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HypQuant

Financial data infrastructure for quantitative traders.

HypQuant gives you clean, validated OHLCV candles, funding rates, and 20 pre-computed features across Hyperliquid and Binance — ready to plug into your backtest or live strategy in minutes.


Why HypQuant?

Raw crypto data is messy. Exchanges return inconsistent timestamps, missing candles, and prices that violate basic OHLCV invariants (low > close). Cleaning that data correctly takes weeks. HypQuant has already done it — and we document every decision we made.

Raw exchange data HypQuant
Timestamp alignment Per-exchange jitter UTC-aligned, cross-exchange matched
Gaps Silently missing Detected, catalogued, forward-filled or flagged
Features You compute them 20 pre-computed, validated against pandas-ta
Data quality signal None DQS score 0–1 with breakdown per asset

5-minute start

pip install hypquant
from hypquant import MarketData

md = MarketData(api_key="qp_...")
df = md.ohlcv("BTC-USDC", exchange="hyperliquid", timeframe="1h", start="2024-01-01")
print(df.head())

Full Getting Started guide


What's available

  • Exchanges: Hyperliquid (perpetuals), Binance (spot)
  • Timeframes: 1m, 5m, 15m, 1h, 4h, 1d
  • Features: RSI, MACD, Bollinger Bands, ATR, VWAP, funding z-score, premium, and more
  • Quality: Data Quality Score (DQS) with gap rate, anomaly, consistency, freshness breakdown

Pricing

Tier Price Rate limit Assets History
Free $0/mo 1k req/day 5 1 year
Pro $149/mo 50k req/day 30 Full
Scale $499/mo Unlimited Unlimited Full + SLA

Free tier requires no credit card. Sign up →


Known limitations

HypQuant v1.0 does not support L3 order book data, WebSocket streaming, or exchanges beyond Hyperliquid and Binance. See the full Known Limitations page before building on top of us — we think transparency here is a feature, not a bug.