Ethereum Classic perpsETC

Crypto perp · Binance, OKX, Hyperliquid · #154 by volume

6.411-3.55% 24h

Binance USDT · 24h 6.352 – 6.679

24h volume: $28.0M; #154 of 914
Open interest: $24.0M; −0.6% contracts · 24h
Spread: 1.53 bps; median · 24h
Size at best price: $3.2K; mean · 24h
Net taker flow: −$1.1M; every contract · 24h
Funding: +0.0012%; per period · BIN

Aperiodic metrics · ETC · 24 h

Are takers buying or selling ETC?

Takers sold $1.0M more than they bought on Binance, OKX and Hyperliquid over 24 h; the heaviest hour, 03:25 UTC, saw $623.0K.

+$623.0K0−$623.0K

23:25 UTCnow

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

What does it cost to cross ETC's spread?

L1 liquidity

1.53 bps median on Binance USDT, tighter than 61% of the 200 most traded perps.

#1BTC0.015 bps
#2ETH0.051 bps
#3SOXL1.56 bps
#5SOL1.25 bps
#10AKE3.18 bps
#25XYZ:XYZ1000.35 bps
#50MUU5.64 bps
#100MVLL8.76 bps
#154ETC1.53 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at ETC's best price?

L1 liquidity

$3.2K at the best bid and ask on Binance USDT, on average, deeper than 56% of the 200 most traded perps.

#1BTC$651.7K
#2ETH$269.8K
#3SOXL$86.9K
#5SOL$157.5K
#10AKE$553
#25XYZ:XYZ100$165.1K
#50MUU$22.4K
#100MVLL$13.7K
#154ETC$3.2K
#200AIN$180

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is ETC's book leaning?

L2 imbalance

Leaned to the ask in 22 of 24 hours on Binance USDT; 47% bids over the day.

58% bid042% bid

23:25 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does ETC trade?

OHLCV

Binance USDT took 74% of $28.0M traded in 24 h.

volume sharespread

Binance USDT74%1.53
OKX USDT23%1.53
Hyperliquid USDC1.4%10.8
OKX USD1.2%6.13

ohlcv.volume_notionaleach contract · 24 h

Does ETC trade away from its index?

Basis

2.45 bps below its index on Binance USDT now; 3.90 bps to 8.64 bps below over 24 h.

+8.64 bps0−8.64 bps

23:25 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in ETC?

Open interest

$24.0M open across 4 contracts: −0.6% in contracts, −4.5% in dollars over 24 h.

$23.3M$22.2M

23:25 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on ETC?

Funding

Longs pay on 3 of 4 contracts; Binance USDT charges +0.0012% a period (Hyperliquid’s are hourly).

Binance USDT+0.0012%
OKX USDT−0.0104%
Hyperliquid USDC+0.0013%
OKX USD+0.0100%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

ETC's 4 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-ETC-USDT:USDT	6.411	-3.55%	$20.8M	$14.9M	+0.0012%	1.53	Charts →
OKX USDTperpetual-ETC-USDT:USDT	6.409	-3.57%	$6.5M	$5.2M	−0.0104%	1.53	Charts →
Hyperliquid USDCperpetual-ETC-USDC:USDC	6.402	-3.78%	$395.4K	$2.2M	+0.0013%	10.8	Charts →
OKX USDperpetual-ETC-USD:ETC	6.396	-3.67%	$330.2K	$1.8M	+0.0100%	6.13	Charts →

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

Every chart for ETC →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

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

6.411

-3.55%

$20.8M

$14.9M

+0.0012%

1.53

Charts →

OKX USDTperpetual-ETC-USDT:USDT

6.409

-3.57%

$6.5M

$5.2M

−0.0104%

1.53

Charts →

Hyperliquid USDCperpetual-ETC-USDC:USDC

6.402

-3.78%

$395.4K

$2.2M

+0.0013%

10.8

Charts →

OKX USDperpetual-ETC-USD:ETC

6.396

-3.67%

$330.2K

$1.8M

+0.0100%

6.13

Charts →

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