dogwifhat perpsWIF

Crypto perp · Binance, OKX, Hyperliquid · #181 by volume

0.14660-3.68% 24h

Binance USDT · 24h 0.14450 – 0.15300

24h volume: $18.8M; #181 of 910
Open interest: $16.8M; +0.2% contracts · 24h
Spread: 6.66 bps; median · 24h
Size at best price: $7.7K; mean · 24h
Net taker flow: −$648.2K; every contract · 24h
Funding: +0.0050%; per period · BIN

Aperiodic metrics · WIF · 24 h

Are takers buying or selling WIF?

Takers sold $671.8K more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 03:20 UTC, saw $388.2K.

+$388.2K0−$388.2K

23:20 UTCnow

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

What does it cost to cross WIF's spread?

L1 liquidity

6.66 bps median on Binance USDT, wider than 90% 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
#181WIF6.66 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at WIF's best price?

L1 liquidity

$7.7K at the best bid and ask on Binance USDT, on average, deeper than 71% 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
#181WIF$7.7K
#200AIN$181

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is WIF's book leaning?

L2 imbalance

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

53% bid047% bid

23:20 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does WIF trade?

OHLCV

Binance USDT took 64% of $18.8M traded in 24 h; the tightest spread is Hyperliquid USDC's, 3.98 bps.

volume sharespread

Binance USDT64%6.66
OKX USDT24%6.66
Binance USDC7.8%6.74
Hyperliquid USDC3.9%3.98

ohlcv.volume_notionaleach contract · 24 h

Does WIF trade away from its index?

Basis

17.2 bps below its index on Binance USDT now; 1.13 bps to 9.85 bps below over 24 h.

+9.85 bps0−9.85 bps

23:20 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in WIF?

Open interest

$16.8M open across 4 contracts: +0.2% in contracts, −2.9% in dollars over 24 h.

$16.6M$16.0M

23:20 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on WIF?

Funding

Longs pay on 4 of 4 contracts; Binance USDT charges +0.0050% a period (Hyperliquid’s are hourly).

Binance USDT+0.0050%
OKX USDT+0.0007%
Binance USDC+0.0050%
Hyperliquid USDC+0.0013%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

WIF's 4 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-WIF-USDT:USDT	0.14660	-3.68%	$12.0M	$9.9M	+0.0050%	6.66	Charts →
OKX USDTperpetual-WIF-USDT:USDT	0.14660	-3.68%	$4.6M	$3.3M	+0.0007%	6.66	Charts →
Binance USDCperpetual-WIF-USDC:USDC	0.14650	-3.68%	$1.5M	$851.1K	+0.0050%	6.74	Charts →
Hyperliquid USDCperpetual-WIF-USDC:USDC	0.14678	-3.60%	$732.3K	$2.9M	+0.0013%	3.98	Charts →

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

Every chart for WIF →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

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

0.14660

-3.68%

$12.0M

$9.9M

+0.0050%

6.66

Charts →

OKX USDTperpetual-WIF-USDT:USDT

0.14660

-3.68%

$4.6M

$3.3M

+0.0007%

6.66

Charts →

Binance USDCperpetual-WIF-USDC:USDC

0.14650

-3.68%

$1.5M

$851.1K

+0.0050%

6.74

Charts →

Hyperliquid USDCperpetual-WIF-USDC:USDC

0.14678

-3.60%

$732.3K

$2.9M

+0.0013%

3.98

Charts →

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