Internet Computer perpsICP

Crypto perp · Binance, OKX, Hyperliquid · #111 by volume

2.477-3.81% 24h

Binance USDT · 24h 2.463 – 2.655

24h volume: $50.7M; #111 of 910
Open interest: $29.4M; +1.8% contracts · 24h
Spread: 3.87 bps; median · 24h
Size at best price: $4.4K; mean · 24h
Net taker flow: −$873.4K; every contract · 24h
Funding: +0.0100%; per period · BIN

Aperiodic metrics · ICP · 24 h

Are takers buying or selling ICP?

Takers sold $862.6K more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 21:20 UTC, saw $631.7K.

+$631.7K0−$631.7K

23:20 UTCnow

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

What does it cost to cross ICP's spread?

L1 liquidity

3.87 bps median on Binance USDT, wider than 79% of the 200 most traded perps.

#1BTC0.014 bps
#2ETH0.051 bps
#3SOXL1.56 bps
#5SOL1.25 bps
#10AKE3.20 bps
#25SP5000.13 bps
#50MUU5.64 bps
#100MVLL8.76 bps
#111ICP3.87 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at ICP's best price?

L1 liquidity

$4.4K at the best bid and ask on Binance USDT, on average, deeper than 62% of the 200 most traded perps.

#1BTC$651.3K
#2ETH$269.7K
#3SOXL$87.0K
#5SOL$157.7K
#10AKE$562
#25SP500$105.4K
#50MUU$22.5K
#100MVLL$13.7K
#111ICP$4.4K
#200AIN$181

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is ICP's book leaning?

L2 imbalance

Leaned to the ask in 17 of 24 hours on Binance USDT; 49% bids over the day.

55% bid045% bid

23:20 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does ICP trade?

OHLCV

Binance USDT took 70% of $50.7M traded in 24 h.

volume sharespread

Binance USDT70%3.87
OKX USDT25%3.87
Hyperliquid USDC5.4%4.32

ohlcv.volume_notionaleach contract · 24 h

Does ICP trade away from its index?

Basis

9.10 bps below its index on Binance USDT now; 4.43 bps to 9.50 bps below over 24 h.

+9.50 bps0−9.50 bps

23:20 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in ICP?

Open interest

$29.4M open across 3 contracts: +1.8% in contracts, −1.6% in dollars over 24 h.

$31.5M$29.4M

23:20 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on ICP?

Funding

Longs pay on 2 of 3 contracts; Binance USDT charges +0.0100% a period (Hyperliquid’s are hourly).

Binance USDT+0.0100%
OKX USDT−0.0023%
Hyperliquid USDC+0.0013%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

ICP's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-ICP-USDT:USDT	2.477	-3.81%	$35.3M	$20.9M	+0.0100%	3.87	Charts →
OKX USDTperpetual-ICP-USDT:USDT	2.476	-3.81%	$12.6M	$5.8M	−0.0023%	3.87	Charts →
Hyperliquid USDCperpetual-ICP-USDC:USDC	2.477	-3.91%	$2.8M	$2.7M	+0.0013%	4.32	Charts →

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

Every chart for ICP →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: ICP on Binance, OKX and Hyperliquid
# 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-ICP-USDT:USDT"),
    ("okx-perps", "perpetual-ICP-USDT:USDT"),
    ("hyperliquid-perps", "perpetual-ICP-USDC:USDC"),
]

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,
    )

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

Contract

Price

24h

Volume 24h

Open interest

Funding

Spread

Binance USDTperpetual-ICP-USDT:USDT

2.477

-3.81%

$35.3M

$20.9M

+0.0100%

3.87

Charts →

OKX USDTperpetual-ICP-USDT:USDT

2.476

-3.81%

$12.6M

$5.8M

−0.0023%

3.87

Charts →

Hyperliquid USDCperpetual-ICP-USDC:USDC

2.477

-3.91%

$2.8M

$2.7M

+0.0013%

4.32

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: ICP on Binance, OKX and Hyperliquid # 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-ICP-USDT:USDT"), ("okx-perps", "perpetual-ICP-USDT:USDT"), ("hyperliquid-perps", "perpetual-ICP-USDC:USDC"), ] 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, )