W perps

Perp · Binance, OKX, Hyperliquid · #235 by volume

0.0097550-0.43% 24h

Binance USDT · 24h 0.0094040 – 0.01020

24h volume: $10.4M; #235 of 910
Open interest: $6.8M; −3.7% contracts · 24h
Spread: 1.02 bps; median · 24h
Size at best price: $280; mean · 24h
Net taker flow: −$200.0K; every contract · 24h
Funding: +0.0050%; per period · BIN

Aperiodic metrics · W · 24 h

Are takers buying or selling W?

Takers sold $199.0K more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 03:20 UTC, saw $168.3K.

+$168.3K0−$168.3K

23:20 UTCnow

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

What does it cost to cross W's spread?

L1 liquidity

1.02 bps median on Binance USDT, tighter than 72% 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
#200AIN2.70 bps
#235W1.02 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at W's best price?

L1 liquidity

$280 at the best bid and ask on Binance USDT, on average, thinner than 91% 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
#200AIN$181
#235W$280

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is W's book leaning?

L2 imbalance

Leaned to the ask in 18 of 24 hours on Binance USDT; 45% bids over the day.

73% bid027% bid

23:20 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does W trade?

OHLCV

Binance USDT took 66% of $10.4M traded in 24 h.

volume sharespread

Binance USDT66%1.02
OKX USDT31%2.04
Hyperliquid USDC3.5%10.3

ohlcv.volume_notionaleach contract · 24 h

Does W trade away from its index?

Basis

19.3 bps below its index on Binance USDT now; 2.72 bps to 16.0 bps below over 24 h.

+16.0 bps0−16.0 bps

23:20 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in W?

Open interest

$6.8M open across 3 contracts: −3.7% in contracts, −4.9% in dollars over 24 h.

$7.3M$6.8M

23:20 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on W?

Funding

Longs pay on 2 of 3 contracts; Binance USDT charges +0.0050% a period (Hyperliquid’s are hourly).

Binance USDT+0.0050%
OKX USDT+0.0032%
Hyperliquid USDC−0.0010%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

W's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-W-USDT:USDT	0.0097550	-0.43%	$6.8M	$3.5M	+0.0050%	1.02	Charts →
OKX USDTperpetual-W-USDT:USDT	0.0097630	-0.36%	$3.2M	$1.3M	+0.0032%	2.04	Charts →
Hyperliquid USDCperpetual-W-USDC:USDC	0.0097600	-0.41%	$361.8K	$2.0M	−0.0010%	10.3	Charts →

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

Every chart for W →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

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

0.0097550

-0.43%

$6.8M

$3.5M

+0.0050%

1.02

Charts →

OKX USDTperpetual-W-USDT:USDT

0.0097630

-0.36%

$3.2M

$1.3M

+0.0032%

2.04

Charts →

Hyperliquid USDCperpetual-W-USDC:USDC

0.0097600

-0.41%

$361.8K

$2.0M

−0.0010%

10.3

Charts →

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