Market Data Datasets
Use Cases
Build and validate momentum, mean-reversion, and carry strategies on reliable price history without data leakage.
Construct factor indices spanning hundreds of instruments using consistent OHLCV aggregations across exchanges.
Power dashboards and research notebooks with high-fidelity candlestick data at 1m–1d resolutions.
Use realized returns computed from clean close prices to calibrate implied-vol models and risk engines.
Compare fills against VWAP and TWAP benchmarks derived from the same raw tick data as your strategy.
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.