S&P 500 perpsSP500

Index perp · Hyperliquid, OKX · #24 by volume

7,527.1-1.02% 24h

Hyperliquid xyz USDC · 24h 7,499.1 – 7,648.8

24h volume: $555.9M; #24 of 914
Open interest: $473.8M; −2.1% contracts · 24h
Spread: 0.13 bps; median · 24h
Size at best price: $105.3K; mean · 24h
Net taker flow: −$18.8M; every contract · 24h
Funding: −0.0052%; per period · HL

Aperiodic metrics · SP500 · 24 h

Every metric on SP500, bar by bar →

Are takers buying or selling SP500?

Flow

Takers sold $19.9M more than they bought on Hyperliquid and OKX over 24 h; the heaviest hour, 14:25 UTC, saw $11.4M.

+$11.4M0−$11.4M

23:25 UTCnow

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

What does it cost to cross SP500's spread?

L1 liquidity

0.13 bps median on Hyperliquid xyz USDC, tighter than 95% of the 200 most traded perps.

#1BTC0.015 bps
#2ETH0.051 bps
#3SOXL1.56 bps
#5SOL1.25 bps
#10AKE3.18 bps
#24SP5000.13 bps
#25XYZ:XYZ1000.35 bps
#50MUU5.64 bps
#100MVLL8.76 bps
#200AIN2.70 bps

l1_liquidity.spread_bpsbusiest contract · median · 24 h

How much size waits at SP500's best price?

L1 liquidity

$105.3K at the best bid and ask on Hyperliquid xyz USDC, on average, deeper than 94% of the 200 most traded perps.

#1BTC$651.7K
#2ETH$269.8K
#3SOXL$86.9K
#5SOL$157.5K
#10AKE$553
#24SP500$105.3K
#25XYZ:XYZ100$165.1K
#50MUU$22.4K
#100MVLL$13.7K
#200AIN$180

l1_liquidity.total_dollar_depthbusiest contract · mean · 24 h

Which way is SP500's book leaning?

L2 imbalance

Leaned to the ask in 18 of 24 hours on Hyperliquid xyz USDC; 48% bids over the day.

64% bid036% bid

23:25 UTCnow

l2_imbalance.imbalance_ratio_10Hyperliquid xyz USDC · top 10 levels · hourly

Where does SP500 trade?

OHLCV

Hyperliquid xyz USDC took 100% of $555.9M traded in 24 h.

volume sharespread

Hyperliquid xyz USDC100%0.13
OKX USDT0.0%2.37

ohlcv.volume_notionaleach contract · 24 h

Does SP500 trade away from its index?

Basis

8.50 bps below its index on Hyperliquid xyz USDC now; 0.30 bps to 5.67 bps below over 24 h.

+5.67 bps0−5.67 bps

23:25 UTCnow

basis.basis_bpsHyperliquid xyz USDC · hourly

Is leverage building in SP500?

Open interest

$473.8M open across 2 contracts: −2.1% in contracts, −2.5% in dollars over 24 h.

$487.9M$449.0M

23:25 UTCnow

open_interest.open_interestbusiest contract on each venue · hourly

Who pays funding on SP500?

Funding

Longs pay on 0 of 2 contracts; Hyperliquid xyz USDC charges −0.0052% a period (Hyperliquid’s are hourly).

Hyperliquid xyz USDC−0.0052%
OKX USDT+0.0000%

← shorts paylongs pay →

funding.funding_rateeach contract · per funding period · now

SP500's 2 contracts · now

Named by Atlas →

Contract	Price	24h	Volume 24h	Open interest	Funding	Spread	Charts
Hyperliquid xyz USDCperpetual-XYZ:SP500-USDC:USDC	7,527.1	-1.02%	$555.8M	$473.5M	−0.0052%	0.13	Charts →
OKX USDTperpetual-US500-USDT:USDT	7,531.6	-1.10%	$146.5K	$323.1K	+0.0000%	2.37	Charts →

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

Every chart for SP500 →

Python

import os
from datetime import date

from aperiodic import get_derivative_metrics, get_metrics

# aperiodic.io/markets: SP500 on Hyperliquid 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 = [
    ("hyperliquid-perps", "perpetual-XYZ:SP500-USDC:USDC"),
    ("okx-perps", "perpetual-US500-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

Hyperliquid xyz USDCperpetual-XYZ:SP500-USDC:USDC

7,527.1

-1.02%

$555.8M

$473.5M

−0.0052%

0.13

Charts →

OKX USDTperpetual-US500-USDT:USDT

7,531.6

-1.10%

$146.5K

$323.1K

+0.0000%

2.37

Charts →

import os from datetime import date from aperiodic import get_derivative_metrics, get_metrics # aperiodic.io/markets: SP500 on Hyperliquid 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 = [ ("hyperliquid-perps", "perpetual-XYZ:SP500-USDC:USDC"), ("okx-perps", "perpetual-US500-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, )