Sentiment Index Construction for Algorithmic Traders
Algorithmic traders leverage Resolved Markets to access production-grade orderbook data from Polymarket's prediction markets, enabling sophisticated quantitative strategies across crypto volatility, economic indicators, sports outcomes, and cross-market correlations. With 20Hz capture rates for crypto markets, full bid/ask depth arrays, and millisecond-precision timestamps, traders construct high-frequency algorithms that exploit orderbook dynamics, spread inefficiencies, and sentiment shifts. The 11.4M+ historical snapshots enable rigorous backtesting against realistic market conditions, while WebSocket streaming powers live deployment of algorithms that respond to orderbook changes in real-time. Integration with professional data infrastructure through REST API and ClickHouse queries enables seamless pipeline construction for trend following, mean reversion, volatility arbitrage, and market-making strategies.
Algorithmic traders backtest and deploy on Sentiment Index Construction. Resolved Markets captures research-grade prediction-market data with 11.4M+ snapshots across 7 prediction-market categories, providing the kind of clean tick history needed for mean-reversion, arbitrage, and event-driven strategies on regime detection, arbitrage backtests, sentiment indices, factor models.
Data challenges Algorithmic Traders run into
Sentiment Index Construction from Resolved Markets is built around the data gaps Algorithmic Traders hit when they try to work with raw Polymarket feeds.
Fragmented orderbook data sources limiting strategy backtesting and realism
Algorithmic traders need orderbook data at the granularity and frequency that matches their strategy timescales. Historical orderbook snapshots from multiple sources often have inconsistent timing, missing depth levels, or gaps during high-volatility periods. Resolved Markets solves this by capturing complete snapshots at 20Hz for crypto markets with zero gaps—every bid/ask level, every price tick, every volume change is recorded with millisecond precision. Backtesting algorithms against these realistic orderbooks reveals whether strategies would actually profit in production, avoiding false positives from incomplete data.
Insufficient update frequency for capturing high-frequency trading opportunities
Market-making and spread arbitrage strategies depend on capturing opportunities before other market participants. Traditional data sources update at 1-5 second intervals, missing fleeting chances where spreads widen then re-compress within seconds. Our 20Hz update rate and sub-millisecond WebSocket latency enable algorithms to react to orderbook changes faster than competitors. Crypto prediction markets on Polymarket often have temporary depth imbalances and spread widening—capturing these with 20Hz precision enables quoting strategies that profit from ephemeral dislocations.
Poor data quality and timestamp precision undermining algorithm accuracy
Timestamp precision directly impacts strategy performance, especially for algorithms that rely on correlation analysis and event timing. Millisecond errors in timestamps can distort latency measurements, corrupt correlation calculations, and introduce false causality in strategy backtests. Resolved Markets provides millisecond-precision timestamps across all 11.4M+ snapshots, enabling traders to construct accurate event windows, measure true latency distributions, and build strategies that exploit precise timing relationships between orderbook changes and price movements.
Operational overhead of maintaining multiple data infrastructure components
Maintaining custom data infrastructure for orderbook management creates operational friction—indexing blockchains, normalizing data formats, handling gaps and outages, optimizing database queries. This overhead diverts resources from strategy research and optimization. Resolved Markets eliminates this by providing production-grade infrastructure with ClickHouse-backed storage, automatic failover, and optimized query performance. Algorithms access clean, standardized data through a simple API, enabling traders to focus entirely on alpha generation rather than infrastructure maintenance.
Built for quantitative work on Sentiment Index Construction
Orderbook-level prediction-market data that doesn't exist anywhere else.
Backtest algorithms against 11.4M+ realistic historical orderbooks at millisecond precision
Rigorous backtesting separates profitable strategies from lucky noise. Resolved Markets' 11.4M+ historical snapshots with complete bid/ask depth arrays enable realistic backtesting against actual market conditions that prediction traders faced. Test your market-making algorithm against real BTC/ETH volatility orderbooks, your arbitrage algorithm against actual spread dynamics, and your position management logic against historical liquidation cascades. This historical realism reveals strategy strengths and weaknesses that idealized backtests miss, enabling confident deployment.
