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SKUU perps on Binance and OKX, from Aperiodic's own 5-minute bars, free and 15 minutes behind. Every perp, A–Z →

Every number here is 15 minutes behind

5m bar 23:20–23:25 UTC

Free, from Aperiodic's own data. The hatched end of each chart marks the 15 minutes left out.

5m bars, 15 minutes behind. The newest runs 23:20–23:25 UTC; the next lands around 23:45 UTC, and the line under this bar fills until it does. Bars are labelled by their open and keyed on capture time: when Aperiodic received each trade, quote and update.

Every metric moves every 15 seconds, just as delayed, each a rolling window over the last 5 minutes, not a 15-second bar; funding, open interest and basis every minute, the finest they are measured at. The day's medians and means roll on with the 5m bars.

1664 perpetuals on Binance, OKX and Hyperliquid.

5m bars received in the last 24h: Binance 99.3% · OKX 100.0%.

Plans with live data and more history →
23:25:00 UTC
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Markets/All perps/SKUU

SKUU perps

Perp · Binance, OKX · #186 by volume

12.500-12.59% 24h

Binance USDT · 24h 12.320 – 15.040

24h volume
$17.7M
#186 of 914
Open interest
$2.0M
−15.9% contracts · 24h
Spread
7.49 bps
median · 24h
Size at best price
$6.5K
mean · 24h
Net taker flow
−$652.3K
every contract · 24h
Funding
−0.0310%
per period · BIN

Aperiodic metrics · SKUU · 24 h

Every metric on SKUU, bar by bar →

Are takers buying or selling SKUU?

Flow

Takers sold $650.0K more than they bought on Binance and OKX over 24 h; the heaviest hour, 14:25 UTC, saw $481.3K.

+$481.3K0−$481.3K
23:25 UTCnow

flow.volume_delta_notionalbusiest contract on each venue · hourly · 24 h

What does it cost to cross SKUU's spread?

L1 liquidity

7.49 bps median on Binance USDT, wider than 93% of the 200 most traded perps.

  • #1BTC0.015 bps
  • #2ETH0.051 bps
  • #3SOXL1.56 bps
  • #5SOL1.25 bps
  • #10AKE3.18 bps
  • #25XYZ:XYZ1000.35 bps
  • #50MUU5.64 bps
  • #100MVLL8.76 bps
  • #186SKUU7.49 bps
  • #200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at SKUU's best price?

L1 liquidity

$6.5K at the best bid and ask on Binance USDT, on average, deeper than 68% of the 200 most traded perps.

  • #1BTC$651.7K
  • #2ETH$269.8K
  • #3SOXL$86.9K
  • #5SOL$157.5K
  • #10AKE$553
  • #25XYZ:XYZ100$165.1K
  • #50MUU$22.4K
  • #100MVLL$13.7K
  • #186SKUU$6.5K
  • #200AIN$180

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is SKUU's book leaning?

L2 imbalance

Leaned to the bid in 14 of 24 hours on Binance USDT; 51% bids over the day.

60% bid040% bid
23:25 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does SKUU trade?

OHLCV

Binance USDT took 83% of $17.7M traded in 24 h; the tightest spread is OKX USDT's, 7.44 bps.

volume sharespread

  • Binance USDT83%7.49
  • OKX USDT17%7.44

ohlcv.volume_notionaleach contract · 24 h

Does SKUU trade away from its index?

Basis

0.075 bps below its index on Binance USDT now; 19.8 bps below to 2.06 bps above over 24 h.

+19.8 bps0−19.8 bps
23:25 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in SKUU?

Open interest

$2.0M open across 2 contracts: −15.9% in contracts, −28.1% in dollars over 24 h.

$2.8M$2.0M
23:25 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on SKUU?

Funding

Longs pay on 0 of 2 contracts; Binance USDT charges −0.0310% a period.

  • Binance USDT−0.0310%
  • OKX USDT+0.0000%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

SKUU's 2 contracts · now

Named by Atlas →
ContractPrice24hVolume 24hOpen interestFundingSpreadCharts
Binance USDTperpetual-SKUU-USDT:USDT12.500-12.59%$14.6M$1.0M−0.0310%7.49Charts →
OKX USDTperpetual-SKUU-USDT:USDT12.520-12.39%$3.1M$951.4K+0.0000%7.44Charts →

History · a year of 5m bars per series · busiest contract on each venue

Every chart for SKUU →
Python
import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: SKUU on Binance and OKX
# 5m bars, 2025-11-12 to 2026-11-12. Install: pip install "aperiodic[polars]"
# Needs an API key (https://aperiodic.io/home/api) on a plan with flow, basis, open_interest, funding (Pro) and l1_liquidity, l2_imbalance (Prime).
# OKX: okx-perps l1_liquidity and l2_liquidity count contracts, not coins (BTC-USDT-SWAP is 0.01 BTC each). Multiply by the contract size to match the page.
API_KEY = os.environ["APERIODIC_API_KEY"]
# timestamp="true" keys bars on capture time, as on the page; "exchange" keys them on exchange time.
PERIOD = dict(
    interval="5m",
    timestamp="true",
    start_date=date(2025, 11, 12),
    end_date=date(2026, 11, 12),
)
CONTRACTS = [
    ("binance-futures", "perpetual-SKUU-USDT:USDT"),
    ("okx-perps", "perpetual-SKUU-USDT:USDT"),
]

frames = {}
for exchange, symbol in CONTRACTS:
    frames["flow", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="flow",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["l1_liquidity", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="l1_liquidity",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["l2_imbalance", exchange, symbol] = get_metrics(
        api_key=API_KEY,
        metric="l2_imbalance",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["basis", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="basis",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["open_interest", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="open_interest",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )
    frames["funding", exchange, symbol] = get_derivative_metrics(
        api_key=API_KEY,
        metric="funding",
        exchange=exchange,
        symbol=symbol,
        **PERIOD,
    )

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Every number is from Aperiodic's own 5-minute bars, 15 minutes behind.

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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.

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