XYZ:JP225 perps

Perp · Hyperliquid · #660 by volume

61,001.0-0.60% 24h

Hyperliquid xyz USDC · 24h 60,144.0 – 61,947.0

24h volume: $1.0M; #660 of 914
Open interest: $2.1M; −14.9% contracts · 24h
Spread: 5.29 bps; median · 24h
Size at best price: $11.7K; mean · 24h
Net taker flow: −$207.1K; every contract · 24h
Funding: +0.0025%; per period · HL

Aperiodic metrics · XYZ:JP225 · 24 h

Every metric on XYZ:JP225, bar by bar →

Are takers buying or selling XYZ:JP225?

Flow

Takers sold $213.5K more than they bought on Hyperliquid xyz USDC over 24 h; the heaviest hour, 07:25 UTC, saw $70.9K.

+$70.9K0−$70.9K

23:25 UTCnow

flow.volume_delta_notionalbusiest contract · hourly · 24 h

What does it cost to cross XYZ:JP225's spread?

L1 liquidity

5.29 bps median on Hyperliquid xyz USDC, wider than 85% 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
#660XYZ:JP2255.29 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at XYZ:JP225's best price?

L1 liquidity

$11.7K at the best bid and ask on Hyperliquid xyz USDC, on average, deeper than 76% 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
#660XYZ:JP225$11.7K

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is XYZ:JP225's book leaning?

L2 imbalance

Leaned to the ask in 13 of 24 hours on Hyperliquid xyz USDC; 50% bids over the day.

69% bid031% bid

23:25 UTCnow

l2_imbalance.imbalance_ratio_10Hyperliquid xyz USDC · top 10 levels · hourly

Does XYZ:JP225 trade away from its index?

Basis

17.6 bps above its index on Hyperliquid xyz USDC now; 1.15 bps below to 3.08 bps above over 24 h.

+3.08 bps0−3.08 bps

23:25 UTCnow

basis.basis_bpsHyperliquid xyz USDC · hourly

Is leverage building in XYZ:JP225?

Open interest

$2.1M open across 1 contract: −14.9% in contracts, −12.4% in dollars over 24 h.

$2.4M$2.1M

23:25 UTCnow

open_interest.open_interestbusiest contract · hourly

Who pays funding on XYZ:JP225?

Funding

Longs pay +0.0025% a period on Hyperliquid xyz USDC; between +0.0001% and +0.0013% over 24 h.

+0.0013%0−0.0013%

23:25 UTCnow

funding.funding_rateHyperliquid xyz USDC · hourly

XYZ:JP225's contract · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Hyperliquid xyz USDCperpetual-XYZ:JP225-USDC:USDC	61,001.0	-0.60%	$1.0M	$2.1M	+0.0025%	5.29	Charts →

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

Every chart for XYZ:JP225 →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: XYZ:JP225 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:JP225-USDC:USDC",
    **PERIOD,
)

l1_liquidity = get_metrics(
    api_key=API_KEY,
    metric="l1_liquidity",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:JP225-USDC:USDC",
    **PERIOD,
)

l2_imbalance = get_metrics(
    api_key=API_KEY,
    metric="l2_imbalance",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:JP225-USDC:USDC",
    **PERIOD,
)

basis = get_derivative_metrics(
    api_key=API_KEY,
    metric="basis",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:JP225-USDC:USDC",
    **PERIOD,
)

open_interest = get_derivative_metrics(
    api_key=API_KEY,
    metric="open_interest",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:JP225-USDC:USDC",
    **PERIOD,
)

funding = get_derivative_metrics(
    api_key=API_KEY,
    metric="funding",
    exchange="hyperliquid-perps",
    symbol="perpetual-XYZ:JP225-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:JP225-USDC:USDC

61,001.0

-0.60%

$1.0M

$2.1M

+0.0025%

5.29

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: XYZ:JP225 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:JP225-USDC:USDC", **PERIOD, ) l1_liquidity = get_metrics( api_key=API_KEY, metric="l1_liquidity", exchange="hyperliquid-perps", symbol="perpetual-XYZ:JP225-USDC:USDC", **PERIOD, ) l2_imbalance = get_metrics( api_key=API_KEY, metric="l2_imbalance", exchange="hyperliquid-perps", symbol="perpetual-XYZ:JP225-USDC:USDC", **PERIOD, ) basis = get_derivative_metrics( api_key=API_KEY, metric="basis", exchange="hyperliquid-perps", symbol="perpetual-XYZ:JP225-USDC:USDC", **PERIOD, ) open_interest = get_derivative_metrics( api_key=API_KEY, metric="open_interest", exchange="hyperliquid-perps", symbol="perpetual-XYZ:JP225-USDC:USDC", **PERIOD, ) funding = get_derivative_metrics( api_key=API_KEY, metric="funding", exchange="hyperliquid-perps", symbol="perpetual-XYZ:JP225-USDC:USDC", **PERIOD, )