Aperiodic
MarketsLive
Pricing
Get Started

Use case

Improve your backtest

Stop backtesting fantasy fills. Price in slippage, impact and funding with point-in-time metrics.

Shown: minute lows of the 465 Binance perpetuals, 20:40–22:00 UTC on 10 Oct 2025, with BTC’s path traced · built with ohlcv 1m

Featured notebook

Backtesting with realistic microstructure cost

A price-only backtest quietly assumes you can trade at the mid-price for free. Real fills pay the half-spread, move the book, and miss when liquidity thins out. This notebook builds a microstructure transaction-cost model — half-spread plus market impact — from Aperiodic's L1 price, impact, and slippage metrics, checks it against measured slippage, and shows how different cost assumptions reshape the same simple momentum backtest.

Loading notebook…

Or have your agent rerun this notebook and tell you what it finds. Start in Claude · Claude Code · Codex · See the prompt

From notebook to production

01

Pick the metrics

Browse the catalog and pull point-in-time microstructure metrics — no L2 reconstruction, no tick archive to maintain.

02

Run the notebook

Every notebook runs end to end on preview data with a free account, in the browser or through the CLI.

03

Plug it into your stack

Swap the preview key for your own and the same code pulls every year your plan includes through the Python package or the API.

Metrics in this use case

More notebooks for this use case

Also featured

Funding-aware perpetual backtests

Improve your backtest

A perpetual-futures position does not only earn the price move — it also pays or receives funding at discrete settlement prints. A price-only backtest ignores those cash flows and can misattribute carry to trading alpha, most of all for a persistently long strategy in a rising, positive-funding market. This notebook isolates realised funding and shows exactly where it binds: it is a first-order cost for a directional (long-biased) position and nets out for a direction-neutral one.

View notebook

Improve your backtest

Stop backtesting fantasy fills. Price in slippage, impact and funding with point-in-time metrics.

Run on preview dataBrowse catalog

Shown: minute lows of the 465 Binance perpetuals, 20:40–22:00 UTC on 10 Oct 2025, with BTC’s path traced · built with ohlcv 1m

L1 Liquidity

L1 (Top of Book)

L1 Liquidity

Spread (absolute and bps), depth, dollar depth — instantaneous and interval-averaged.

See it on real data

Need the ticks behind this metric? Prime + Raw includes raw quotes.

Sample CSVStart in Claude
CodeLive StreamAPI DocsTry It
00h06h12h18h
18152231

Shown: total_dollar_depth_avg, hourly, 1–31 January 2024, from this page's Sample CSV · extreme: $892042, 29 Jan, 06:00 UTC · built with l1_liquidity

lowhighextreme
spread_bps

Spread (bps)

Spread in basis points measures the instantaneous cost of crossing from the best bid to the best ask on a normalized scale.

It is one of the most direct and actionable summaries of top-of-book trading conditions.

spread_depth_ratio

Spread/Depth Ratio

Spread/Depth Ratio combines price width and displayed size into a single liquidity efficiency measure.

A market with tight spreads but little size can still be fragile, and this ratio helps expose that weakness.

total_dollar_depth

Total Dollar Depth

Total Dollar Depth aggregates the top-level bid and ask liquidity in value terms.

This gives a more practical view of executable size than raw units, especially across instruments with different prices.

dollar_depth_bid_avg

Avg Bid Dollar Depth

Average Bid Dollar Depth tracks the mean value resting on the bid at the top of book throughout the interval.

It helps answer whether supportive displayed buying liquidity was consistently present or only flashed briefly.

dollar_depth_ask_avg

Avg Ask Dollar Depth

Average Ask Dollar Depth provides the matching view for displayed sell-side liquidity at the best offer.

Comparing it with the bid average helps reveal whether one side of the book was structurally thinner or thicker during the bar.

