Arm perpsARM

Stock perp · Binance, OKX, Hyperliquid · #135 by volume

186.080-7.70% 24h

Binance USDT · 24h 181.390 – 205.070

24h volume: $36.9M; #135 of 910
Open interest: $8.9M; +3.1% contracts · 24h
Spread: 2.12 bps; median · 24h
Size at best price: $440; mean · 24h
Net taker flow: −$1.1M; every contract · 24h
Funding: +0.0000%; per period · BIN

Aperiodic metrics · ARM · 24 h

Are takers buying or selling ARM?

Takers sold $1.1M more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 14:20 UTC, saw $392.4K.

+$392.4K0−$392.4K

23:20 UTCnow

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

What does it cost to cross ARM's spread?

L1 liquidity

2.12 bps median on Binance USDT, wider than 54% 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
#135ARM2.12 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at ARM's best price?

L1 liquidity

$440 at the best bid and ask on Binance USDT, on average, thinner than 84% 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
#135ARM$440
#200AIN$181

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is ARM's book leaning?

L2 imbalance

Leaned to the bid in 12 of 24 hours on Binance USDT; 52% bids over the day.

71% bid029% bid

23:20 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does ARM trade?

OHLCV

Binance USDT took 75% of $36.9M traded in 24 h.

volume sharespread

Binance USDT75%2.12
OKX USDT14%2.53
Hyperliquid xyz USDC12%3.45

ohlcv.volume_notionaleach contract · 24 h

Does ARM trade away from its index?

Basis

4.58 bps above its index on Binance USDT now; 4.13 bps below to 18.0 bps above over 24 h.

+18.0 bps0−18.0 bps

23:20 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in ARM?

Open interest

$8.9M open across 3 contracts: +3.1% in contracts, −4.7% in dollars over 24 h.

$9.3M$8.3M

23:20 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on ARM?

Funding

Longs pay on 1 of 3 contracts; Binance USDT charges +0.0000% a period (Hyperliquid’s are hourly).

Binance USDT+0.0000%
OKX USDT+0.0000%
Hyperliquid xyz USDC+0.0006%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

ARM's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-ARM-USDT:USDT	186.080	-7.70%	$27.5M	$3.6M	+0.0000%	2.12	Charts →
OKX USDTperpetual-ARM-USDT:USDT	186.000	-7.74%	$5.1M	$1.3M	+0.0000%	2.53	Charts →
Hyperliquid xyz USDCperpetual-XYZ:ARM-USDC:USDC	186.210	-7.51%	$4.3M	$4.0M	+0.0006%	3.45	Charts →

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

Every chart for ARM →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: ARM 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-ARM-USDT:USDT"),
    ("okx-perps", "perpetual-ARM-USDT:USDT"),
    ("hyperliquid-perps", "perpetual-XYZ:ARM-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-ARM-USDT:USDT

186.080

-7.70%

$27.5M

$3.6M

+0.0000%

2.12

Charts →

OKX USDTperpetual-ARM-USDT:USDT

186.000

-7.74%

$5.1M

$1.3M

+0.0000%

2.53

Charts →

Hyperliquid xyz USDCperpetual-XYZ:ARM-USDC:USDC

186.210

-7.51%

$4.3M

$4.0M

+0.0006%

3.45

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: ARM 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-ARM-USDT:USDT"), ("okx-perps", "perpetual-ARM-USDT:USDT"), ("hyperliquid-perps", "perpetual-XYZ:ARM-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, )