesting against complete historical orderbooks

Why BTC Up Token Depth Charts matters

Quant researchers reach for BTC Up Token Depth Charts because Resolved Markets ships it as a reproducible, documented dataset. Methodology, schema, and timestamps are all published, so studies built on BTC Up Token Depth Charts can be replicated by other teams without infrastructure overhead.

BTC Up Token Depth Charts in context

Quant research on prediction markets has been bottlenecked by data quality. BTC Up Token Depth Charts closes that gap: 20Hz capture against live crypto spot prices, full depth arrays, and a documented schema. Researchers studying BTC up/down tokens, ETH 1h settlements, SOL daily markets can finally work at the same resolution as a centralized-exchange microstructure paper.

Frequently asked: BTC Up Token Depth Charts for Quantitative Researchers

  • How comprehensive is the orderbook depth data—do you capture all orders or just top-N levels?

    Resolved Markets captures complete bid/ask depth arrays showing all resting orders at each price level, not just the top 5 or top 20 levels. This enables full microstructure analysis including visualization of iceberg orders, detection of spoofing (fake orders designed to manipulate prices), and measurement of true market liquidity across all price levels. Each snapshot includes full depth with millisecond precision.

  • Can I query historical data for specific time windows, or must I download all 11.4M snapshots?

    Resolved Markets provides REST API query functions supporting time-range filtering, market symbol filtering, and orderbook metric calculations (spreads, depth, order counts). Query a single sports market during game hours, or aggregate across all crypto markets during a specific 24-hour window. ClickHouse backend enables sub-second query response times even against months of historical data—you're not limited to batch downloads.

  • Are timestamp precision and consistency guaranteed across all markets and the full dataset?

    Yes—all 11.4M snapshots include millisecond-precision timestamps captured at the moment of orderbook state validation. Timestamp precision is consistent across crypto (20Hz), sports (regular intervals), economics, and weather categories. Data lineage is fully documented, enabling you to cite exact data provenance in publications and validate timestamp accuracy against Polymarket's canonical time sources.

  • How can I use Resolved Markets for publication-quality research if it's a commercial API?

    Academic researchers receive free tier access with unlimited query depth, exportable datasets, and versioned snapshots for reproducibility. Export your research dataset with query parameters and snapshot checksums, enabling other researchers to independently validate findings against the same data. We document our data collection and validation methodology in a public technical paper, meeting standards for academic transparency.

  • Can I analyze how different information sources (news, sports outcomes, economic data) affect prediction market orderbooks?

    Yes—combine Resolved Markets' millisecond-precision orderbook timestamps with external event data (news APIs, sports schedules, economic calendars). Correlate sudden spread compression or order cancellations with external information arrivals to measure information velocity. Our REST API supports datetime range queries enabling event-study methodologies—identify the exact moment markets absorb information by analyzing orderbook changes in millisecond windows around known event times.

  • How do quant researchers ingest BTC Up Token Depth Charts?

    Resolved Markets ships BTC Up Token Depth Charts as a 14-column ClickHouse schema. Bid/ask arrays, depth values, and DateTime64(3) timestamps map directly into pandas DataFrames or R tibbles for downstream microstructure work.

  • What research questions does BTC Up Token Depth Charts enable?

    Market microstructure analysis, volatility forecasting, liquidity dynamics, cross-market correlations, and ML model validation across the crypto orderbook ecosystem. BTC Up Token Depth Charts pairs especially well with information-velocity and price-discovery studies.

  • How is BTC Up Token Depth Charts different from existing prediction-market datasets?

    Most public prediction-market datasets capture only final outcomes or hourly OHLC. BTC Up Token Depth Charts from Resolved Markets is continuous, with full bid/ask arrays and 20Hz capture against live crypto spot prices. That makes it usable for true microstructure research.

  • Is there a Python SDK for BTC Up Token Depth Charts?

    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 BTC Up Token Depth Charts 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

Ready to access BTC Up Token Depth Charts?

Get live orderbook data from Polymarket. Free API key, no credit card required.