Deploy high-frequency strategies with 20Hz updates and sub-millisecond WebSocket latency
Live algorithmic trading requires minimal latency between market data arrival and position response. Our WebSocket API delivers orderbook updates with sub-millisecond latency, enabling algorithms to respond to spread widening, depth imbalances, and momentum shifts before other market participants. Deploy quoting algorithms that adjust bid/ask prices based on orderbook changes in real-time, arbitrage algorithms that detect cross-market price dislocations instantly, and hedge algorithms that rebalance positions at the exact moment correlation shifts emerge.
Execute complex hedging strategies using cross-market bid/ask correlations
Sophisticated traders profit from relationships between different orderbooks—when BTC volatility widens, where does capital flow? When economic expectation changes, how do prediction markets adjust? Resolved Markets' coverage across crypto, economics, and sports prediction markets enables correlation trading and hedging strategies. Build algorithms that trade BTC/ETH correlations, hedge crypto exposure using economic uncertainty markets, or arbitrage sentiment differences between prediction markets and spot price movements.
Optimize position management with real-time spread dynamics and depth visualization
Position management quality determines whether strategies survive real market stress. Use live bid/ask spread data from Resolved Markets to optimize entry/exit decisions—when spreads widen to 2%+ (indicating stress), algorithms can reduce position sizes or tighten risk limits. Construct real-time dashboards showing orderbook depth at multiple price levels, enabling traders to visualize liquidity and anticipate slippage. Monitor depth shifts that signal order arrival patterns, helping algorithms distinguish genuine trends from temporary depth imbalances.
How Algorithmic Traders use Sentiment Index Construction
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.
Sentiment Index Construction ships with
What Algorithmic Traders build with Sentiment Index Construction
Up and running in minutes
Three steps from signup to live Sentiment Index Construction in your application.
Get Your API Key
Generate a free API key instantly. No credit card. Just click and go.
Sign Up FreeExplore the API
Browse 11 endpoints with live examples. Test requests directly from the docs.
API ReferenceStart Building
Integrate live Sentiment Index Construction into your research pipeline, trading bot, or analytics platform.
fetch('/v1/markets/live', { headers: { 'X-API-Key': key } })
rm-api download --crypto BTC --days 90Wiring Sentiment Index Construction into your workflow
Algo traders prototype on REST, backfill via CLI, and deploy via WebSocket. Sentiment Index Construction flows the same way through every channel, so backtest and production share one data shape.
- Polygon.io-compatible REST shim
- QuantConnect Lean engine adapter
- Native Zipline bundle for backtesting
Why Algorithmic Traders pick Sentiment Index Construction
- 20Hz orderbook snapshots for BTC, ETH, SOL, XRP prediction markets with full bid/ask depth enabling high-frequency strategy execution and millisecond-precision backtesting
- 11.4M+ historical snapshots with complete market microstructure enabling rigorous algorithm validation against realistic Polymarket conditions
- Sub-millisecond WebSocket latency and REST API with ClickHouse backend for seamless integration into professional trading infrastructure
- Cross-market orderbook correlation data across crypto, economics, and sports for hedging, arbitrage, and portfolio optimization strategies
Why Sentiment Index Construction matters
Sentiment Index Construction matters for algorithmic trading because backtest fidelity depends on tick resolution. 11.4M+ snapshots across 7 prediction-market categories on regime detection, arbitrage backtests, sentiment indices, factor models delivers exactly the data shape strategies need to behave consistently in production.
Sentiment Index Construction in context
Algorithmic prediction-market trading depends on data quality. Sentiment Index Construction from Resolved Markets supplies 11.4M+ snapshots across 7 prediction-market categories on regime detection, arbitrage backtests, sentiment indices, factor models, eliminating the polling overhead that wrecks naive backtests.