Endpoint
/api/v1/data/l1_liquidity
Category
L1 (Top of Book)
Built from
Raw quotes →
Intervals
1m5m15m30m1h4h1d
Requires Institutional
15s30s
Exchanges
binance-futuresokx-perpshyperliquid-perps

Fields

14
FieldNameDescription
spreadSpreadLast best ask price minus best bid price in the interval
spread_bpsSpread (bps)Last bid-ask spread in basis points of the midprice
spread_depth_ratioSpread/Depth RatioLast bid-ask spread divided by total top-of-book quantity
total_depthTotal DepthLast total top-of-book quantity across bid and ask
dollar_depth_bidBid Dollar DepthLast bid-side top-of-book notional
dollar_depth_askAsk Dollar DepthLast ask-side top-of-book notional
total_dollar_depthTotal Dollar DepthLast total top-of-book notional across bid and ask
spread_avgAvg SpreadAverage bid-ask spread in the interval
spread_bps_avgAvg Spread (bps)Average bid-ask spread in basis points over the interval
spread_depth_ratio_avgAvg Spread/Depth RatioAverage spread-to-depth ratio over the interval
total_depth_avgAvg Total DepthAverage total top-of-book quantity across bid and ask in the interval
dollar_depth_bid_avgAvg Bid Dollar DepthAverage bid-side top-of-book notional in the interval
dollar_depth_ask_avgAvg Ask Dollar DepthAverage ask-side top-of-book notional in the interval
total_dollar_depth_avgAvg Total Dollar DepthAverage total top-of-book notional across bid and ask in the interval

Example Request

# 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 l1_liquidity --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"

Live Stream

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 l1_liquidity.<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]"
pypi ↗
import os

from aperiodic import stream

for message in stream(
    api_key=os.environ["APERIODIC_API_KEY"],
    dataset="l1_liquidity",
    exchange="binance-futures",
    interval="1m",
    symbols=["perpetual-BTC-USDT:USDT"],  # omit for every symbol on your plan
):
    print(message.channel, message.snapshot, message.data)

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. Sub-minute intervals (15s, 30s) require an Institutional plan.

15s30s1m5m15m30m1h4h1d
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). 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>
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 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

Schema
filesobject[]required

Files 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.

yearintegerrequired

Year of the data file

monthintegerrequired

Month of the data file (1-12)

dayinteger

Day 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>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": 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&..."
    }
  ]
}

Try It

Prefilled with the shared DEMO-KEY and a free preview slice — send the request to see live data, no account required.

Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Authentication
GET/api/v1/data/preview/l1_liquidity?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT%3AUSDT&start_date=2025-05-01&end_date=2025-05-31
Response will appear here
Aperiodic

Built from hundreds of terabytes of raw data and distilled into point-in-time metrics you can pull as parquet files. Plus the raw trades, quotes and derivatives data behind them.

Use Cases
  • Improve your backtest
  • Find new alpha
  • Execute smarter
Indices
  • All indices
  • Aperiodic Cost Index
  • Aperiodic Depth Index
  • Aperiodic Impact Index
Metrics
  • Metrics library
  • Data Catalog
  • Live markets dashboard
  • Global Liquidity
  • Unusual activity
  • Order Flow
  • L1 & L2
  • Derivatives
  • RWA
  • Raw Data
Developers
  • API Docs
  • Live WebSocket Feed
  • MCP Server
  • Notebooks
  • For AI Agents
  • Atlas Security Master
  • Pre-flight
  • Changelog
  • Roadmap
  • llms.txt
Learn
  • Replays
  • Microstructure Guide
  • Architecture
  • Research Blog
  • FAQ
Compare
  • All vendors
  • vs. Tardis
  • vs. CoinGlass
  • vs. Kaiko
  • vs. Amberdata
Company
  • Pricing
  • Contact
  • Book a call
  • Terms of Service
  • Privacy Policy
  • Licensing
  • SLA

© Copyright 2026 Aperiodic. All Rights Reserved.

Aperiodic Limited · Registered in Ireland · Company No. 815273 ·
136 Capel Street, Dublin D01 T2C9, Ireland

Shown: minute closes of 847 perpetuals, 20:30–22:30 UTC on 10 Oct 2025, IOTX in orange · built with ohlcv 1m