Highlighted Metrics
Derivatives Datasets
Perpetual futures mark price premium over index price (basis) and last trade price, in absolute and basis-point terms.
Key fields
Funding rate and update frequencies for perpetual futures contracts.
Key fields
Open interest values with percentage change, volatility, and OI/price change ratio.
Key fields
Derivatives — Use Cases
Detect crowded positioning and carry opportunities by monitoring funding rate levels and predicted-vs-realized spread dynamics.
Identify leverage build-up and potential liquidation cascades from OI/price divergences before they materialize.
Model perp-spot basis and mark-to-trade spread to evaluate and monitor basis trading strategies in real time.
Aggregate OI volatility and funding rate extremes into composite stress indicators for risk management overlays.
Use mark-to-index price change ratios as leading indicators of short-term directional pressure in perp markets.
In crypto perpetual futures, funding rate, basis, and open interest are the primary indicators of leverage positioning and directional crowding. When funding, basis, and open interest all point the same direction, the market is building a position that will eventually need to unwind.
Get started in minutes
pip install aperiodicfrom datetime import date
from aperiodic import get_metrics
df = get_metrics(
api_key="your-api-key",
metric="flow",
timestamp="exchange",
interval="1h",
exchange="binance-futures",
symbol="perpetual-BTC-USDT:USDT",
start_date=date(2024, 1, 1),
end_date=date(2024, 1, 31),
)
print(df.head())Get access to our full catalog of market microstructure data.