HPE perps

Perp · Binance, OKX · #516 by volume

47.540-6.20% 24h

Binance USDT · 24h 47.010 – 51.410

24h volume: $1.9M; #516 of 914
Open interest: $461.0K; −2.1% contracts · 24h
Spread: 6.25 bps; median · 24h
Size at best price: $395; mean · 24h
Net taker flow: −$117.9K; every contract · 24h
Funding: −0.0833%; per period · BIN

Aperiodic metrics · HPE · 24 h

Every metric on HPE, bar by bar →

Are takers buying or selling HPE?

Flow

Takers sold $117.8K more than they bought on Binance and OKX over 24 h; the heaviest hour, 14:25 UTC, saw $35.6K.

+$35.6K0−$35.6K

23:25 UTCnow

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

What does it cost to cross HPE's spread?

L1 liquidity

6.25 bps median on Binance USDT, wider than 89% 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
#200AIN2.70 bps
#516HPE6.25 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at HPE's best price?

L1 liquidity

$395 at the best bid and ask on Binance USDT, on average, thinner than 88% 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
#200AIN$180
#516HPE$395

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is HPE's book leaning?

L2 imbalance

Leaned to the bid in 13 of 24 hours on Binance USDT; 51% bids over the day.

68% bid032% bid

23:25 UTCnow

l2_imbalance.imbalance_ratio_10Binance USDT · top 10 levels · hourly

Where does HPE trade?

OHLCV

Binance USDT took 91% of $1.9M traded in 24 h.

volume sharespread

Binance USDT91%6.25
OKX USDT9.0%8.45

ohlcv.volume_notionaleach contract · 24 h

Does HPE trade away from its index?

Basis

21.5 bps below its index on Binance USDT now; 51.7 bps below to 14.9 bps above over 24 h.

+51.7 bps0−51.7 bps

23:25 UTCnow

basis.basis_bpsBinance USDT · hourly

Is leverage building in HPE?

Open interest

$461.0K open across 2 contracts: −2.1% in contracts, −9.1% in dollars over 24 h.

$521.7K$460.7K

23:25 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on HPE?

Funding

Longs pay on 0 of 2 contracts; Binance USDT charges −0.0833% a period.

Binance USDT−0.0833%
OKX USDT−0.0652%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

HPE's 2 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Binance USDTperpetual-HPE-USDT:USDT	47.540	-6.20%	$1.7M	$295.4K	−0.0833%	6.25	Charts →
OKX USDTperpetual-HPE-USDT:USDT	47.590	-6.06%	$171.8K	$165.6K	−0.0652%	8.45	Charts →

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

Every chart for HPE →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

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

47.540

-6.20%

$1.7M

$295.4K

−0.0833%

6.25

Charts →

OKX USDTperpetual-HPE-USDT:USDT

47.590

-6.06%

$171.8K

$165.6K

−0.0652%

8.45

Charts →

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