S&P 500 Up/Down Markets 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.
S&P 500 Up/Down Markets is structured for quant research from day one. Resolved Markets captures S&P 500 daily open prediction markets with tick-level capture of equity index prediction contracts, then ships the result as a 14-column schema that maps directly into pandas, R, and ClickHouse. Quant researchers can study SPX daily-open up/down resolution markets without rebuilding the data layer.
Data challenges Quantitative Researchers run into
S&P 500 Up/Down Markets from Resolved Markets is built around the data gaps Quantitative Researchers hit when they try to work with raw Polymarket feeds.
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.
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.
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.
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 S&P 500 Up/Down Markets
Orderbook-level prediction-market data that doesn't exist anywhere else.
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.
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.
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.
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.
How Quantitative Researchers use S&P 500 Up/Down Markets
Seven categories, hundreds of markets
Prediction markets across crypto, sports, economics, weather, and more — live and historical orderbook data, all queryable through one API.
Crypto
BTC, ETH, SOL, XRP — up/down markets every 5m to 1d.
Equities
S&P 500 (SPX) daily open — up or down predictions.
Social
Elon Musk tweet counts — weekly prediction ranges.
Sports
NBA, NFL, EPL — game outcomes and season predictions.
Economics
Fed decisions, jobs reports — FOMC meetings and macro data.
Weather
44 cities daily — temperature, hurricanes, Arctic ice.
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.
| Side | Bid | Size | Ask | Size | Spread |
|---|---|---|---|---|---|
| UP | 0.5400 | 1,240 | 0.5500 | 1,100 | 1.00% |
| UP | 0.5300 | 980 | 0.5600 | 1,450 | 3.00% |
| UP | 0.5200 | 1,560 | 0.5700 | 890 | 5.00% |
| UP | 0.5100 | 2,100 | 0.5800 | 2,300 | 7.00% |
| UP | 0.5000 | 1,800 | 0.5900 | 1,700 | 9.00% |
| UP | 0.4900 | 3,200 | 0.6000 | 3,100 | 11.00% |
cryptoLowCardinality(String)BTCtimeframeLowCardinality(String)5mtoken_sideEnum8('UP','DOWN')UPtimestampDateTime64(3)2026-05-09 03:14:12.061crypto_priceFloat64$80,471.01best_bidFloat640.5400best_askFloat640.5500mid_priceFloat640.5450spreadFloat640.0100bidsArray(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.
S&P 500 Up/Down Markets ships with
What Quantitative Researchers build with S&P 500 Up/Down Markets
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Browse 11 endpoints with live examples. Test requests directly from the docs.
API ReferenceStart Building
Integrate live S&P 500 Up/Down Markets into your research pipeline, trading bot, or analytics platform.
fetch('/v1/markets/live', { headers: { 'X-API-Key': key } })
curl -H 'X-API-Key: rm_xxx' https://api.resolvedmarkets.com/v1/categoriesrm-api download --crypto BTC --days 90 --format csvWiring S&P 500 Up/Down Markets into your workflow
Quantitative researchers typically access S&P 500 Up/Down Markets 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 S&P 500 Up/Down Markets when validating hypotheses in real time.
- Excel/Bloomberg UDF for pulling S&P 500 Up/Down Markets into existing analyst spreadsheets
- QuantConnect Lean engine adapter for backtesting on S&P 500 Up/Down Markets
- Refinitiv Eikon plugin for cross-asset workflows
Why Quantitative Researchers pick S&P 500 Up/Down Markets
- 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 S&P 500 Up/Down Markets matters
S&P 500 Up/Down Markets matters for quant research because it provides tick-level capture of equity index prediction contracts on SPX daily-open up/down resolution markets. That's the level of resolution required for proper microstructure work — and it's exactly what aggregated public datasets fail to deliver.
S&P 500 Up/Down Markets in context
Quant research on prediction markets has been bottlenecked by data quality. S&P 500 Up/Down Markets closes that gap: tick-level capture of equity index prediction contracts, full depth arrays, and a documented schema. Researchers studying SPX daily-open up/down resolution markets can finally work at the same resolution as a centralized-exchange microstructure paper.
Frequently asked: S&P 500 Up/Down Markets for Quantitative Researchers
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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.
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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.
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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.
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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.
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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.
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What is the time resolution of S&P 500 Up/Down Markets?
DateTime64(3) — millisecond precision. tick-level capture of equity index prediction contracts means quant researchers can sequence events at the same resolution they would expect from a centralized exchange feed.
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How do quant researchers ingest S&P 500 Up/Down Markets?
Resolved Markets ships S&P 500 Up/Down Markets 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.
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What research questions does S&P 500 Up/Down Markets enable?
Market microstructure analysis, volatility forecasting, liquidity dynamics, cross-market correlations, and ML model validation across the equity prediction-market space. S&P 500 Up/Down Markets pairs especially well with information-velocity and price-discovery studies.
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Does S&P 500 Up/Down Markets cover individual stocks or only indices?
S&P 500 Up/Down Markets currently covers SPX (S&P 500) daily-open up/down markets. Single-name equity prediction markets are added on demand through the enterprise tier.
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Can I import S&P 500 Up/Down Markets into a Bloomberg Terminal?
Yes, through the Excel API. S&P 500 Up/Down Markets returns JSON that maps cleanly into Bloomberg's BDP/BDH formulas via a small Excel UDF wrapper.