XYZ:NET perps

Perp · Hyperliquid · #594 by volume

304.510-4.89% 24h

Hyperliquid xyz USDC · 24h 300.910 – 327.850

24h volume: $1.4M; #594 of 914
Open interest: $1.9M; −4.7% contracts · 24h
Spread: 9.50 bps; median · 24h
Size at best price: $4.3K; mean · 24h
Net taker flow: −$60.6K; every contract · 24h
Funding: −0.0049%; per period · HL

Aperiodic metrics · XYZ:NET · 24 h

Every metric on XYZ:NET, bar by bar →

Are takers buying or selling XYZ:NET?

Flow

Takers sold $60.5K more than they bought on Hyperliquid xyz USDC over 24 h; the heaviest hour, 14:25 UTC, saw $67.6K.

+$67.6K0−$67.6K

23:25 UTCnow

flow.volume_delta_notionalbusiest contract · hourly · 24 h

What does it cost to cross XYZ:NET's spread?

L1 liquidity

9.50 bps median on Hyperliquid xyz USDC, wider than 97% 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
#594XYZ:NET9.50 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at XYZ:NET's best price?

L1 liquidity

$4.3K at the best bid and ask on Hyperliquid xyz USDC, on average, deeper than 62% 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
#594XYZ:NET$4.3K

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is XYZ:NET's book leaning?

L2 imbalance

Leaned to the bid in 13 of 24 hours on Hyperliquid xyz USDC; 52% bids over the day.

66% bid034% bid

23:25 UTCnow

l2_imbalance.imbalance_ratio_10Hyperliquid xyz USDC · top 10 levels · hourly

Does XYZ:NET trade away from its index?

Basis

0.99 bps below its index on Hyperliquid xyz USDC now; 15.6 bps below to 15.2 bps above over 24 h.

+15.6 bps0−15.6 bps

23:25 UTCnow

basis.basis_bpsHyperliquid xyz USDC · hourly

Is leverage building in XYZ:NET?

Open interest

$1.9M open across 1 contract: −4.7% in contracts, −9.6% in dollars over 24 h.

$2.2M$1.9M

23:25 UTCnow

open_interest.open_interestbusiest contract · hourly

Who pays funding on XYZ:NET?

Funding

Shorts pay −0.0049% a period on Hyperliquid xyz USDC; between −0.0099% and +0.0059% over 24 h.

+0.0099%0−0.0099%

23:25 UTCnow

funding.funding_rateHyperliquid xyz USDC · hourly

XYZ:NET's contract · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Hyperliquid xyz USDCperpetual-XYZ:NET-USDC:USDC	304.510	-4.89%	$1.4M	$1.9M	−0.0049%	9.50	Charts →

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

Every chart for XYZ:NET →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: XYZ:NET on 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).
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),
)

flow = get_metrics(
    api_key=API_KEY,
    metric="flow",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:NET-USDC:USDC",
    **PERIOD,
)

l1_liquidity = get_metrics(
    api_key=API_KEY,
    metric="l1_liquidity",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:NET-USDC:USDC",
    **PERIOD,
)

l2_imbalance = get_metrics(
    api_key=API_KEY,
    metric="l2_imbalance",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:NET-USDC:USDC",
    **PERIOD,
)

basis = get_derivative_metrics(
    api_key=API_KEY,
    metric="basis",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:NET-USDC:USDC",
    **PERIOD,
)

open_interest = get_derivative_metrics(
    api_key=API_KEY,
    metric="open_interest",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:NET-USDC:USDC",
    **PERIOD,
)

funding = get_derivative_metrics(
    api_key=API_KEY,
    metric="funding",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:NET-USDC:USDC",
    **PERIOD,
)

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

Contract

Price

24h

Volume 24h

Open interest

Funding

Spread

Hyperliquid xyz USDCperpetual-XYZ:NET-USDC:USDC

304.510

-4.89%

$1.4M

$1.9M

−0.0049%

9.50

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: XYZ:NET on 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). 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), ) flow = get_metrics( api_key=API_KEY, metric="flow", exchange="hyperliquid-perps", symbol="perpetual-XYZ:NET-USDC:USDC", **PERIOD, ) l1_liquidity = get_metrics( api_key=API_KEY, metric="l1_liquidity", exchange="hyperliquid-perps", symbol="perpetual-XYZ:NET-USDC:USDC", **PERIOD, ) l2_imbalance = get_metrics( api_key=API_KEY, metric="l2_imbalance", exchange="hyperliquid-perps", symbol="perpetual-XYZ:NET-USDC:USDC", **PERIOD, ) basis = get_derivative_metrics( api_key=API_KEY, metric="basis", exchange="hyperliquid-perps", symbol="perpetual-XYZ:NET-USDC:USDC", **PERIOD, ) open_interest = get_derivative_metrics( api_key=API_KEY, metric="open_interest", exchange="hyperliquid-perps", symbol="perpetual-XYZ:NET-USDC:USDC", **PERIOD, ) funding = get_derivative_metrics( api_key=API_KEY, metric="funding", exchange="hyperliquid-perps", symbol="perpetual-XYZ:NET-USDC:USDC", **PERIOD, )