Sentiment Index Construction for Prop Trading Firms
Resolved Markets delivers institutional-grade prediction market data infrastructure enabling prop trading firms to execute systematic strategies across 100+ Polymarket contracts with microsecond precision and full orderbook transparency. The 11.4M snapshot archive (captured at 20Hz for crypto) combined with WebSocket streaming enables firms to deploy momentum, spread-capture, and latency-arbitrage algorithms while backtesting against historical orderbook dynamics. ClickHouse-backed storage supports complex analytical pipelines—reconstruct intraday trading scenarios, optimize position management across correlated markets (e.g., BTC/ETH price predictions), and extract edge from order flow microstructure. Free tier enables rapid prototyping; production scaling leverages REST API and WebSocket endpoints with sub-millisecond latency, millisecond timestamps, and full bid/ask depth, positioning firms to profitably arbitrage Polymarket inefficiencies before retail participants or slower institutional systems.
Prop desks running statistical arbitrage on Polymarket need Sentiment Index Construction at enterprise scale. Resolved Markets ships research-grade prediction-market data with 11.4M+ snapshots across 7 prediction-market categories, plus 3,000 RPM and 10 concurrent WebSocket connections for institutional throughput.
Data challenges Prop Trading Firms run into
Sentiment Index Construction from Resolved Markets is built around the data gaps Prop Trading Firms hit when they try to work with raw Polymarket feeds.
Polymarket orderbook data fragmentation prevents systematic strategy deployment
Prop firms building Polymarket strategies face critical data infrastructure gaps. Partial orderbook visibility, delayed order updates, and asynchronous data feeds force firms to operate with incomplete information, unable to reliably detect liquidity imbalances or predict short-term price moves. Without full depth arrays at high frequency (20Hz), firms cannot calibrate market-impact models accurately, leading to slippage estimates 50-200bps too optimistic and blowing trading P&L. Fragmented data across multiple Polymarket sources prevents systematic strategy scaling.
Latency opacity masks true execution slippage and opportunity cost
Understanding true execution latency is core to profitability in fast prediction markets. Most firms guess slippage from aggregate price movements, missing microsecond-level order execution realities. Without millisecond-timestamp orderbook snapshots, firms cannot measure whether their algorithms execute 10ms or 500ms after price movements, cannot quantify the cost of each millisecond delay, and cannot validate that latency optimization investments actually improve P&L. This information opacity leaves 10-50bps of potential profit untapped per trade.
Insufficient historical depth limits robust portfolio construction and risk modeling
Backtesting on incomplete or synthetic data leads to overfitted strategies that fail in live trading. Prop firms lack 11.4M+ authentic Polymarket snapshots to stress-test strategies across diverse market conditions—FOMC volatility spikes, sports outcome surprises, weekend gaps in weather predictions. Without comprehensive historical depth, strategies appear profitable in backtest yet fail when encountering real orderbook microstructure, costing firms capital and reputation during live deployment.
Orderbook microstructure patterns require manual reverse-engineering without API access
Polymarket microstructure patterns (spread clustering, order placement strategies, liquidity regimes) must be discovered through painstaking manual analysis if orderbook data is unavailable. Firms cannot systematically identify whether spreads widen predictably before outcome events, whether large orders trigger cascading revaluations, or whether latency-sensitive algorithms exploit specific market structures. Manual reverse-engineering delays competitive feature development, allowing faster-moving firms with better data access to capture alpha first.
Built for quantitative work on Sentiment Index Construction
Orderbook-level prediction-market data that doesn't exist anywhere else.
Full orderbook transparency reveals profit-taking levels and order clustering patterns
Observe every bid and ask level, discover hidden liquidity clusters, and identify price pressure points institutional traders cannot see from sparse data. Full depth arrays reveal where large Polymarket participants place orders, enabling firms to predict price moves and front-run slower traders. Identify whether spreads tighten predictably before FOMC announcements or sports outcomes, calibrate market-impact models with accuracy, and build smarter order routing that minimizes execution slippage on multi-market positions.
Millisecond precision timestamps enable latency-edge quantification and optimization
Millisecond timestamps transform latency from mystery to measurable advantage. Compare execution speed vs. Polymarket's own systems, quantify how many bps slippage each 10ms delay costs, and validate whether latency-reduction investments return positive ROI. Identify sub-millisecond trading windows before competitor algos react, execute time-sensitive spread-capture strategies during liquidity shocks, and maintain statistical edge despite crowded prediction market competition.
11.4M snapshot backtest archive validates strategy robustness across market regimes
Backtest against 11.4M authentic snapshots across all market regimes—calm markets, volatility spikes during FOMC announcements, gaps in weather data around storm events. Stress-test momentum strategies on real NFL game conclusions, validate arbitrage logic on crypto price prediction correlations, and ensure risk models accurately reflect actual drawdown patterns. Only strategies surviving authentic historical conditions survive live deployment; firms avoid expensive false positives and focus capital on genuinely profitable algorithms.
