Interactive Guide
Shown: an illustrative order book over time, bids below the mid and asks above it.
Imagine a room where buyers line up on the left and sellers on the right. The person at the front of each line sets the best bid and best ask. The gap between them is the spread. When a buyer gets impatient and crosses over to the seller's side at their price, a trade happens.
Mid price
A market order hits
Try placing a market buy with a large size. Watch how the order eats through the ask side, consuming liquidity level by level. The spread widens. The midprice shifts. This is in its most elemental form.
The book above is simulated. Our measures the depth of real books, and there's a free sample to try.
Trades
How much each unit of trading volume moves the price, measured via Amihud illiquidity, Kyle lambda, impact per notional, and large-trade reversal.
Need the ticks behind this metric? Prime + Raw includes raw trades.
Shown: kyle_like_lambda, hourly, 1–31 January 2024, from this page's Sample CSV · extreme: 2.66e-5, 5 Jan, 01:00 UTC · built with impact
amihud_likeAmihud Illiquidity measures how much price moved for a given amount of traded notional, providing a classic impact-per-volume lens.
Higher values imply that relatively small amounts of trading were able to move the market, which is usually a sign of thin or fragile liquidity.
kyle_like_lambdaKyle Lambda estimates the sensitivity of price changes to signed order flow, translating imbalance into impact.
When it rises, the same net buying or selling pressure tends to push price farther, suggesting a more impressionable market.
impact_per_notionalImpact per Notional asks a practical question: how much movement did each unit of traded value cause?
It helps traders benchmark execution cost in a way that feels intuitive and transferable across strategies.
large_trade_reversalLarge Trade Reversal measures how often and how strongly price snaps back after a large trade moves through the market.
Strong reversal behavior often suggests the initiating trade consumed liquidity but failed to represent durable information.
directional_impact_asymmetryDirectional Impact Asymmetry compares whether buy-side and sell-side aggression moved price by the same amount.
Asymmetry can reveal one-sided fragility, such as a market that lifts easily but resists downside, or the reverse.
Market impact — the price displacement caused by trading — is the central cost of active investing. Two foundational academic measures capture it from different angles, and both reveal something the other misses.
/api/v1/data/impact| Field | Name | Description |
|---|---|---|
amihud_like | Amihud Illiquidity | Absolute interval return divided by total traded notional |
kyle_like_lambda | Kyle Lambda | Covariance of trade returns and signed trade size divided by signed-size variance |
impact_per_notional | Impact per Notional | Absolute interval return divided by absolute signed notional flow |
large_trade_reversal | Large Trade Reversal | Average five-trade-ahead return after trades in the top 10% by notional |
directional_impact_asymmetry | Directional Impact Asymmetry | Average buy-trade price impact minus average sell-trade price impact |
# Install the Aperiodic CLI into ~/.local/bin
mkdir -p "$HOME/.local/bin"
curl -fsSL https://raw.githubusercontent.com/aperiodic-io/cli/main/install.sh | INSTALL_DIR="$HOME/.local/bin" bash
export PATH="$HOME/.local/bin:$PATH"
# Free preview — no API key required
aperiodic impact --preview \
--exchange binance-futures \
--symbol perpetual-BTC-USDT:USDT \
--interval 5m \
--timestamp exchange \
--start-date 2025-05-01 \
--end-date 2025-05-31 \
--output-dir ./data && echo "Saved to $PWD/data"Every new row as it is computed, over WebSocket at wss://stream.aperiodic.io/v1/stream. Authenticate with your API key in the X-API-KEY header and subscribe to channels named impact.<exchange>.<interval>, on intervals 15s, 30s, 1m, 5m, 15m, 30m, 1h, 4h, 1d (15s and 30s on Institutional Live only). Streaming is included on Live plans.
pip install "aperiodic[stream]"import os
from aperiodic import stream
for message in stream(
api_key=os.environ["APERIODIC_API_KEY"],
dataset="impact",
exchange="binance-futures",
interval="1m",
symbols=["perpetual-BTC-USDT:USDT"], # omit for every symbol on your plan
):
print(message.channel, message.snapshot, message.data)timestampreqstringTimestamp source. 'exchange' uses the exchange-reported timestamp, 'true' uses actual arrival time at our servers.
exchangetrueintervalreqstringAggregation time interval for the data. Sub-minute intervals (15s, 30s) require an Institutional plan.
15s30s1m5m15m30m1h4h1dexchangereqstringSource exchange for the data.
binance-futuresokx-perpshyperliquid-perpssymbolreqstringTrading pair symbol in the format of Atlas' universal symbology: https://github.com/aperiodic-io/atlas
start_datereqstring<date>Start date for the data range (YYYY-MM-DD format). A metric series starts on the first day of the raw series it is computed from (see /metadata/raw); raw trades and quotes start binance-futures from 2020-01-01, okx-perps from 2019-09-01, hyperliquid-perps from 2025-01-01. Earlier days return no files. How far back you can go depends on the plan: 4 years on Pro, 5 years on Prime and Prime + Raw, full history on Institutional. An earlier start_date returns 403.
end_datereqstring<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 every existing file covering the range from the series' published start — one per month before 2026-08-01, one per day from 2026-08-01 onwards
filesobject[]requiredFiles covering the requested date range, in chronological order. Data before 2026-08-01 is split by month (one file per calendar month, no `day`); data from 2026-08-01 onwards is split by day (one file per calendar day, with `day` set). The changeover falls on a month boundary, so a given month is served entirely one way or the other; a range spanning it returns the earlier months as monthly files followed by a daily file per day.
yearintegerrequiredYear of the data file
monthintegerrequiredMonth of the data file (1-12)
dayintegerDay of the data file (1-31). Present only on daily files, i.e. those covering 2026-08-01 onwards. Absent on monthly files, which cover an entire calendar month.
urlstring<uri>requiredPresigned 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.
{
"files": [
{
"year": 2026,
"month": 6,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-06.parquet?X-Amz-Expires=300&..."
},
{
"year": 2026,
"month": 7,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-07.parquet?X-Amz-Expires=300&..."
},
{
"year": 2026,
"month": 8,
"day": 1,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-01.parquet?X-Amz-Expires=300&..."
},
{
"year": 2026,
"month": 8,
"day": 2,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-02.parquet?X-Amz-Expires=300&..."
}
]
}
Prefilled with the shared DEMO-KEY and a free preview slice — send the request to see live data, no account required.
/api/v1/data/preview/impact?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT%3AUSDT&start_date=2025-05-01&end_date=2025-05-31