Shiba Inu perpsSHIB

Crypto perp · Binance, OKX · #118 by volume

0.0042300-2.94% 24h

Binance USDT · 24h 0.0041490 – 0.0043730

24h volume: $44.7M; #118 of 910
Open interest: $25.6M; −2.0% contracts · 24h
Spread: 2.33 bps; median · 24h
Size at best price: $10.2K; mean · 24h
Net taker flow: −$2.1M; every contract · 24h
Funding: +0.0009%; per period · BIN

Aperiodic metrics · SHIB · 24 h

Every metric on SHIB, bar by bar →

Are takers buying or selling SHIB?

Flow

Takers sold $2.0M more than they bought on Binance and OKX over 24 h; the heaviest hour, 03:20 UTC, saw $977.1K.

+$977.1K0−$977.1K

23:20 UTCnow

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

What does it cost to cross SHIB's spread?

L1 liquidity

2.33 bps median on Binance USDT, wider than 59% 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
#118SHIB2.33 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at SHIB's best price?

L1 liquidity

$10.2K at the best bid and ask on Binance USDT, on average, deeper than 75% 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
#118SHIB$10.2K
#200AIN$181

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is SHIB's book leaning?

L2 imbalance

Leaned to the ask in 23 of 24 hours on Binance USDT; 45% bids over the day.

60% bid040% bid

23:20 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does SHIB trade?

OHLCV

Binance USDT took 70% of $44.7M traded in 24 h.

volume sharespread

Binance USDT70%2.33
OKX USDT27%2.33
Binance USDC3.7%2.34

ohlcv.volume_notionaleach contract · 24 h

Does SHIB trade away from its index?

Basis

4.91 bps below its index on Binance USDT now; 0.27 bps to 7.73 bps below over 24 h.

+7.73 bps0−7.73 bps

23:20 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in SHIB?

Open interest

$25.6M open across 3 contracts: −2.0% in contracts, −4.9% in dollars over 24 h.

$25.5M$24.3M

23:20 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on SHIB?

Funding

Longs pay on 2 of 3 contracts; Binance USDT charges +0.0009% a period.

Binance USDT+0.0009%
OKX USDT−0.0082%
Binance USDC+0.0066%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

SHIB's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-1000SHIB-USDT:USDT	0.0042300	-2.94%	$31.1M	$18.3M	+0.0009%	2.33	Charts →
OKX USDTperpetual-SHIB-USDT:USDT	0.000004229	-2.92%	$11.9M	$6.1M	−0.0082%	2.33	Charts →
Binance USDCperpetual-1000SHIB-USDC:USDC	0.0042240	-2.92%	$1.6M	$1.3M	+0.0066%	2.34	Charts →

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

Every chart for SHIB →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: SHIB 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-1000SHIB-USDT:USDT"),
    ("okx-perps", "perpetual-SHIB-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,
    )

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

Contract

Price

24h

Volume 24h

Open interest

Funding

Spread

Binance USDTperpetual-1000SHIB-USDT:USDT

0.0042300

-2.94%

$31.1M

$18.3M

+0.0009%

2.33

Charts →

OKX USDTperpetual-SHIB-USDT:USDT

0.000004229

-2.92%

$11.9M

$6.1M

−0.0082%

2.33

Charts →

Binance USDCperpetual-1000SHIB-USDC:USDC

0.0042240

-2.92%

$1.6M

$1.3M

+0.0066%

2.34

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: SHIB 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-1000SHIB-USDT:USDT"), ("okx-perps", "perpetual-SHIB-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, )