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Data Catalog

Browse our curated market data catalog across exchanges and asset types.

19 datasets

Trades

Derivatives

Market Data

L1 (Top of Book)

L2 (Order Book)

Preview Data

No subscription required

The following datasets are available to any authenticated user — even without a paid plan. Pass preview=True in the Python client, or call /api/v1/data/preview/:metric_id directly.

DatasetExchangeSymbolIntervalTimestampDate range
Candlesticksbinance-futuresperpetual-BTC-USDT:USDT5mexchange2025-05-01 — 2025-05-31
L2 Order Book Imbalancebinance-futuresperpetual-BTC-USDT:USDT5mexchange2025-05-01 — 2025-05-31
Slippage

Slippage

How much each trade pays above the best ask (buys) or receives below the best bid (sells) relative to the prevailing quote, aggregated per interval.

CodeAPI DocsTry It

slippage_bps_mean

Mean Slippage (bps)

Mean Slippage in basis points captures the average execution shortfall relative to the chosen benchmark.

It offers a clean first-pass estimate of how expensive crossing the spread and consuming liquidity was in practice.

slippage_bps_p95

Slippage P95 (bps)

The 95th percentile of slippage focuses on the bad tail rather than on the average experience.

It is especially useful for execution planning because desks often care more about occasional painful outcomes than about typical ones.

slippage_bps_vwap

VWAP Slippage (bps)

VWAP Slippage compares executions with the interval volume-weighted market price, anchoring cost to where activity actually traded.

This often provides a more realistic benchmark for larger or more patient trading styles than a single last price snapshot.

slippage_bps_buy_sell_ratio

Buy/Sell Slippage Ratio

Buy/Sell Slippage Ratio asks whether lifting liquidity was more expensive than hitting it, or vice versa.

Asymmetry here can reveal directional stress, inventory pressure, or a book that is materially less resilient on one side.

slippage_bps_std

Slippage Std Dev (bps)

Slippage Std Dev measures how variable execution quality was from trade to trade.

Two markets can have the same mean cost but very different predictability, and this metric tells you which one is more stable.

Endpoint

/api/v1/data/slippage

Category

Trades

Intervals
1m5m15m30m1h4h1d
Requires Prime
1s

Requires timestamp=true

Exchanges
binance-futuresokx-perpshyperliquid-perps
Fields10
slippage_meanMean SlippageAverage slippage in price units versus the prevailing quote
slippage_bps_meanMean Slippage (bps)Average slippage in basis points versus the prevailing quote
slippage_bps_stdSlippage Std Dev (bps)Standard deviation of slippage in basis points
slippage_bps_medianMedian Slippage (bps)Median slippage in basis points
slippage_bps_p95Slippage P95 (bps)95th percentile slippage in basis points
slippage_bps_vwapVWAP Slippage (bps)Trade-size-weighted average slippage in basis points
slippage_bps_buy_meanBuy Slippage Mean (bps)Average slippage in basis points for buy-side trades
slippage_bps_sell_meanSell Slippage Mean (bps)Average slippage in basis points for sell-side trades
slippage_bps_buy_sell_ratioBuy/Sell Slippage RatioBuy-side average slippage divided by sell-side average slippage
slippage_bps_sell_buy_ratioSell/Buy Slippage RatioSell-side average slippage divided by buy-side average slippage
Example Request
from datetime import date
from aperiodic import get_metrics
df = get_metrics(
    api_key="YOUR_API_KEY",
    metric="slippage",
    exchange="binance-futures",
    symbol="perpetual-BTC-USDT:USDT",
    interval="1d",
    start_date=date(2024, 1, 1),
    end_date=date(2024, 3, 1),
)
print(df.head())

Query Parameters

timestampreqstring
string

Timestamp source. 'exchange' uses the exchange-reported timestamp, 'true' uses actual arrival time at our servers.

exchangetrue
intervalreqstring
string

Aggregation time interval for the data.

1m5m15m30m1h4h1d
exchangereqstring
string

Source exchange for the data.

binance-futuresokx-perpshyperliquid-perps
symbolreqstring
string

Trading pair symbol in the format of Atlas' universal symbology: https://github.com/aperiodic-io/atlas

start_datereqstring<date>
string<date>

Start date for the data range (YYYY-MM-DD format). Data is partitioned by year and month.

end_datereqstring<date>
string<date>

End date for the data range (YYYY-MM-DD format). Must be greater than or equal to start_date.

Successful response with download URLs for each monthly file

Schema
filesobject[]required

Array of file information for each month in the requested date range

yearintegerrequired

Year of the data file

monthintegerrequired

Month of the data file (1-12)

urlstring<uri>required

Presigned URL for direct file download (valid for 5 minutes). URLs are served from dataset-specific subdomains, e.g. ohlcv.aperiodic.io, trade-metrics.aperiodic.io, l1-metrics.aperiodic.io, l2-metrics.aperiodic.io, derivative-metrics.aperiodic.io.

Example
{
  "files": [
    {
      "year": 2024,
      "month": 1,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2024-01.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2024,
      "month": 2,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2024-02.parquet?X-Amz-Expires=300&..."
    }
  ]
}
Try It
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Authentication
An API key is required to send requests.Sign up
GET/api/v1/data/slippage?timestamp=exchange&interval=1m&exchange=binance-futures
Response will appear here
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