Frequently asked: Sentiment Index Construction for Algorithmic Traders
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How can I backtest a market-making strategy using Resolved Markets historical orderbooks?
Resolved Markets stores 11.4M+ snapshots with complete bid/ask depth, prices, and millisecond timestamps. Download historical snapshots for your target market (BTC, ETH, SOL prediction markets, etc.) through the REST API or query ClickHouse directly. Reconstruct orderbooks for your backtesting period, simulate your quoting algorithm against realistic depth and spreads, and measure P&L including slippage. Compare strategy performance across different market regimes—high volatility (tight spreads), stress periods (wide spreads), and normal conditions—to validate robustness.
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What is the update latency for WebSocket orderbook streams and how do I deploy live algorithms?
Our WebSocket API delivers orderbook updates with sub-millisecond latency—typically 100-500 microseconds from snapshot capture to stream delivery. Connect your algorithm to the WebSocket endpoint for your target market, receive depth updates in JSON format, and execute position changes (place orders, cancel, adjust prices) immediately. The millisecond timestamps in each update enable precise latency tracking and correlation analysis. Live algorithms can respond to spread changes, depth imbalances, and momentum signals in real-time, competing effectively in Polymarket's prediction markets.
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Can I use Resolved Markets to detect and exploit orderbook inefficiencies?
Yes. Prediction markets often display temporary depth imbalances, wide spreads during low-activity periods, and correlation breaks between related markets. Our 20Hz updates capture these inefficiencies in real-time. Algorithms can detect when BTC/ETH orderbook correlation diverges from underlying spot price correlation, when spreads widen beyond justifiable levels, or when depth clusters at psychological price levels. Historical analysis of these patterns enables strategy development; live WebSocket streams enable real-time exploitation as inefficiencies emerge.
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How do I access historical orderbook data for BTC and ETH prediction markets?
Use the REST API or direct ClickHouse queries to access 11.4M+ historical snapshots. Specify your market (BTC up/down, ETH movement, etc.), date range, and desired time resolution. Responses include full orderbook state—bid prices, bid quantities, ask prices, ask quantities, and millisecond timestamps. Our ClickHouse backend enables fast queries across gigabytes of orderbook data, returning results in seconds. Python, JavaScript, and SQL clients can all query the API efficiently, enabling rapid backtesting workflow development.
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How can I use cross-market orderbook data for hedging and correlation trading?
Resolved Markets covers prediction markets across crypto (BTC, ETH, SOL, XRP), economics (FOMC, jobs, inflation), and sports categories. Build algorithms that monitor correlations between BTC volatility markets and economic uncertainty markets—when policy expectations shift, crypto traders often adjust positions, creating tradeable correlations. Use orderbook depth changes in one market to predict orderbook changes in correlated markets. Hedge crypto directional exposure using economic sentiment shifts. Our comprehensive market coverage enables sophisticated multi-leg strategies unavailable from single-market data providers.
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What strategy types work with Sentiment Index Construction?
Mean-reversion, arbitrage, event-driven, momentum, and statistical arbitrage strategies. Sentiment Index Construction provides the tick-level resolution these strategies require.
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How do algo traders deploy strategies on Sentiment Index Construction?
WebSocket streaming pushes live Sentiment Index Construction to running strategies. The same data shape used in backtest is used in production, eliminating training-serving skew.
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What's the historical depth of Sentiment Index Construction?
11.4M+ snapshots and growing. Sufficient for walk-forward optimization and out-of-sample validation across multiple market regimes.
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Can Sentiment Index Construction be used in a portfolio context?
Yes. Many funds treat prediction markets as an alternative sleeve and use Sentiment Index Construction as the structured data feed. Risk-parity, factor-tilting, and sentiment-overlay strategies all consume Sentiment Index Construction.
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Is there published research using Sentiment Index Construction?
Yes — academic and industry researchers have published work on prediction-market microstructure using Resolved Markets data. The dataset is documented and reproducible, which makes it suitable for peer review.