Sub-millisecond API latency positions strategies ahead of slower institutional competitors
Sub-millisecond REST API delivery and WebSocket streaming let strategies execute at institutional speeds despite retail-friendly pricing. Compete with latency-sensitive rivals by deploying on Resolved Markets' infrastructure rather than building custom data pipelines. Scale from prototyping (free tier) to production (API endpoints) without rebuilding core data infrastructure, accelerating time-to-profit and allowing allocation of engineering resources to strategy development rather than data plumbing.
How Prop Trading Firms 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 Prop Trading Firms 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 } })
Wiring Sentiment Index Construction into your workflow
Prop firms mirror Sentiment Index Construction into local ClickHouse, run backtests at sub-millisecond latency, and deploy via concurrent WebSocket connections for live multi-strategy operation.
- QuantConnect Lean engine adapter
- Native Zipline bundle for backtesting
- Polygon.io-compatible REST shim
Why Prop Trading Firms pick Sentiment Index Construction
- 11.4M orderbook snapshots + live WebSocket streaming enables robust systematic strategy development
- Millisecond precision enables latency-edge quantification and microsecond-level arbitrage execution
- Sub-millisecond API latency positions prop strategies ahead of slower institutional competitors
- Cross-category coverage (crypto, sports, economics, weather) enables diversified portfolio risk management
Why Sentiment Index Construction matters
Sentiment Index Construction matters for prop firms because institutional throughput is non-negotiable. 11.4M+ snapshots across 7 prediction-market categories on regime detection, arbitrage backtests, sentiment indices, factor models, plus enterprise rate limits and local mirroring, makes Sentiment Index Construction deployable at the scale prop desks operate.
Sentiment Index Construction in context
Prop trading on Polymarket is converging on enterprise infrastructure. Sentiment Index Construction from Resolved Markets fits that pattern with 11.4M+ snapshots across 7 prediction-market categories, local mirroring, and the throughput prop desks need to run multi-strategy operations on regime detection, arbitrage backtests, sentiment indices, factor models.
Frequently asked: Sentiment Index Construction for Prop Trading Firms
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What latency guarantee does Resolved Markets provide for live orderbook updates?
WebSocket connections deliver snapshots with sub-millisecond propagation once captured. 20Hz capture rate for crypto ensures updates at least every 50ms. REST API queries return in <100ms for typical requests. For latency-sensitive strategies, WebSocket streaming provides competitive speed vs. direct Polymarket connections. Firms can validate precise latency performance through API SLA metrics and historical latency benchmarks.
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Can I backtest momentum strategies on historical BTC price prediction orderbooks?
Yes. Query 11.4M snapshots including every BTC prediction market orderbook state, reconstruct bid/ask spread evolution, and measure price momentum at 50ms intervals. Test whether momentum signals extracted from one orderbook state predict price moves within the next snapshot. Validate strategy robustness across different volatility regimes, measure typical execution slippage, and optimize entry/exit rules before live deployment.
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How do I handle cross-category portfolio risk across crypto, sports, and economics markets?
Resolved Markets provides orderbook snapshots across all categories, enabling correlation analysis. Measure whether BTC price prediction movements co-move with EPL outcome predictions, whether FOMC announcement volatility spikes spread to sports markets. Use historical snapshots to calibrate portfolio correlation matrices, stress-test drawdown scenarios across categories, and optimize position sizing to maintain target portfolio risk despite cross-category spillovers.
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What production guarantees does Resolved Markets provide for trading operations?
API endpoints support production trading workflows with documented uptime SLAs, redundancy, and monitoring. WebSocket connections ensure continuous real-time data flow. REST API enables backup query capabilities if streaming drops. Timestamps enable precise trade logging for compliance and audit. Pricing tiers scale from prototyping (free) to enterprise (dedicated infrastructure), supporting firm growth from concept validation through large-scale deployment.
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How can I exploit spread-capture opportunities in less-liquid Polymarket contracts?
Analyze 11.4M snapshots to identify which markets exhibit wider, more volatile spreads. Sports contracts (NFL, EPL) often show different spread dynamics than crypto. Query orderbook depth to find price levels with sparse liquidity—placing orders there may capture wider spreads. Combine spread analysis with latency advantage from Resolved Markets' sub-millisecond updates to identify micro-arbitrage windows competitors miss. Backtest on historical data to validate profitability before scaling.
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What enterprise features support Sentiment Index Construction?
3,000 RPM, 10 concurrent WebSocket connections, ClickHouse bulk mirroring, and dedicated support. Sentiment Index Construction is shipped with the throughput prop desks expect.
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Can Sentiment Index Construction be mirrored locally?
Yes. Prop firms typically mirror Sentiment Index Construction into local ClickHouse for sub-millisecond backtests and event-driven research.
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How do prop firms use Sentiment Index Construction at scale?
Prop desks mirror Sentiment Index Construction into local ClickHouse for ultra-low-latency backtests, then deploy strategies via WebSocket streaming. Enterprise throughput supports multiple concurrent strategies.
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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.
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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.