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.
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.