Coherent perpsCOHR

Stock perp · Binance, OKX, Hyperliquid · #144 by volume

213.060-10.49% 24h

Binance USDT · 24h 207.710 – 241.330

24h volume: $32.7M; #144 of 925
Open interest: $8.2M; +2.7% contracts · 24h
Spread: 2.60 bps; median · 24h
Size at best price: $415; mean · 24h
Net taker flow: −$2.2M; every contract · 24h
Funding: +0.0000%; per period · BIN

Aperiodic metrics · COHR · 24 h

Are takers buying or selling COHR?

Takers sold $2.1M more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 14:50 UTC, saw $948.4K.

+$948.4K0−$948.4K

00:50 UTCnow

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

What does it cost to cross COHR's spread?

L1 liquidity

2.60 bps median on Binance USDT, wider than 64% of the 200 most traded perps.

#1BTC0.015 bps
#2ETH0.052 bps
#3SOXL1.57 bps
#5SOL1.25 bps
#10SPCX0.71 bps
#25SP5000.13 bps
#50MUU5.65 bps
#100INTW1.73 bps
#144COHR2.60 bps
#200MON6.08 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at COHR's best price?

L1 liquidity

$415 at the best bid and ask on Binance USDT, on average, thinner than 84% of the 200 most traded perps.

#1BTC$656.4K
#2ETH$269.0K
#3SOXL$87.6K
#5SOL$157.2K
#10SPCX$17.6K
#25SP500$111.9K
#50MUU$21.2K
#100INTW$1.3K
#144COHR$415
#200MON$2.3K

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is COHR's book leaning?

L2 imbalance

Leaned to the bid in 12 of 24 hours on Binance USDT; 50% bids over the day.

71% bid029% bid

00:50 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does COHR trade?

OHLCV

Binance USDT took 87% of $32.7M traded in 24 h.

volume sharespread

Binance USDT87%2.60
OKX USDT7.9%4.20
Hyperliquid para USDC5.0%26.3

ohlcv.volume_notionaleach contract · 24 h

Does COHR trade away from its index?

Basis

6.36 bps below its index on Binance USDT now; 0.071 bps below to 12.9 bps above over 24 h.

+12.9 bps0−12.9 bps

00:50 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in COHR?

Open interest

$8.2M open across 3 contracts: +2.7% in contracts, −8.0% in dollars over 24 h.

$9.0M$8.1M

00:50 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on COHR?

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 para USDC+0.0008%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

COHR's 3 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-COHR-USDT:USDT	213.060	-10.49%	$28.4M	$6.0M	+0.0000%	2.60	Charts →
OKX USDTperpetual-COHR-USDT:USDT	213.150	-10.45%	$2.6M	$1.2M	+0.0000%	4.20	Charts →
Hyperliquid para USDCperpetual-PARA:COHR-USDC:USDC	213.790	-10.57%	$1.6M	$1.0M	+0.0008%	26.3	Charts →

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

Every chart for COHR →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: COHR on Binance, OKX and Hyperliquid
# 5m bars, 2025-11-13 to 2026-11-13. 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, 13),
    end_date=date(2026, 11, 13),
)
CONTRACTS = [
    ("binance-futures", "perpetual-COHR-USDT:USDT"),
    ("okx-perps", "perpetual-COHR-USDT:USDT"),
    ("hyperliquid-perps", "perpetual-PARA:COHR-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-COHR-USDT:USDT

213.060

-10.49%

$28.4M

$6.0M

+0.0000%

2.60

Charts →

OKX USDTperpetual-COHR-USDT:USDT

213.150

-10.45%

$2.6M

$1.2M

+0.0000%

4.20

Charts →

Hyperliquid para USDCperpetual-PARA:COHR-USDC:USDC

213.790

-10.57%

$1.6M

$1.0M

+0.0008%

26.3

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: COHR on Binance, OKX and Hyperliquid # 5m bars, 2025-11-13 to 2026-11-13. 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, 13), end_date=date(2026, 11, 13), ) CONTRACTS = [ ("binance-futures", "perpetual-COHR-USDT:USDT"), ("okx-perps", "perpetual-COHR-USDT:USDT"), ("hyperliquid-perps", "perpetual-PARA:COHR-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, )