BOME perps

Perp · Binance, OKX, Hyperliquid · #198 by volume

0.0005675+0.76% 24h

Binance USDT · 24h 0.0005383 – 0.0005925

24h volume: $15.7M; #198 of 910
Open interest: $5.4M; −8.6% contracts · 24h
Spread: 1.77 bps; median · 24h
Size at best price: $521; mean · 24h
Net taker flow: −$253.1K; every contract · 24h
Funding: +0.0050%; per period · BIN

Aperiodic metrics · BOME · 24 h

Are takers buying or selling BOME?

Takers sold $215.3K more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 13:20 UTC, saw $141.0K.

+$141.0K0−$141.0K

23:20 UTCnow

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

What does it cost to cross BOME's spread?

L1 liquidity

1.77 bps median on Binance USDT, tighter than 52% 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
#198BOME1.77 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at BOME's best price?

L1 liquidity

$521 at the best bid and ask on Binance USDT, on average, thinner than 81% 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
#198BOME$521
#200AIN$181

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is BOME's book leaning?

L2 imbalance

Leaned to the bid in 17 of 24 hours on Binance USDT; 52% bids over the day.

59% bid041% bid

23:20 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does BOME trade?

OHLCV

Binance USDT took 61% of $15.7M traded in 24 h.

volume sharespread

Binance USDT61%1.77
OKX USDT25%1.83
Binance USDC14%8.58
Hyperliquid USDC0.5%17.9

ohlcv.volume_notionaleach contract · 24 h

Does BOME trade away from its index?

Basis

4.05 bps below its index on Binance USDT now; 6.93 bps to 14.8 bps below over 24 h.

+14.8 bps0−14.8 bps

23:20 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in BOME?

Open interest

$5.4M open across 4 contracts: −8.6% in contracts, −8.1% in dollars over 24 h.

$5.2M$4.7M

23:20 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on BOME?

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+0.0050%
Binance USDC+0.0050%
Hyperliquid USDC+0.0013%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

BOME's 4 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-BOME-USDT:USDT	0.0005675	+0.76%	$9.5M	$3.5M	+0.0050%	1.77	Charts →
OKX USDTperpetual-BOME-USDT:USDT	0.0005676	+0.76%	$3.9M	$945.8K	+0.0050%	1.83	Charts →
Binance USDCperpetual-BOME-USDC:USDC	0.0005669	+0.82%	$2.2M	$723.6K	+0.0050%	8.58	Charts →
Hyperliquid USDCperpetual-BOME-USDC:USDC	0.0005660	-0.53%	$76.0K	$250.9K	+0.0013%	17.9	Charts →

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

Every chart for BOME →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

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

0.0005675

+0.76%

$9.5M

$3.5M

+0.0050%

1.77

Charts →

OKX USDTperpetual-BOME-USDT:USDT

0.0005676

+0.76%

$3.9M

$945.8K

+0.0050%

1.83

Charts →

Binance USDCperpetual-BOME-USDC:USDC

0.0005669

+0.82%

$2.2M

$723.6K

+0.0050%

8.58

Charts →

Hyperliquid USDCperpetual-BOME-USDC:USDC

0.0005660

-0.53%

$76.0K

$250.9K

+0.0013%

17.9

Charts →

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